[Bioc-devel] exptData(SummarizedExperiment)

Hi Tim,

The SummarizedExperiment class is being replaced with the
RangedSummarizedExperiment class from the new SummarizedExperiment
package. This is a work-in-progress and the name and internal
representation of the RangedSummarizedExperiment class are not
finalized yet. The main goal for now is to move all the
SummarizedExperiment stuff from GenomicRanges to its own package.

Anyway, metadata() is the replacement for exptData() on
RangedSummarizedExperiment objects. It's on my list to add
an exptData method for backward compatibility.

Cheers,
H.


On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

who determined that breaking this would be a good idea?!?

R> ?SummarizedExperiment
Help on topic 'SummarizedExperiment' was found in the following
packages:

   Package               Library
   GenomicRanges         /home/tim/R/x86_64-pc-linux-gnu-library/3.2
   SummarizedExperiment
                       /home/tim/R/x86_64-pc-linux-gnu-library/3.2

  R> nrows <- 200; ncols <- 6
R>        counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
R>        rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)),
+                           IRanges(floor(runif(200, 1e5, 1e6)),
width=100),
+                           strand=sample(c("+", "-"), 200, TRUE))
R>        colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),
+                             row.names=LETTERS[1:6])
R>        sset <- SummarizedExperiment(assays=SimpleList(counts=counts),
+                       rowRanges=rowRanges, colData=colData)
R>        sset
class: RangedSummarizedExperiment
dim: 200 6
metadata(0):
assays(1): counts
rownames: NULL
rowRanges metadata column names(0):
colnames(6): A B ... E F
colData names(1): Treatment
R>        assayNames(sset)
[1] "counts"
R>        assays(sset) <- endoapply(assays(sset), asinh)
R>        head(assay(sset))
         A    B    C    D    E    F
[1,] 6.89 8.81 9.46 9.20 8.88 9.44
[2,] 5.07 9.70 4.08 7.47 8.91 5.64
[3,] 9.88 9.84 8.95 9.07 9.86 9.06
[4,] 9.89 8.88 8.92 8.05 8.46 9.51
[5,] 9.75 8.48 4.73 9.86 8.43 9.86
[6,] 9.29 9.13 9.80 9.77 9.50 8.40
R> exptData(sset)
Error in (function (classes, fdef, mtable)  :
   unable to find an inherited method for function 'exptData' for
signature
'"RangedSummarizedExperiment"'



It's one of those things that's a handy place to put data when you need to
carry it around for the same set of people/subjects but don't have a handy
multidimensional container for it.  So it's a bit of a drag that it now
breaks...


Bonus:

R> ?"exptData,SummarizedExperiment-method"

SummarizedExperiment-class    package:GenomicRanges    R Documentation

SummarizedExperiment instances

Description:

      The SummarizedExperiment class is a matrix-like container where
      rows represent ranges of interest (as a 'GRanges or
      GRangesList-class') and columns represent samples (with sample
      data summarized as a 'DataFrame-class'). A 'SummarizedExperiment'
      contains one or more assays, each represented by a matrix-like
      object of numeric or other mode.




R> sessionInfo()
R version 3.2.0 (2015-04-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 15.04

locale:
  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
  [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
  [1] grid      stats4    parallel  stats     graphics  grDevices datasets
  [8] utils     methods   base

other attached packages:
  [1] disintegrator_0.4.8         vegan_2.2-1
  [3] permute_0.8-3               CCAGFA_1.0.4
  [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
  [7] igraph_0.7.1                corrplot_0.73
  [9] marray_1.47.0               AnnotationDbi_1.31.6
[11] MotifDb_1.10.0              PWMEnrich_4.5.0
[13] SCAN.UPC_2.10.0             sva_3.15.0
[15] genefilter_1.51.0           mgcv_1.8-6
[17] nlme_3.1-120                affyio_1.37.0
[19] affy_1.47.0                 oligo_1.33.0
[21] oligoClasses_1.31.0         SRAdb_1.23.0
[23] RCurl_1.95-4.6              bitops_1.0-6
[25] graph_1.47.0                quadprog_1.5-5
[27] mclust_5.0.1                ConsensusClusterPlus_1.23.0
[29] simulatorZ_1.5.1            CoxBoost_1.4
[31] prodlim_1.5.1               rsig_1.0
[33] survival_2.38-1             DMRcate_1.5.42
[35] matrixStats_0.14.0          rtracklayer_1.29.5
[37] Matrix_1.2-0                qvalue_2.1.0
[39] impute_1.43.0               DMRcatedata_1.5.0
[41] minfi_1.15.3                bumphunter_1.8.0
[43] locfit_1.5-9.1              iterators_1.0.7
[45] foreach_1.4.2               Biostrings_2.37.2
[47] XVector_0.9.1               SummarizedExperiment_0.1.1
[49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
[51] IRanges_2.3.8               S4Vectors_0.7.2
[53] lattice_0.20-31             limma_3.25.3
[55] ks_1.9.4                    rgl_0.95.1247
[57] mvtnorm_1.0-2               misc3d_0.8-4
[59] KernSmooth_2.23-14          dplyr_0.4.1
[61] GEOmetadb_1.29.0            RSQLite_1.0.0
[63] DBI_0.3.1                   GEOquery_2.35.4
[65] Biobase_2.29.1              BiocGenerics_0.15.0
[67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
[69] magrittr_1.5                gtools_3.4.2

loaded via a namespace (and not attached):
  [1] Hmisc_3.16-0            plyr_1.8.2              splines_3.2.0
  [4] BiocParallel_1.3.9      ggplot2_1.0.1           digest_0.6.8
  [7] SuppDists_1.1-9.1       gdata_2.16.1            GMD_0.3.3
[10] checkmate_1.5.2         BBmisc_1.9              cluster_2.0.1
[13] annotate_1.47.0         siggenes_1.43.0         colorspace_1.2-6
[16] tcltk_3.2.0             registry_0.2            gtable_0.1.2
[19] zlibbioc_1.15.0         RGCCA_2.0               evd_2.3-0
[22] scales_0.2.4            futile.options_1.0.0    pheatmap_1.0.2
[25] rngtools_1.2.4          Rcpp_0.11.6             xtable_1.7-4
[28] foreign_0.8-63          bit_1.1-12              preprocessCore_1.31.0
[31] Formula_1.2-1           lava_1.4.0              glmnet_2.0-2
[34] httr_0.6.1              gplots_2.17.0           RColorBrewer_1.1-2
[37] acepack_1.3-3.3         ff_2.2-13               reshape_0.8.5
[40] XML_3.98-1.1            nnet_7.3-9              reshape2_1.4.1
[43] munsell_0.4.2           tools_3.2.0             stringr_1.0.0
[46] bootstrap_2015.2        beanplot_1.2            caTools_1.17.1
[49] doRNG_1.6               nor1mix_1.2-0           biomaRt_2.25.1
[52] stringi_0.4-1           superpc_1.09            futile.logger_1.4.1
[55] GenomicFeatures_1.21.2  survcomp_1.19.0         gbm_2.1.1
[58] survivalROC_1.0.3       multtest_2.25.0         R6_2.0.1
[61] latticeExtra_0.6-26     gridExtra_0.9.1         affxparser_1.41.2
[64] codetools_0.2-11        lambda.r_1.1.7          seqLogo_1.35.0
[67] MASS_7.3-40             assertthat_0.1          proto_0.3-10
[70] pkgmaker_0.22           GenomicAlignments_1.5.8 Rsamtools_1.21.4
[73] mixOmics_5.0-4          rpart_4.1-9             base64_1.1
[76] illuminaio_0.11.0       rmeta_2.16




Statistics is the grammar of science.
Karl Pearson <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

        [[alternative HTML version deleted]]

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

Splitting stuff into different packages is good for modularity, but
tough on the mind of the user. What about having some sort of "meta"
package that simply loads the core infrastructure packages? Named
something simple like "Genomics" or "GenomicsCore".

On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Tim,

    The SummarizedExperiment class is being replaced with the
    RangedSummarizedExperiment class from the new SummarizedExperiment
    package. This is a work-in-progress and the name and internal
    representation of the RangedSummarizedExperiment class are not
    finalized yet. The main goal for now is to move all the
    SummarizedExperiment stuff from GenomicRanges to its own package.

    Anyway, metadata() is the replacement for exptData() on
    RangedSummarizedExperiment objects. It's on my list to add
    an exptData method for backward compatibility.

    Cheers,
    H.


    On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

        who determined that breaking this would be a good idea?!?

        R> ?SummarizedExperiment
        Help on topic 'SummarizedExperiment' was found in the following
        packages:

            Package               Library
            GenomicRanges
          /home/tim/R/x86_64-pc-linux-gnu-library/3.2
            SummarizedExperiment
                                /home/tim/R/x86_64-pc-linux-gnu-library/3.2

           R> nrows <- 200; ncols <- 6
        R>        counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
        R>        rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)),
        +                           IRanges(floor(runif(200, 1e5, 1e6)),
        width=100),
        +                           strand=sample(c("+", "-"), 200, TRUE))
        R>        colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),
        +                             row.names=LETTERS[1:6])
        R>        sset <-
        SummarizedExperiment(assays=SimpleList(counts=counts),
        +                       rowRanges=rowRanges, colData=colData)
        R>        sset
        class: RangedSummarizedExperiment
        dim: 200 6
        metadata(0):
        assays(1): counts
        rownames: NULL
        rowRanges metadata column names(0):
        colnames(6): A B ... E F
        colData names(1): Treatment
        R>        assayNames(sset)
        [1] "counts"
        R>        assays(sset) <- endoapply(assays(sset), asinh)
        R>        head(assay(sset))
                  A    B    C    D    E    F
        [1,] 6.89 8.81 9.46 9.20 8.88 9.44
        [2,] 5.07 9.70 4.08 7.47 8.91 5.64
        [3,] 9.88 9.84 8.95 9.07 9.86 9.06
        [4,] 9.89 8.88 8.92 8.05 8.46 9.51
        [5,] 9.75 8.48 4.73 9.86 8.43 9.86
        [6,] 9.29 9.13 9.80 9.77 9.50 8.40
        R> exptData(sset)
        Error in (function (classes, fdef, mtable)  :
            unable to find an inherited method for function 'exptData'
        for signature
        '"RangedSummarizedExperiment"'



        It's one of those things that's a handy place to put data when
        you need to
        carry it around for the same set of people/subjects but don't
        have a handy
        multidimensional container for it.  So it's a bit of a drag that
        it now
        breaks...


        Bonus:

        R> ?"exptData,SummarizedExperiment-method"

        SummarizedExperiment-class    package:GenomicRanges    R
        Documentation

        SummarizedExperiment instances

        Description:

               The SummarizedExperiment class is a matrix-like container
        where
               rows represent ranges of interest (as a 'GRanges or
               GRangesList-class') and columns represent samples (with
        sample
               data summarized as a 'DataFrame-class'). A
        'SummarizedExperiment'
               contains one or more assays, each represented by a
        matrix-like
               object of numeric or other mode.




        R> sessionInfo()
        R version 3.2.0 (2015-04-16)
        Platform: x86_64-pc-linux-gnu (64-bit)
        Running under: Ubuntu 15.04

        locale:
           [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
           [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
           [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
           [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
           [9] LC_ADDRESS=C               LC_TELEPHONE=C
        [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

        attached base packages:
           [1] grid      stats4    parallel  stats     graphics
        grDevices datasets
           [8] utils     methods   base

        other attached packages:
           [1] disintegrator_0.4.8         vegan_2.2-1
           [3] permute_0.8-3               CCAGFA_1.0.4
           [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
           [7] igraph_0.7.1                corrplot_0.73
           [9] marray_1.47.0               AnnotationDbi_1.31.6
        [11] MotifDb_1.10.0              PWMEnrich_4.5.0
        [13] SCAN.UPC_2.10.0             sva_3.15.0
        [15] genefilter_1.51.0           mgcv_1.8-6
        [17] nlme_3.1-120                affyio_1.37.0
        [19] affy_1.47.0                 oligo_1.33.0
        [21] oligoClasses_1.31.0         SRAdb_1.23.0
        [23] RCurl_1.95-4.6              bitops_1.0-6
        [25] graph_1.47.0                quadprog_1.5-5
        [27] mclust_5.0.1                ConsensusClusterPlus_1.23.0
        [29] simulatorZ_1.5.1            CoxBoost_1.4
        [31] prodlim_1.5.1               rsig_1.0
        [33] survival_2.38-1             DMRcate_1.5.42
        [35] matrixStats_0.14.0          rtracklayer_1.29.5
        [37] Matrix_1.2-0                qvalue_2.1.0
        [39] impute_1.43.0               DMRcatedata_1.5.0
        [41] minfi_1.15.3                bumphunter_1.8.0
        [43] locfit_1.5-9.1              iterators_1.0.7
        [45] foreach_1.4.2               Biostrings_2.37.2
        [47] XVector_0.9.1               SummarizedExperiment_0.1.1
        [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
        [51] IRanges_2.3.8               S4Vectors_0.7.2
        [53] lattice_0.20-31             limma_3.25.3
        [55] ks_1.9.4                    rgl_0.95.1247
        [57] mvtnorm_1.0-2               misc3d_0.8-4
        [59] KernSmooth_2.23-14          dplyr_0.4.1
        [61] GEOmetadb_1.29.0            RSQLite_1.0.0
        [63] DBI_0.3.1                   GEOquery_2.35.4
        [65] Biobase_2.29.1              BiocGenerics_0.15.0
        [67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
        [69] magrittr_1.5                gtools_3.4.2

        loaded via a namespace (and not attached):
           [1] Hmisc_3.16-0            plyr_1.8.2              splines_3.2.0
           [4] BiocParallel_1.3.9      ggplot2_1.0.1           digest_0.6.8
           [7] SuppDists_1.1-9.1       gdata_2.16.1            GMD_0.3.3
        [10] checkmate_1.5.2         BBmisc_1.9              cluster_2.0.1
        [13] annotate_1.47.0         siggenes_1.43.0
          colorspace_1.2-6
        [16] tcltk_3.2.0             registry_0.2            gtable_0.1.2
        [19] zlibbioc_1.15.0         RGCCA_2.0               evd_2.3-0
        [22] scales_0.2.4            futile.options_1.0.0    pheatmap_1.0.2
        [25] rngtools_1.2.4          Rcpp_0.11.6             xtable_1.7-4
        [28] foreign_0.8-63          bit_1.1-12
        preprocessCore_1.31.0
        [31] Formula_1.2-1           lava_1.4.0              glmnet_2.0-2
        [34] httr_0.6.1              gplots_2.17.0
          RColorBrewer_1.1-2
        [37] acepack_1.3-3.3         ff_2.2-13               reshape_0.8.5
        [40] XML_3.98-1.1            nnet_7.3-9              reshape2_1.4.1
        [43] munsell_0.4.2           tools_3.2.0             stringr_1.0.0
        [46] bootstrap_2015.2        beanplot_1.2            caTools_1.17.1
        [49] doRNG_1.6               nor1mix_1.2-0           biomaRt_2.25.1
        [52] stringi_0.4-1           superpc_1.09
        futile.logger_1.4.1
        [55] GenomicFeatures_1.21.2  survcomp_1.19.0         gbm_2.1.1
        [58] survivalROC_1.0.3       multtest_2.25.0         R6_2.0.1
        [61] latticeExtra_0.6-26     gridExtra_0.9.1
          affxparser_1.41.2
        [64] codetools_0.2-11        lambda.r_1.1.7          seqLogo_1.35.0
        [67] MASS_7.3-40             assertthat_0.1          proto_0.3-10
        [70] pkgmaker_0.22           GenomicAlignments_1.5.8
        Rsamtools_1.21.4
        [73] mixOmics_5.0-4          rpart_4.1-9             base64_1.1
        [76] illuminaio_0.11.0       rmeta_2.16




        Statistics is the grammar of science.
        Karl Pearson <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

                 [[alternative HTML version deleted]]

Hi Michael,

On 05/11/2015 05:35 PM, Michael Lawrence wrote:

Splitting stuff into different packages is good for modularity, but
tough on the mind of the user. What about having some sort of "meta"
package that simply loads the core infrastructure packages? Named
something simple like "Genomics" or "GenomicsCore".

Don't know if we need this. For example, for all the
SummarizedExperiment use cases I ran into, the end-user generally
only needs to load the corresponding high-level package (DESeq2,
VariantAnnotation, minfi, GenomicAlignments, etc...) and that takes
care of loading all the low-level infrastructure packages.

H.

On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Tim,

    The SummarizedExperiment class is being replaced with the
    RangedSummarizedExperiment class from the new SummarizedExperiment
    package. This is a work-in-progress and the name and internal
    representation of the RangedSummarizedExperiment class are not
    finalized yet. The main goal for now is to move all the
    SummarizedExperiment stuff from GenomicRanges to its own package.

    Anyway, metadata() is the replacement for exptData() on
    RangedSummarizedExperiment objects. It's on my list to add
    an exptData method for backward compatibility.

    Cheers,
    H.


    On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

        who determined that breaking this would be a good idea?!?

        R> ?SummarizedExperiment
        Help on topic 'SummarizedExperiment' was found in the following
        packages:

            Package               Library
            GenomicRanges
          /home/tim/R/x86_64-pc-linux-gnu-library/3.2
            SummarizedExperiment

/home/tim/R/x86_64-pc-linux-gnu-library/3.2

           R> nrows <- 200; ncols <- 6
        R>        counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
        R>        rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)),
        +                           IRanges(floor(runif(200, 1e5, 1e6)),
        width=100),
        +                           strand=sample(c("+", "-"), 200, TRUE))
        R>        colData <- DataFrame(Treatment=rep(c("ChIP", "Input"),
3),
        +                             row.names=LETTERS[1:6])
        R>        sset <-
        SummarizedExperiment(assays=SimpleList(counts=counts),
        +                       rowRanges=rowRanges, colData=colData)
        R>        sset
        class: RangedSummarizedExperiment
        dim: 200 6
        metadata(0):
        assays(1): counts
        rownames: NULL
        rowRanges metadata column names(0):
        colnames(6): A B ... E F
        colData names(1): Treatment
        R>        assayNames(sset)
        [1] "counts"
        R>        assays(sset) <- endoapply(assays(sset), asinh)
        R>        head(assay(sset))
                  A    B    C    D    E    F
        [1,] 6.89 8.81 9.46 9.20 8.88 9.44
        [2,] 5.07 9.70 4.08 7.47 8.91 5.64
        [3,] 9.88 9.84 8.95 9.07 9.86 9.06
        [4,] 9.89 8.88 8.92 8.05 8.46 9.51
        [5,] 9.75 8.48 4.73 9.86 8.43 9.86
        [6,] 9.29 9.13 9.80 9.77 9.50 8.40
        R> exptData(sset)
        Error in (function (classes, fdef, mtable)  :
            unable to find an inherited method for function 'exptData'
        for signature
        '"RangedSummarizedExperiment"'



        It's one of those things that's a handy place to put data when
        you need to
        carry it around for the same set of people/subjects but don't
        have a handy
        multidimensional container for it.  So it's a bit of a drag that
        it now
        breaks...


        Bonus:

        R> ?"exptData,SummarizedExperiment-method"

        SummarizedExperiment-class    package:GenomicRanges    R
        Documentation

        SummarizedExperiment instances

        Description:

               The SummarizedExperiment class is a matrix-like container
        where
               rows represent ranges of interest (as a 'GRanges or
               GRangesList-class') and columns represent samples (with
        sample
               data summarized as a 'DataFrame-class'). A
        'SummarizedExperiment'
               contains one or more assays, each represented by a
        matrix-like
               object of numeric or other mode.




        R> sessionInfo()
        R version 3.2.0 (2015-04-16)
        Platform: x86_64-pc-linux-gnu (64-bit)
        Running under: Ubuntu 15.04

        locale:
           [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
           [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
           [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
           [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
           [9] LC_ADDRESS=C               LC_TELEPHONE=C
        [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

        attached base packages:
           [1] grid      stats4    parallel  stats     graphics
        grDevices datasets
           [8] utils     methods   base

        other attached packages:
           [1] disintegrator_0.4.8         vegan_2.2-1
           [3] permute_0.8-3               CCAGFA_1.0.4
           [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
           [7] igraph_0.7.1                corrplot_0.73
           [9] marray_1.47.0               AnnotationDbi_1.31.6
        [11] MotifDb_1.10.0              PWMEnrich_4.5.0
        [13] SCAN.UPC_2.10.0             sva_3.15.0
        [15] genefilter_1.51.0           mgcv_1.8-6
        [17] nlme_3.1-120                affyio_1.37.0
        [19] affy_1.47.0                 oligo_1.33.0
        [21] oligoClasses_1.31.0         SRAdb_1.23.0
        [23] RCurl_1.95-4.6              bitops_1.0-6
        [25] graph_1.47.0                quadprog_1.5-5
        [27] mclust_5.0.1                ConsensusClusterPlus_1.23.0
        [29] simulatorZ_1.5.1            CoxBoost_1.4
        [31] prodlim_1.5.1               rsig_1.0
        [33] survival_2.38-1             DMRcate_1.5.42
        [35] matrixStats_0.14.0          rtracklayer_1.29.5
        [37] Matrix_1.2-0                qvalue_2.1.0
        [39] impute_1.43.0               DMRcatedata_1.5.0
        [41] minfi_1.15.3                bumphunter_1.8.0
        [43] locfit_1.5-9.1              iterators_1.0.7
        [45] foreach_1.4.2               Biostrings_2.37.2
        [47] XVector_0.9.1               SummarizedExperiment_0.1.1
        [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
        [51] IRanges_2.3.8               S4Vectors_0.7.2
        [53] lattice_0.20-31             limma_3.25.3
        [55] ks_1.9.4                    rgl_0.95.1247
        [57] mvtnorm_1.0-2               misc3d_0.8-4
        [59] KernSmooth_2.23-14          dplyr_0.4.1
        [61] GEOmetadb_1.29.0            RSQLite_1.0.0
        [63] DBI_0.3.1                   GEOquery_2.35.4
        [65] Biobase_2.29.1              BiocGenerics_0.15.0
        [67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
        [69] magrittr_1.5                gtools_3.4.2

        loaded via a namespace (and not attached):
           [1] Hmisc_3.16-0            plyr_1.8.2
splines_3.2.0
           [4] BiocParallel_1.3.9      ggplot2_1.0.1
 digest_0.6.8
           [7] SuppDists_1.1-9.1       gdata_2.16.1            GMD_0.3.3
        [10] checkmate_1.5.2         BBmisc_1.9              cluster_2.0.1
        [13] annotate_1.47.0         siggenes_1.43.0
          colorspace_1.2-6
        [16] tcltk_3.2.0             registry_0.2            gtable_0.1.2
        [19] zlibbioc_1.15.0         RGCCA_2.0               evd_2.3-0
        [22] scales_0.2.4            futile.options_1.0.0
pheatmap_1.0.2
        [25] rngtools_1.2.4          Rcpp_0.11.6             xtable_1.7-4
        [28] foreign_0.8-63          bit_1.1-12
        preprocessCore_1.31.0
        [31] Formula_1.2-1           lava_1.4.0              glmnet_2.0-2
        [34] httr_0.6.1              gplots_2.17.0
          RColorBrewer_1.1-2
        [37] acepack_1.3-3.3         ff_2.2-13               reshape_0.8.5
        [40] XML_3.98-1.1            nnet_7.3-9
reshape2_1.4.1
        [43] munsell_0.4.2           tools_3.2.0             stringr_1.0.0
        [46] bootstrap_2015.2        beanplot_1.2
caTools_1.17.1
        [49] doRNG_1.6               nor1mix_1.2-0
 biomaRt_2.25.1
        [52] stringi_0.4-1           superpc_1.09
        futile.logger_1.4.1
        [55] GenomicFeatures_1.21.2  survcomp_1.19.0         gbm_2.1.1
        [58] survivalROC_1.0.3       multtest_2.25.0         R6_2.0.1
        [61] latticeExtra_0.6-26     gridExtra_0.9.1
          affxparser_1.41.2
        [64] codetools_0.2-11        lambda.r_1.1.7
seqLogo_1.35.0
        [67] MASS_7.3-40             assertthat_0.1          proto_0.3-10
        [70] pkgmaker_0.22           GenomicAlignments_1.5.8
        Rsamtools_1.21.4
        [73] mixOmics_5.0-4          rpart_4.1-9             base64_1.1
        [76] illuminaio_0.11.0       rmeta_2.16




        Statistics is the grammar of science.
        Karl Pearson <http://en.wikipedia.org/wiki/The_Grammar_of_Science

                 [[alternative HTML version deleted]]

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

It's more general than SummarizedExperiment. I think people would
appreciate a simple way to load the core, without having to remember,
for example, that VCF reading is in VariantAnnotation.

On Mon, May 11, 2015 at 9:51 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Michael,

    On 05/11/2015 05:35 PM, Michael Lawrence wrote:

        Splitting stuff into different packages is good for modularity, but
        tough on the mind of the user. What about having some sort of "meta"
        package that simply loads the core infrastructure packages? Named
        something simple like "Genomics" or "GenomicsCore".


    Don't know if we need this. For example, for all the
    SummarizedExperiment use cases I ran into, the end-user generally
    only needs to load the corresponding high-level package (DESeq2,
    VariantAnnotation, minfi, GenomicAlignments, etc...) and that takes
    care of loading all the low-level infrastructure packages.

    H.


        On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s
        <hpages at fredhutch.org <mailto:hpages at fredhutch.org>
        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>> wrote:

             Hi Tim,

             The SummarizedExperiment class is being replaced with the
             RangedSummarizedExperiment class from the new
        SummarizedExperiment
             package. This is a work-in-progress and the name and internal
             representation of the RangedSummarizedExperiment class are not
             finalized yet. The main goal for now is to move all the
             SummarizedExperiment stuff from GenomicRanges to its own
        package.

             Anyway, metadata() is the replacement for exptData() on
             RangedSummarizedExperiment objects. It's on my list to add
             an exptData method for backward compatibility.

             Cheers,
             H.


             On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

                 who determined that breaking this would be a good idea?!?

                 R> ?SummarizedExperiment
                 Help on topic 'SummarizedExperiment' was found in the
        following
                 packages:

                     Package               Library
                     GenomicRanges
                   /home/tim/R/x86_64-pc-linux-gnu-library/3.2
                     SummarizedExperiment

        /home/tim/R/x86_64-pc-linux-gnu-library/3.2

                    R> nrows <- 200; ncols <- 6
                 R>        counts <- matrix(runif(nrows * ncols, 1,
        1e4), nrows)
                 R>        rowRanges <- GRanges(rep(c("chr1", "chr2"),
        c(50, 150)),
                 +                           IRanges(floor(runif(200,
        1e5, 1e6)),
                 width=100),
                 +                           strand=sample(c("+", "-"),
        200, TRUE))
                 R>        colData <- DataFrame(Treatment=rep(c("ChIP",
        "Input"), 3),
                 +                             row.names=LETTERS[1:6])
                 R>        sset <-
                 SummarizedExperiment(assays=SimpleList(counts=counts),
                 +                       rowRanges=rowRanges,
        colData=colData)
                 R>        sset
                 class: RangedSummarizedExperiment
                 dim: 200 6
                 metadata(0):
                 assays(1): counts
                 rownames: NULL
                 rowRanges metadata column names(0):
                 colnames(6): A B ... E F
                 colData names(1): Treatment
                 R>        assayNames(sset)
                 [1] "counts"
                 R>        assays(sset) <- endoapply(assays(sset), asinh)
                 R>        head(assay(sset))
                           A    B    C    D    E    F
                 [1,] 6.89 8.81 9.46 9.20 8.88 9.44
                 [2,] 5.07 9.70 4.08 7.47 8.91 5.64
                 [3,] 9.88 9.84 8.95 9.07 9.86 9.06
                 [4,] 9.89 8.88 8.92 8.05 8.46 9.51
                 [5,] 9.75 8.48 4.73 9.86 8.43 9.86
                 [6,] 9.29 9.13 9.80 9.77 9.50 8.40
                 R> exptData(sset)
                 Error in (function (classes, fdef, mtable)  :
                     unable to find an inherited method for function
        'exptData'
                 for signature
                 '"RangedSummarizedExperiment"'



                 It's one of those things that's a handy place to put
        data when
                 you need to
                 carry it around for the same set of people/subjects but
        don't
                 have a handy
                 multidimensional container for it.  So it's a bit of a
        drag that
                 it now
                 breaks...


                 Bonus:

                 R> ?"exptData,SummarizedExperiment-method"

                 SummarizedExperiment-class    package:GenomicRanges    R
                 Documentation

                 SummarizedExperiment instances

                 Description:

                        The SummarizedExperiment class is a matrix-like
        container
                 where
                        rows represent ranges of interest (as a 'GRanges or
                        GRangesList-class') and columns represent
        samples (with
                 sample
                        data summarized as a 'DataFrame-class'). A
                 'SummarizedExperiment'
                        contains one or more assays, each represented by a
                 matrix-like
                        object of numeric or other mode.




                 R> sessionInfo()
                 R version 3.2.0 (2015-04-16)
                 Platform: x86_64-pc-linux-gnu (64-bit)
                 Running under: Ubuntu 15.04

                 locale:
                    [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
                    [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
                    [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
                    [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
                    [9] LC_ADDRESS=C               LC_TELEPHONE=C
                 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

                 attached base packages:
                    [1] grid      stats4    parallel  stats     graphics
                 grDevices datasets
                    [8] utils     methods   base

                 other attached packages:
                    [1] disintegrator_0.4.8         vegan_2.2-1
                    [3] permute_0.8-3               CCAGFA_1.0.4
                    [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
                    [7] igraph_0.7.1                corrplot_0.73
                    [9] marray_1.47.0               AnnotationDbi_1.31.6
                 [11] MotifDb_1.10.0              PWMEnrich_4.5.0
                 [13] SCAN.UPC_2.10.0             sva_3.15.0
                 [15] genefilter_1.51.0           mgcv_1.8-6
                 [17] nlme_3.1-120                affyio_1.37.0
                 [19] affy_1.47.0                 oligo_1.33.0
                 [21] oligoClasses_1.31.0         SRAdb_1.23.0
                 [23] RCurl_1.95-4.6              bitops_1.0-6
                 [25] graph_1.47.0                quadprog_1.5-5
                 [27] mclust_5.0.1
        ConsensusClusterPlus_1.23.0
                 [29] simulatorZ_1.5.1            CoxBoost_1.4
                 [31] prodlim_1.5.1               rsig_1.0
                 [33] survival_2.38-1             DMRcate_1.5.42
                 [35] matrixStats_0.14.0          rtracklayer_1.29.5
                 [37] Matrix_1.2-0                qvalue_2.1.0
                 [39] impute_1.43.0               DMRcatedata_1.5.0
                 [41] minfi_1.15.3                bumphunter_1.8.0
                 [43] locfit_1.5-9.1              iterators_1.0.7
                 [45] foreach_1.4.2               Biostrings_2.37.2
                 [47] XVector_0.9.1               SummarizedExperiment_0.1.1
                 [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
                 [51] IRanges_2.3.8               S4Vectors_0.7.2
                 [53] lattice_0.20-31             limma_3.25.3
                 [55] ks_1.9.4                    rgl_0.95.1247
                 [57] mvtnorm_1.0-2               misc3d_0.8-4
                 [59] KernSmooth_2.23-14          dplyr_0.4.1
                 [61] GEOmetadb_1.29.0            RSQLite_1.0.0
                 [63] DBI_0.3.1                   GEOquery_2.35.4
                 [65] Biobase_2.29.1              BiocGenerics_0.15.0
                 [67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
                 [69] magrittr_1.5                gtools_3.4.2

                 loaded via a namespace (and not attached):
                    [1] Hmisc_3.16-0            plyr_1.8.2
        splines_3.2.0
                    [4] BiocParallel_1.3.9      ggplot2_1.0.1
          digest_0.6.8
                    [7] SuppDists_1.1-9.1       gdata_2.16.1
        GMD_0.3.3
                 [10] checkmate_1.5.2         BBmisc_1.9
        cluster_2.0.1
                 [13] annotate_1.47.0         siggenes_1.43.0
                   colorspace_1.2-6
                 [16] tcltk_3.2.0             registry_0.2
        gtable_0.1.2
                 [19] zlibbioc_1.15.0         RGCCA_2.0
          evd_2.3-0
                 [22] scales_0.2.4            futile.options_1.0.0
        pheatmap_1.0.2
                 [25] rngtools_1.2.4          Rcpp_0.11.6
          xtable_1.7-4
                 [28] foreign_0.8-63          bit_1.1-12
                 preprocessCore_1.31.0
                 [31] Formula_1.2-1           lava_1.4.0
        glmnet_2.0-2
                 [34] httr_0.6.1              gplots_2.17.0
                   RColorBrewer_1.1-2
                 [37] acepack_1.3-3.3         ff_2.2-13
          reshape_0.8.5
                 [40] XML_3.98-1.1            nnet_7.3-9
        reshape2_1.4.1
                 [43] munsell_0.4.2           tools_3.2.0
          stringr_1.0.0
                 [46] bootstrap_2015.2        beanplot_1.2
        caTools_1.17.1
                 [49] doRNG_1.6               nor1mix_1.2-0
          biomaRt_2.25.1
                 [52] stringi_0.4-1           superpc_1.09
                 futile.logger_1.4.1
                 [55] GenomicFeatures_1.21.2  survcomp_1.19.0
          gbm_2.1.1
                 [58] survivalROC_1.0.3       multtest_2.25.0
          R6_2.0.1
                 [61] latticeExtra_0.6-26     gridExtra_0.9.1
                   affxparser_1.41.2
                 [64] codetools_0.2-11        lambda.r_1.1.7
        seqLogo_1.35.0
                 [67] MASS_7.3-40             assertthat_0.1
        proto_0.3-10
                 [70] pkgmaker_0.22           GenomicAlignments_1.5.8
                 Rsamtools_1.21.4
                 [73] mixOmics_5.0-4          rpart_4.1-9
          base64_1.1
                 [76] illuminaio_0.11.0       rmeta_2.16




                 Statistics is the grammar of science.
                 Karl Pearson
        <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

                          [[alternative HTML version deleted]]

SummarizedExperiment was just an example. I agree it can be a
little challenging for end users to know where to find a particular
functionality but I'm not sure about using "meta" packages to address
that. At least I feel we should probably avoid creating new "meta"
packages out of the blue, with arbitrary limits and possibly endless
discussions about what exactly goes in them. Also I don't think there
is a single "core" but rather several domain-specific cores.

What about using the existing workflow packages instead?
A workflow package (like the variants package here
http://bioconductor.org/help/workflows/variants/)
covers a specific domain and loading it should load the "core"
for that domain. Plus the user gets a great vignette as a bonus
to get started so it's not just an empty shell.

There are probably some shortcomings with workflow packages
that would need to be addressed before they can serve as
convenient "meta" packages though e.g. they're treated too
differently from other BioC packages (e.g. they're not available
via biocLite() and don't show up under the biocViews tree here
http://bioconductor.org/packages/release/BiocViews.html).
Nothing that seems impossible to address though...

H.


On 05/12/2015 03:22 PM, Michael Lawrence wrote:

It's more general than SummarizedExperiment. I think people would
appreciate a simple way to load the core, without having to remember,
for example, that VCF reading is in VariantAnnotation.

On Mon, May 11, 2015 at 9:51 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Michael,

    On 05/11/2015 05:35 PM, Michael Lawrence wrote:

        Splitting stuff into different packages is good for modularity,
but
        tough on the mind of the user. What about having some sort of
"meta"
        package that simply loads the core infrastructure packages? Named
        something simple like "Genomics" or "GenomicsCore".


    Don't know if we need this. For example, for all the
    SummarizedExperiment use cases I ran into, the end-user generally
    only needs to load the corresponding high-level package (DESeq2,
    VariantAnnotation, minfi, GenomicAlignments, etc...) and that takes
    care of loading all the low-level infrastructure packages.

    H.


        On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s
        <hpages at fredhutch.org <mailto:hpages at fredhutch.org>
        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>>
wrote:

             Hi Tim,

             The SummarizedExperiment class is being replaced with the
             RangedSummarizedExperiment class from the new
        SummarizedExperiment
             package. This is a work-in-progress and the name and internal
             representation of the RangedSummarizedExperiment class are
not
             finalized yet. The main goal for now is to move all the
             SummarizedExperiment stuff from GenomicRanges to its own
        package.

             Anyway, metadata() is the replacement for exptData() on
             RangedSummarizedExperiment objects. It's on my list to add
             an exptData method for backward compatibility.

             Cheers,
             H.


             On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

                 who determined that breaking this would be a good idea?!?

                 R> ?SummarizedExperiment
                 Help on topic 'SummarizedExperiment' was found in the
        following
                 packages:

                     Package               Library
                     GenomicRanges
                   /home/tim/R/x86_64-pc-linux-gnu-library/3.2
                     SummarizedExperiment

        /home/tim/R/x86_64-pc-linux-gnu-library/3.2

                    R> nrows <- 200; ncols <- 6
                 R>        counts <- matrix(runif(nrows * ncols, 1,
        1e4), nrows)
                 R>        rowRanges <- GRanges(rep(c("chr1", "chr2"),
        c(50, 150)),
                 +                           IRanges(floor(runif(200,
        1e5, 1e6)),
                 width=100),
                 +                           strand=sample(c("+", "-"),
        200, TRUE))
                 R>        colData <- DataFrame(Treatment=rep(c("ChIP",
        "Input"), 3),
                 +                             row.names=LETTERS[1:6])
                 R>        sset <-
                 SummarizedExperiment(assays=SimpleList(counts=counts),
                 +                       rowRanges=rowRanges,
        colData=colData)
                 R>        sset
                 class: RangedSummarizedExperiment
                 dim: 200 6
                 metadata(0):
                 assays(1): counts
                 rownames: NULL
                 rowRanges metadata column names(0):
                 colnames(6): A B ... E F
                 colData names(1): Treatment
                 R>        assayNames(sset)
                 [1] "counts"
                 R>        assays(sset) <- endoapply(assays(sset), asinh)
                 R>        head(assay(sset))
                           A    B    C    D    E    F
                 [1,] 6.89 8.81 9.46 9.20 8.88 9.44
                 [2,] 5.07 9.70 4.08 7.47 8.91 5.64
                 [3,] 9.88 9.84 8.95 9.07 9.86 9.06
                 [4,] 9.89 8.88 8.92 8.05 8.46 9.51
                 [5,] 9.75 8.48 4.73 9.86 8.43 9.86
                 [6,] 9.29 9.13 9.80 9.77 9.50 8.40
                 R> exptData(sset)
                 Error in (function (classes, fdef, mtable)  :
                     unable to find an inherited method for function
        'exptData'
                 for signature
                 '"RangedSummarizedExperiment"'



                 It's one of those things that's a handy place to put
        data when
                 you need to
                 carry it around for the same set of people/subjects but
        don't
                 have a handy
                 multidimensional container for it.  So it's a bit of a
        drag that
                 it now
                 breaks...


                 Bonus:

                 R> ?"exptData,SummarizedExperiment-method"

                 SummarizedExperiment-class    package:GenomicRanges    R
                 Documentation

                 SummarizedExperiment instances

                 Description:

                        The SummarizedExperiment class is a matrix-like
        container
                 where
                        rows represent ranges of interest (as a 'GRanges
or
                        GRangesList-class') and columns represent
        samples (with
                 sample
                        data summarized as a 'DataFrame-class'). A
                 'SummarizedExperiment'
                        contains one or more assays, each represented by a
                 matrix-like
                        object of numeric or other mode.




                 R> sessionInfo()
                 R version 3.2.0 (2015-04-16)
                 Platform: x86_64-pc-linux-gnu (64-bit)
                 Running under: Ubuntu 15.04

                 locale:
                    [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
                    [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
                    [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
                    [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
                    [9] LC_ADDRESS=C               LC_TELEPHONE=C
                 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

                 attached base packages:
                    [1] grid      stats4    parallel  stats     graphics
                 grDevices datasets
                    [8] utils     methods   base

                 other attached packages:
                    [1] disintegrator_0.4.8         vegan_2.2-1
                    [3] permute_0.8-3               CCAGFA_1.0.4
                    [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
                    [7] igraph_0.7.1                corrplot_0.73
                    [9] marray_1.47.0               AnnotationDbi_1.31.6
                 [11] MotifDb_1.10.0              PWMEnrich_4.5.0
                 [13] SCAN.UPC_2.10.0             sva_3.15.0
                 [15] genefilter_1.51.0           mgcv_1.8-6
                 [17] nlme_3.1-120                affyio_1.37.0
                 [19] affy_1.47.0                 oligo_1.33.0
                 [21] oligoClasses_1.31.0         SRAdb_1.23.0
                 [23] RCurl_1.95-4.6              bitops_1.0-6
                 [25] graph_1.47.0                quadprog_1.5-5
                 [27] mclust_5.0.1
        ConsensusClusterPlus_1.23.0
                 [29] simulatorZ_1.5.1            CoxBoost_1.4
                 [31] prodlim_1.5.1               rsig_1.0
                 [33] survival_2.38-1             DMRcate_1.5.42
                 [35] matrixStats_0.14.0          rtracklayer_1.29.5
                 [37] Matrix_1.2-0                qvalue_2.1.0
                 [39] impute_1.43.0               DMRcatedata_1.5.0
                 [41] minfi_1.15.3                bumphunter_1.8.0
                 [43] locfit_1.5-9.1              iterators_1.0.7
                 [45] foreach_1.4.2               Biostrings_2.37.2
                 [47] XVector_0.9.1
 SummarizedExperiment_0.1.1
                 [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
                 [51] IRanges_2.3.8               S4Vectors_0.7.2
                 [53] lattice_0.20-31             limma_3.25.3
                 [55] ks_1.9.4                    rgl_0.95.1247
                 [57] mvtnorm_1.0-2               misc3d_0.8-4
                 [59] KernSmooth_2.23-14          dplyr_0.4.1
                 [61] GEOmetadb_1.29.0            RSQLite_1.0.0
                 [63] DBI_0.3.1                   GEOquery_2.35.4
                 [65] Biobase_2.29.1              BiocGenerics_0.15.0
                 [67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
                 [69] magrittr_1.5                gtools_3.4.2

                 loaded via a namespace (and not attached):
                    [1] Hmisc_3.16-0            plyr_1.8.2
        splines_3.2.0
                    [4] BiocParallel_1.3.9      ggplot2_1.0.1
          digest_0.6.8
                    [7] SuppDists_1.1-9.1       gdata_2.16.1
        GMD_0.3.3
                 [10] checkmate_1.5.2         BBmisc_1.9
        cluster_2.0.1
                 [13] annotate_1.47.0         siggenes_1.43.0
                   colorspace_1.2-6
                 [16] tcltk_3.2.0             registry_0.2
        gtable_0.1.2
                 [19] zlibbioc_1.15.0         RGCCA_2.0
          evd_2.3-0
                 [22] scales_0.2.4            futile.options_1.0.0
        pheatmap_1.0.2
                 [25] rngtools_1.2.4          Rcpp_0.11.6
          xtable_1.7-4
                 [28] foreign_0.8-63          bit_1.1-12
                 preprocessCore_1.31.0
                 [31] Formula_1.2-1           lava_1.4.0
        glmnet_2.0-2
                 [34] httr_0.6.1              gplots_2.17.0
                   RColorBrewer_1.1-2
                 [37] acepack_1.3-3.3         ff_2.2-13
          reshape_0.8.5
                 [40] XML_3.98-1.1            nnet_7.3-9
        reshape2_1.4.1
                 [43] munsell_0.4.2           tools_3.2.0
          stringr_1.0.0
                 [46] bootstrap_2015.2        beanplot_1.2
        caTools_1.17.1
                 [49] doRNG_1.6               nor1mix_1.2-0
          biomaRt_2.25.1
                 [52] stringi_0.4-1           superpc_1.09
                 futile.logger_1.4.1
                 [55] GenomicFeatures_1.21.2  survcomp_1.19.0
          gbm_2.1.1
                 [58] survivalROC_1.0.3       multtest_2.25.0
          R6_2.0.1
                 [61] latticeExtra_0.6-26     gridExtra_0.9.1
                   affxparser_1.41.2
                 [64] codetools_0.2-11        lambda.r_1.1.7
        seqLogo_1.35.0
                 [67] MASS_7.3-40             assertthat_0.1
        proto_0.3-10
                 [70] pkgmaker_0.22           GenomicAlignments_1.5.8
                 Rsamtools_1.21.4
                 [73] mixOmics_5.0-4          rpart_4.1-9
          base64_1.1
                 [76] illuminaio_0.11.0       rmeta_2.16




                 Statistics is the grammar of science.
                 Karl Pearson
        <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

                          [[alternative HTML version deleted]]

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

wrote:

I like the idea of having multiple, domain-specific cores. Those could also
serve as a vehicle for high-level documentation, including the workflows
but also more "cheat-sheet" and/or cookbook-style documentation. Rafa has
brought this up on the phone calls.


On Tue, May 12, 2015 at 4:10 PM, Herv? Pag?s <hpages at fredhutch.org> wrote:

SummarizedExperiment was just an example. I agree it can be a
little challenging for end users to know where to find a particular
functionality but I'm not sure about using "meta" packages to address
that. At least I feel we should probably avoid creating new "meta"
packages out of the blue, with arbitrary limits and possibly endless
discussions about what exactly goes in them. Also I don't think there
is a single "core" but rather several domain-specific cores.

What about using the existing workflow packages instead?
A workflow package (like the variants package here
http://bioconductor.org/help/workflows/variants/)
covers a specific domain and loading it should load the "core"
for that domain. Plus the user gets a great vignette as a bonus
to get started so it's not just an empty shell.

There are probably some shortcomings with workflow packages
that would need to be addressed before they can serve as
convenient "meta" packages though e.g. they're treated too
differently from other BioC packages (e.g. they're not available
via biocLite() and don't show up under the biocViews tree here
http://bioconductor.org/packages/release/BiocViews.html).
Nothing that seems impossible to address though...

H.


On 05/12/2015 03:22 PM, Michael Lawrence wrote:

It's more general than SummarizedExperiment. I think people would
appreciate a simple way to load the core, without having to remember,
for example, that VCF reading is in VariantAnnotation.

On Mon, May 11, 2015 at 9:51 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Michael,

    On 05/11/2015 05:35 PM, Michael Lawrence wrote:

        Splitting stuff into different packages is good for modularity,
but
        tough on the mind of the user. What about having some sort of
"meta"
        package that simply loads the core infrastructure packages?

Named

        something simple like "Genomics" or "GenomicsCore".


    Don't know if we need this. For example, for all the
    SummarizedExperiment use cases I ran into, the end-user generally
    only needs to load the corresponding high-level package (DESeq2,
    VariantAnnotation, minfi, GenomicAlignments, etc...) and that takes
    care of loading all the low-level infrastructure packages.

    H.


        On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s
        <hpages at fredhutch.org <mailto:hpages at fredhutch.org>
        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>>
wrote:

             Hi Tim,

             The SummarizedExperiment class is being replaced with the
             RangedSummarizedExperiment class from the new
        SummarizedExperiment
             package. This is a work-in-progress and the name and

internal

             representation of the RangedSummarizedExperiment class are
not
             finalized yet. The main goal for now is to move all the
             SummarizedExperiment stuff from GenomicRanges to its own
        package.

             Anyway, metadata() is the replacement for exptData() on
             RangedSummarizedExperiment objects. It's on my list to add
             an exptData method for backward compatibility.

             Cheers,
             H.


             On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

                 who determined that breaking this would be a good

idea?!?

                 R> ?SummarizedExperiment
                 Help on topic 'SummarizedExperiment' was found in the
        following
                 packages:

                     Package               Library
                     GenomicRanges
                   /home/tim/R/x86_64-pc-linux-gnu-library/3.2
                     SummarizedExperiment

        /home/tim/R/x86_64-pc-linux-gnu-library/3.2

                    R> nrows <- 200; ncols <- 6
                 R>        counts <- matrix(runif(nrows * ncols, 1,
        1e4), nrows)
                 R>        rowRanges <- GRanges(rep(c("chr1", "chr2"),
        c(50, 150)),
                 +                           IRanges(floor(runif(200,
        1e5, 1e6)),
                 width=100),
                 +                           strand=sample(c("+", "-"),
        200, TRUE))
                 R>        colData <- DataFrame(Treatment=rep(c("ChIP",
        "Input"), 3),
                 +                             row.names=LETTERS[1:6])
                 R>        sset <-
                 SummarizedExperiment(assays=SimpleList(counts=counts),
                 +                       rowRanges=rowRanges,
        colData=colData)
                 R>        sset
                 class: RangedSummarizedExperiment
                 dim: 200 6
                 metadata(0):
                 assays(1): counts
                 rownames: NULL
                 rowRanges metadata column names(0):
                 colnames(6): A B ... E F
                 colData names(1): Treatment
                 R>        assayNames(sset)
                 [1] "counts"
                 R>        assays(sset) <- endoapply(assays(sset),

asinh)

                 R>        head(assay(sset))
                           A    B    C    D    E    F
                 [1,] 6.89 8.81 9.46 9.20 8.88 9.44
                 [2,] 5.07 9.70 4.08 7.47 8.91 5.64
                 [3,] 9.88 9.84 8.95 9.07 9.86 9.06
                 [4,] 9.89 8.88 8.92 8.05 8.46 9.51
                 [5,] 9.75 8.48 4.73 9.86 8.43 9.86
                 [6,] 9.29 9.13 9.80 9.77 9.50 8.40
                 R> exptData(sset)
                 Error in (function (classes, fdef, mtable)  :
                     unable to find an inherited method for function
        'exptData'
                 for signature
                 '"RangedSummarizedExperiment"'



                 It's one of those things that's a handy place to put
        data when
                 you need to
                 carry it around for the same set of people/subjects but
        don't
                 have a handy
                 multidimensional container for it.  So it's a bit of a
        drag that
                 it now
                 breaks...


                 Bonus:

                 R> ?"exptData,SummarizedExperiment-method"

                 SummarizedExperiment-class    package:GenomicRanges

R

                 Documentation

                 SummarizedExperiment instances

                 Description:

                        The SummarizedExperiment class is a matrix-like
        container
                 where
                        rows represent ranges of interest (as a 'GRanges
or
                        GRangesList-class') and columns represent
        samples (with
                 sample
                        data summarized as a 'DataFrame-class'). A
                 'SummarizedExperiment'
                        contains one or more assays, each represented

by a

                 matrix-like
                        object of numeric or other mode.




                 R> sessionInfo()
                 R version 3.2.0 (2015-04-16)
                 Platform: x86_64-pc-linux-gnu (64-bit)
                 Running under: Ubuntu 15.04

                 locale:
                    [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
                    [3] LC_TIME=en_US.UTF-8

LC_COLLATE=en_US.UTF-8

                    [5] LC_MONETARY=en_US.UTF-8

LC_MESSAGES=en_US.UTF-8

                    [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
                    [9] LC_ADDRESS=C               LC_TELEPHONE=C
                 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

                 attached base packages:
                    [1] grid      stats4    parallel  stats     graphics
                 grDevices datasets
                    [8] utils     methods   base

                 other attached packages:
                    [1] disintegrator_0.4.8         vegan_2.2-1
                    [3] permute_0.8-3               CCAGFA_1.0.4
                    [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
                    [7] igraph_0.7.1                corrplot_0.73
                    [9] marray_1.47.0               AnnotationDbi_1.31.6
                 [11] MotifDb_1.10.0              PWMEnrich_4.5.0
                 [13] SCAN.UPC_2.10.0             sva_3.15.0
                 [15] genefilter_1.51.0           mgcv_1.8-6
                 [17] nlme_3.1-120                affyio_1.37.0
                 [19] affy_1.47.0                 oligo_1.33.0
                 [21] oligoClasses_1.31.0         SRAdb_1.23.0
                 [23] RCurl_1.95-4.6              bitops_1.0-6
                 [25] graph_1.47.0                quadprog_1.5-5
                 [27] mclust_5.0.1
        ConsensusClusterPlus_1.23.0
                 [29] simulatorZ_1.5.1            CoxBoost_1.4
                 [31] prodlim_1.5.1               rsig_1.0
                 [33] survival_2.38-1             DMRcate_1.5.42
                 [35] matrixStats_0.14.0          rtracklayer_1.29.5
                 [37] Matrix_1.2-0                qvalue_2.1.0
                 [39] impute_1.43.0               DMRcatedata_1.5.0
                 [41] minfi_1.15.3                bumphunter_1.8.0
                 [43] locfit_1.5-9.1              iterators_1.0.7
                 [45] foreach_1.4.2               Biostrings_2.37.2
                 [47] XVector_0.9.1
 SummarizedExperiment_0.1.1
                 [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
                 [51] IRanges_2.3.8               S4Vectors_0.7.2
                 [53] lattice_0.20-31             limma_3.25.3
                 [55] ks_1.9.4                    rgl_0.95.1247
                 [57] mvtnorm_1.0-2               misc3d_0.8-4
                 [59] KernSmooth_2.23-14          dplyr_0.4.1
                 [61] GEOmetadb_1.29.0            RSQLite_1.0.0
                 [63] DBI_0.3.1                   GEOquery_2.35.4
                 [65] Biobase_2.29.1              BiocGenerics_0.15.0
                 [67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
                 [69] magrittr_1.5                gtools_3.4.2

                 loaded via a namespace (and not attached):
                    [1] Hmisc_3.16-0            plyr_1.8.2
        splines_3.2.0
                    [4] BiocParallel_1.3.9      ggplot2_1.0.1
          digest_0.6.8
                    [7] SuppDists_1.1-9.1       gdata_2.16.1
        GMD_0.3.3
                 [10] checkmate_1.5.2         BBmisc_1.9
        cluster_2.0.1
                 [13] annotate_1.47.0         siggenes_1.43.0
                   colorspace_1.2-6
                 [16] tcltk_3.2.0             registry_0.2
        gtable_0.1.2
                 [19] zlibbioc_1.15.0         RGCCA_2.0
          evd_2.3-0
                 [22] scales_0.2.4            futile.options_1.0.0
        pheatmap_1.0.2
                 [25] rngtools_1.2.4          Rcpp_0.11.6
          xtable_1.7-4
                 [28] foreign_0.8-63          bit_1.1-12
                 preprocessCore_1.31.0
                 [31] Formula_1.2-1           lava_1.4.0
        glmnet_2.0-2
                 [34] httr_0.6.1              gplots_2.17.0
                   RColorBrewer_1.1-2
                 [37] acepack_1.3-3.3         ff_2.2-13
          reshape_0.8.5
                 [40] XML_3.98-1.1            nnet_7.3-9
        reshape2_1.4.1
                 [43] munsell_0.4.2           tools_3.2.0
          stringr_1.0.0
                 [46] bootstrap_2015.2        beanplot_1.2
        caTools_1.17.1
                 [49] doRNG_1.6               nor1mix_1.2-0
          biomaRt_2.25.1
                 [52] stringi_0.4-1           superpc_1.09
                 futile.logger_1.4.1
                 [55] GenomicFeatures_1.21.2  survcomp_1.19.0
          gbm_2.1.1
                 [58] survivalROC_1.0.3       multtest_2.25.0
          R6_2.0.1
                 [61] latticeExtra_0.6-26     gridExtra_0.9.1
                   affxparser_1.41.2
                 [64] codetools_0.2-11        lambda.r_1.1.7
        seqLogo_1.35.0
                 [67] MASS_7.3-40             assertthat_0.1
        proto_0.3-10
                 [70] pkgmaker_0.22           GenomicAlignments_1.5.8
                 Rsamtools_1.21.4
                 [73] mixOmics_5.0-4          rpart_4.1-9
          base64_1.1
                 [76] illuminaio_0.11.0       rmeta_2.16




                 Statistics is the grammar of science.
                 Karl Pearson
        <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

                          [[alternative HTML version deleted]]

Bioc-devel at r-project.org

                 mailing list

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

        [[alternative HTML version deleted]]

Agreed that the workflow vehicle should get more attention.  Do all
workflows correspond to packages?

On Tue, May 12, 2015 at 7:31 PM, Michael Lawrence <
lawrence.michael at gene.com

wrote:

I like the idea of having multiple, domain-specific cores. Those could

also

serve as a vehicle for high-level documentation, including the workflows
but also more "cheat-sheet" and/or cookbook-style documentation. Rafa has
brought this up on the phone calls.


On Tue, May 12, 2015 at 4:10 PM, Herv? Pag?s <hpages at fredhutch.org>

wrote:

SummarizedExperiment was just an example. I agree it can be a
little challenging for end users to know where to find a particular
functionality but I'm not sure about using "meta" packages to address
that. At least I feel we should probably avoid creating new "meta"
packages out of the blue, with arbitrary limits and possibly endless
discussions about what exactly goes in them. Also I don't think there
is a single "core" but rather several domain-specific cores.

What about using the existing workflow packages instead?
A workflow package (like the variants package here
http://bioconductor.org/help/workflows/variants/)
covers a specific domain and loading it should load the "core"
for that domain. Plus the user gets a great vignette as a bonus
to get started so it's not just an empty shell.

There are probably some shortcomings with workflow packages
that would need to be addressed before they can serve as
convenient "meta" packages though e.g. they're treated too
differently from other BioC packages (e.g. they're not available
via biocLite() and don't show up under the biocViews tree here
http://bioconductor.org/packages/release/BiocViews.html).
Nothing that seems impossible to address though...

H.


On 05/12/2015 03:22 PM, Michael Lawrence wrote:

It's more general than SummarizedExperiment. I think people would
appreciate a simple way to load the core, without having to remember,
for example, that VCF reading is in VariantAnnotation.

On Mon, May 11, 2015 at 9:51 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Michael,

    On 05/11/2015 05:35 PM, Michael Lawrence wrote:

        Splitting stuff into different packages is good for

modularity,

but
        tough on the mind of the user. What about having some sort of
"meta"
        package that simply loads the core infrastructure packages?

Named

        something simple like "Genomics" or "GenomicsCore".


    Don't know if we need this. For example, for all the
    SummarizedExperiment use cases I ran into, the end-user generally
    only needs to load the corresponding high-level package (DESeq2,
    VariantAnnotation, minfi, GenomicAlignments, etc...) and that

takes

    care of loading all the low-level infrastructure packages.

    H.


        On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s
        <hpages at fredhutch.org <mailto:hpages at fredhutch.org>
        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>>
wrote:

             Hi Tim,

             The SummarizedExperiment class is being replaced with the
             RangedSummarizedExperiment class from the new
        SummarizedExperiment
             package. This is a work-in-progress and the name and

internal

             representation of the RangedSummarizedExperiment class

are

not
             finalized yet. The main goal for now is to move all the
             SummarizedExperiment stuff from GenomicRanges to its own
        package.

             Anyway, metadata() is the replacement for exptData() on
             RangedSummarizedExperiment objects. It's on my list to

add

             an exptData method for backward compatibility.

             Cheers,
             H.


             On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

                 who determined that breaking this would be a good

idea?!?

                 R> ?SummarizedExperiment
                 Help on topic 'SummarizedExperiment' was found in the
        following
                 packages:

                     Package               Library
                     GenomicRanges
                   /home/tim/R/x86_64-pc-linux-gnu-library/3.2
                     SummarizedExperiment

        /home/tim/R/x86_64-pc-linux-gnu-library/3.2

                    R> nrows <- 200; ncols <- 6
                 R>        counts <- matrix(runif(nrows * ncols, 1,
        1e4), nrows)
                 R>        rowRanges <- GRanges(rep(c("chr1", "chr2"),
        c(50, 150)),
                 +                           IRanges(floor(runif(200,
        1e5, 1e6)),
                 width=100),
                 +                           strand=sample(c("+",

"-"),

        200, TRUE))
                 R>        colData <-

DataFrame(Treatment=rep(c("ChIP",

        "Input"), 3),
                 +                             row.names=LETTERS[1:6])
                 R>        sset <-

SummarizedExperiment(assays=SimpleList(counts=counts),

                 +                       rowRanges=rowRanges,
        colData=colData)
                 R>        sset
                 class: RangedSummarizedExperiment
                 dim: 200 6
                 metadata(0):
                 assays(1): counts
                 rownames: NULL
                 rowRanges metadata column names(0):
                 colnames(6): A B ... E F
                 colData names(1): Treatment
                 R>        assayNames(sset)
                 [1] "counts"
                 R>        assays(sset) <- endoapply(assays(sset),

asinh)

                 R>        head(assay(sset))
                           A    B    C    D    E    F
                 [1,] 6.89 8.81 9.46 9.20 8.88 9.44
                 [2,] 5.07 9.70 4.08 7.47 8.91 5.64
                 [3,] 9.88 9.84 8.95 9.07 9.86 9.06
                 [4,] 9.89 8.88 8.92 8.05 8.46 9.51
                 [5,] 9.75 8.48 4.73 9.86 8.43 9.86
                 [6,] 9.29 9.13 9.80 9.77 9.50 8.40
                 R> exptData(sset)
                 Error in (function (classes, fdef, mtable)  :
                     unable to find an inherited method for function
        'exptData'
                 for signature
                 '"RangedSummarizedExperiment"'



                 It's one of those things that's a handy place to put
        data when
                 you need to
                 carry it around for the same set of people/subjects

but

        don't
                 have a handy
                 multidimensional container for it.  So it's a bit of

a

        drag that
                 it now
                 breaks...


                 Bonus:

                 R> ?"exptData,SummarizedExperiment-method"

                 SummarizedExperiment-class    package:GenomicRanges

R

                 Documentation

                 SummarizedExperiment instances

                 Description:

                        The SummarizedExperiment class is a

matrix-like

        container
                 where
                        rows represent ranges of interest (as a

'GRanges

or
                        GRangesList-class') and columns represent
        samples (with
                 sample
                        data summarized as a 'DataFrame-class'). A
                 'SummarizedExperiment'
                        contains one or more assays, each represented

by a

                 matrix-like
                        object of numeric or other mode.




                 R> sessionInfo()
                 R version 3.2.0 (2015-04-16)
                 Platform: x86_64-pc-linux-gnu (64-bit)
                 Running under: Ubuntu 15.04

                 locale:
                    [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
                    [3] LC_TIME=en_US.UTF-8

LC_COLLATE=en_US.UTF-8

                    [5] LC_MONETARY=en_US.UTF-8

LC_MESSAGES=en_US.UTF-8

                    [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
                    [9] LC_ADDRESS=C               LC_TELEPHONE=C
                 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

                 attached base packages:
                    [1] grid      stats4    parallel  stats

 graphics

                 grDevices datasets
                    [8] utils     methods   base

                 other attached packages:
                    [1] disintegrator_0.4.8         vegan_2.2-1
                    [3] permute_0.8-3               CCAGFA_1.0.4
                    [5] FEM_2.3.0                   org.Hs.eg.db_3.1.2
                    [7] igraph_0.7.1                corrplot_0.73
                    [9] marray_1.47.0

 AnnotationDbi_1.31.6

                 [11] MotifDb_1.10.0              PWMEnrich_4.5.0
                 [13] SCAN.UPC_2.10.0             sva_3.15.0
                 [15] genefilter_1.51.0           mgcv_1.8-6
                 [17] nlme_3.1-120                affyio_1.37.0
                 [19] affy_1.47.0                 oligo_1.33.0
                 [21] oligoClasses_1.31.0         SRAdb_1.23.0
                 [23] RCurl_1.95-4.6              bitops_1.0-6
                 [25] graph_1.47.0                quadprog_1.5-5
                 [27] mclust_5.0.1
        ConsensusClusterPlus_1.23.0
                 [29] simulatorZ_1.5.1            CoxBoost_1.4
                 [31] prodlim_1.5.1               rsig_1.0
                 [33] survival_2.38-1             DMRcate_1.5.42
                 [35] matrixStats_0.14.0          rtracklayer_1.29.5
                 [37] Matrix_1.2-0                qvalue_2.1.0
                 [39] impute_1.43.0               DMRcatedata_1.5.0
                 [41] minfi_1.15.3                bumphunter_1.8.0
                 [43] locfit_1.5-9.1              iterators_1.0.7
                 [45] foreach_1.4.2               Biostrings_2.37.2
                 [47] XVector_0.9.1
 SummarizedExperiment_0.1.1
                 [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
                 [51] IRanges_2.3.8               S4Vectors_0.7.2
                 [53] lattice_0.20-31             limma_3.25.3
                 [55] ks_1.9.4                    rgl_0.95.1247
                 [57] mvtnorm_1.0-2               misc3d_0.8-4
                 [59] KernSmooth_2.23-14          dplyr_0.4.1
                 [61] GEOmetadb_1.29.0            RSQLite_1.0.0
                 [63] DBI_0.3.1                   GEOquery_2.35.4
                 [65] Biobase_2.29.1              BiocGenerics_0.15.0
                 [67] bigrquery_0.1.0.9000        BiocInstaller_1.19.5
                 [69] magrittr_1.5                gtools_3.4.2

                 loaded via a namespace (and not attached):
                    [1] Hmisc_3.16-0            plyr_1.8.2
        splines_3.2.0
                    [4] BiocParallel_1.3.9      ggplot2_1.0.1
          digest_0.6.8
                    [7] SuppDists_1.1-9.1       gdata_2.16.1
        GMD_0.3.3
                 [10] checkmate_1.5.2         BBmisc_1.9
        cluster_2.0.1
                 [13] annotate_1.47.0         siggenes_1.43.0
                   colorspace_1.2-6
                 [16] tcltk_3.2.0             registry_0.2
        gtable_0.1.2
                 [19] zlibbioc_1.15.0         RGCCA_2.0
          evd_2.3-0
                 [22] scales_0.2.4            futile.options_1.0.0
        pheatmap_1.0.2
                 [25] rngtools_1.2.4          Rcpp_0.11.6
          xtable_1.7-4
                 [28] foreign_0.8-63          bit_1.1-12
                 preprocessCore_1.31.0
                 [31] Formula_1.2-1           lava_1.4.0
        glmnet_2.0-2
                 [34] httr_0.6.1              gplots_2.17.0
                   RColorBrewer_1.1-2
                 [37] acepack_1.3-3.3         ff_2.2-13
          reshape_0.8.5
                 [40] XML_3.98-1.1            nnet_7.3-9
        reshape2_1.4.1
                 [43] munsell_0.4.2           tools_3.2.0
          stringr_1.0.0
                 [46] bootstrap_2015.2        beanplot_1.2
        caTools_1.17.1
                 [49] doRNG_1.6               nor1mix_1.2-0
          biomaRt_2.25.1
                 [52] stringi_0.4-1           superpc_1.09
                 futile.logger_1.4.1
                 [55] GenomicFeatures_1.21.2  survcomp_1.19.0
          gbm_2.1.1
                 [58] survivalROC_1.0.3       multtest_2.25.0
          R6_2.0.1
                 [61] latticeExtra_0.6-26     gridExtra_0.9.1
                   affxparser_1.41.2
                 [64] codetools_0.2-11        lambda.r_1.1.7
        seqLogo_1.35.0
                 [67] MASS_7.3-40             assertthat_0.1
        proto_0.3-10
                 [70] pkgmaker_0.22           GenomicAlignments_1.5.8
                 Rsamtools_1.21.4
                 [73] mixOmics_5.0-4          rpart_4.1-9
          base64_1.1
                 [76] illuminaio_0.11.0       rmeta_2.16




                 Statistics is the grammar of science.
                 Karl Pearson
        <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

                          [[alternative HTML version deleted]]

Bioc-devel at r-project.org

                 mailing list

hpages at fredhutch.org>

        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>
             Phone: (206) 667-5791 <tel:%28206%29%20667-5791>
        <tel:%28206%29%20667-5791>
             Fax: (206) 667-1319 <tel:%28206%29%20667-1319>
        <tel:%28206%29%20667-1319>

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

        [[alternative HTML version deleted]]

        [[alternative HTML version deleted]]

the original workflow idea was exactly that it should go beyond a single
package.

Having domain specific cores might be controversial since we often have
multiple packages competing in the same domain.  To some extent the
GenomicRanges/Biostring/etc/etc is a special case of this, where "everyone"
is using these packages.  To me it sounds too much like an official
endorsement of a specific combination of packages.  With workflows, all one
is saying is that "you can use package A,B,C to accomplish tasks 1,2,3";
there is no official endorsement of a "winner".  I think this is worth
thinking about: I think the project does benefit from multiple attempts at
achieving the same result and the resulting competition it creates.

Best,
Kasper

On Tue, May 12, 2015 at 11:26 PM, Vincent Carey <
stvjc at channing.harvard.edu>
wrote:

Agreed that the workflow vehicle should get more attention.  Do all
workflows correspond to packages?

On Tue, May 12, 2015 at 7:31 PM, Michael Lawrence <
lawrence.michael at gene.com

wrote:

I like the idea of having multiple, domain-specific cores. Those could

also

serve as a vehicle for high-level documentation, including the

workflows

but also more "cheat-sheet" and/or cookbook-style documentation. Rafa

has

brought this up on the phone calls.


On Tue, May 12, 2015 at 4:10 PM, Herv? Pag?s <hpages at fredhutch.org>

wrote:

SummarizedExperiment was just an example. I agree it can be a
little challenging for end users to know where to find a particular
functionality but I'm not sure about using "meta" packages to address
that. At least I feel we should probably avoid creating new "meta"
packages out of the blue, with arbitrary limits and possibly endless
discussions about what exactly goes in them. Also I don't think there
is a single "core" but rather several domain-specific cores.

What about using the existing workflow packages instead?
A workflow package (like the variants package here
http://bioconductor.org/help/workflows/variants/)
covers a specific domain and loading it should load the "core"
for that domain. Plus the user gets a great vignette as a bonus
to get started so it's not just an empty shell.

There are probably some shortcomings with workflow packages
that would need to be addressed before they can serve as
convenient "meta" packages though e.g. they're treated too
differently from other BioC packages (e.g. they're not available
via biocLite() and don't show up under the biocViews tree here
http://bioconductor.org/packages/release/BiocViews.html).
Nothing that seems impossible to address though...

H.


On 05/12/2015 03:22 PM, Michael Lawrence wrote:

It's more general than SummarizedExperiment. I think people would
appreciate a simple way to load the core, without having to

remember,

for example, that VCF reading is in VariantAnnotation.

On Mon, May 11, 2015 at 9:51 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Michael,

    On 05/11/2015 05:35 PM, Michael Lawrence wrote:

        Splitting stuff into different packages is good for

modularity,

but
        tough on the mind of the user. What about having some sort

of

"meta"
        package that simply loads the core infrastructure packages?

Named

        something simple like "Genomics" or "GenomicsCore".


    Don't know if we need this. For example, for all the
    SummarizedExperiment use cases I ran into, the end-user

generally

    only needs to load the corresponding high-level package (DESeq2,
    VariantAnnotation, minfi, GenomicAlignments, etc...) and that

takes

    care of loading all the low-level infrastructure packages.

    H.


        On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s
        <hpages at fredhutch.org <mailto:hpages at fredhutch.org>
        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org

wrote:

             Hi Tim,

             The SummarizedExperiment class is being replaced with

the

             RangedSummarizedExperiment class from the new
        SummarizedExperiment
             package. This is a work-in-progress and the name and

internal

             representation of the RangedSummarizedExperiment class

are

not
             finalized yet. The main goal for now is to move all the
             SummarizedExperiment stuff from GenomicRanges to its

own

        package.

             Anyway, metadata() is the replacement for exptData() on
             RangedSummarizedExperiment objects. It's on my list to

add

             an exptData method for backward compatibility.

             Cheers,
             H.


             On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

                 who determined that breaking this would be a good

idea?!?

                 R> ?SummarizedExperiment
                 Help on topic 'SummarizedExperiment' was found in

the

        following
                 packages:

                     Package               Library
                     GenomicRanges
                   /home/tim/R/x86_64-pc-linux-gnu-library/3.2
                     SummarizedExperiment

        /home/tim/R/x86_64-pc-linux-gnu-library/3.2

                    R> nrows <- 200; ncols <- 6
                 R>        counts <- matrix(runif(nrows * ncols, 1,
        1e4), nrows)
                 R>        rowRanges <- GRanges(rep(c("chr1",

"chr2"),

        c(50, 150)),
                 +

 IRanges(floor(runif(200,

        1e5, 1e6)),
                 width=100),
                 +                           strand=sample(c("+",

"-"),

        200, TRUE))
                 R>        colData <-

DataFrame(Treatment=rep(c("ChIP",

        "Input"), 3),
                 +

 row.names=LETTERS[1:6])

                 R>        sset <-

SummarizedExperiment(assays=SimpleList(counts=counts),

                 +                       rowRanges=rowRanges,
        colData=colData)
                 R>        sset
                 class: RangedSummarizedExperiment
                 dim: 200 6
                 metadata(0):
                 assays(1): counts
                 rownames: NULL
                 rowRanges metadata column names(0):
                 colnames(6): A B ... E F
                 colData names(1): Treatment
                 R>        assayNames(sset)
                 [1] "counts"
                 R>        assays(sset) <- endoapply(assays(sset),

asinh)

                 R>        head(assay(sset))
                           A    B    C    D    E    F
                 [1,] 6.89 8.81 9.46 9.20 8.88 9.44
                 [2,] 5.07 9.70 4.08 7.47 8.91 5.64
                 [3,] 9.88 9.84 8.95 9.07 9.86 9.06
                 [4,] 9.89 8.88 8.92 8.05 8.46 9.51
                 [5,] 9.75 8.48 4.73 9.86 8.43 9.86
                 [6,] 9.29 9.13 9.80 9.77 9.50 8.40
                 R> exptData(sset)
                 Error in (function (classes, fdef, mtable)  :
                     unable to find an inherited method for function
        'exptData'
                 for signature
                 '"RangedSummarizedExperiment"'



                 It's one of those things that's a handy place to

put

        data when
                 you need to
                 carry it around for the same set of people/subjects

but

        don't
                 have a handy
                 multidimensional container for it.  So it's a bit

of

a

        drag that
                 it now
                 breaks...


                 Bonus:

                 R> ?"exptData,SummarizedExperiment-method"

                 SummarizedExperiment-class    package:GenomicRanges

R

                 Documentation

                 SummarizedExperiment instances

                 Description:

                        The SummarizedExperiment class is a

matrix-like

        container
                 where
                        rows represent ranges of interest (as a

'GRanges

or
                        GRangesList-class') and columns represent
        samples (with
                 sample
                        data summarized as a 'DataFrame-class'). A
                 'SummarizedExperiment'
                        contains one or more assays, each

represented

by a

                 matrix-like
                        object of numeric or other mode.




                 R> sessionInfo()
                 R version 3.2.0 (2015-04-16)
                 Platform: x86_64-pc-linux-gnu (64-bit)
                 Running under: Ubuntu 15.04

                 locale:
                    [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
                    [3] LC_TIME=en_US.UTF-8

LC_COLLATE=en_US.UTF-8

                    [5] LC_MONETARY=en_US.UTF-8

LC_MESSAGES=en_US.UTF-8

                    [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
                    [9] LC_ADDRESS=C               LC_TELEPHONE=C
                 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

                 attached base packages:
                    [1] grid      stats4    parallel  stats

 graphics

                 grDevices datasets
                    [8] utils     methods   base

                 other attached packages:
                    [1] disintegrator_0.4.8         vegan_2.2-1
                    [3] permute_0.8-3               CCAGFA_1.0.4
                    [5] FEM_2.3.0

 org.Hs.eg.db_3.1.2

                    [7] igraph_0.7.1                corrplot_0.73
                    [9] marray_1.47.0

 AnnotationDbi_1.31.6

                 [11] MotifDb_1.10.0              PWMEnrich_4.5.0
                 [13] SCAN.UPC_2.10.0             sva_3.15.0
                 [15] genefilter_1.51.0           mgcv_1.8-6
                 [17] nlme_3.1-120                affyio_1.37.0
                 [19] affy_1.47.0                 oligo_1.33.0
                 [21] oligoClasses_1.31.0         SRAdb_1.23.0
                 [23] RCurl_1.95-4.6              bitops_1.0-6
                 [25] graph_1.47.0                quadprog_1.5-5
                 [27] mclust_5.0.1
        ConsensusClusterPlus_1.23.0
                 [29] simulatorZ_1.5.1            CoxBoost_1.4
                 [31] prodlim_1.5.1               rsig_1.0
                 [33] survival_2.38-1             DMRcate_1.5.42
                 [35] matrixStats_0.14.0          rtracklayer_1.29.5
                 [37] Matrix_1.2-0                qvalue_2.1.0
                 [39] impute_1.43.0               DMRcatedata_1.5.0
                 [41] minfi_1.15.3                bumphunter_1.8.0
                 [43] locfit_1.5-9.1              iterators_1.0.7
                 [45] foreach_1.4.2               Biostrings_2.37.2
                 [47] XVector_0.9.1
 SummarizedExperiment_0.1.1
                 [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
                 [51] IRanges_2.3.8               S4Vectors_0.7.2
                 [53] lattice_0.20-31             limma_3.25.3
                 [55] ks_1.9.4                    rgl_0.95.1247
                 [57] mvtnorm_1.0-2               misc3d_0.8-4
                 [59] KernSmooth_2.23-14          dplyr_0.4.1
                 [61] GEOmetadb_1.29.0            RSQLite_1.0.0
                 [63] DBI_0.3.1                   GEOquery_2.35.4
                 [65] Biobase_2.29.1

BiocGenerics_0.15.0

                 [67] bigrquery_0.1.0.9000

BiocInstaller_1.19.5

                 [69] magrittr_1.5                gtools_3.4.2

                 loaded via a namespace (and not attached):
                    [1] Hmisc_3.16-0            plyr_1.8.2
        splines_3.2.0
                    [4] BiocParallel_1.3.9      ggplot2_1.0.1
          digest_0.6.8
                    [7] SuppDists_1.1-9.1       gdata_2.16.1
        GMD_0.3.3
                 [10] checkmate_1.5.2         BBmisc_1.9
        cluster_2.0.1
                 [13] annotate_1.47.0         siggenes_1.43.0
                   colorspace_1.2-6
                 [16] tcltk_3.2.0             registry_0.2
        gtable_0.1.2
                 [19] zlibbioc_1.15.0         RGCCA_2.0
          evd_2.3-0
                 [22] scales_0.2.4            futile.options_1.0.0
        pheatmap_1.0.2
                 [25] rngtools_1.2.4          Rcpp_0.11.6
          xtable_1.7-4
                 [28] foreign_0.8-63          bit_1.1-12
                 preprocessCore_1.31.0
                 [31] Formula_1.2-1           lava_1.4.0
        glmnet_2.0-2
                 [34] httr_0.6.1              gplots_2.17.0
                   RColorBrewer_1.1-2
                 [37] acepack_1.3-3.3         ff_2.2-13
          reshape_0.8.5
                 [40] XML_3.98-1.1            nnet_7.3-9
        reshape2_1.4.1
                 [43] munsell_0.4.2           tools_3.2.0
          stringr_1.0.0
                 [46] bootstrap_2015.2        beanplot_1.2
        caTools_1.17.1
                 [49] doRNG_1.6               nor1mix_1.2-0
          biomaRt_2.25.1
                 [52] stringi_0.4-1           superpc_1.09
                 futile.logger_1.4.1
                 [55] GenomicFeatures_1.21.2  survcomp_1.19.0
          gbm_2.1.1
                 [58] survivalROC_1.0.3       multtest_2.25.0
          R6_2.0.1
                 [61] latticeExtra_0.6-26     gridExtra_0.9.1
                   affxparser_1.41.2
                 [64] codetools_0.2-11        lambda.r_1.1.7
        seqLogo_1.35.0
                 [67] MASS_7.3-40             assertthat_0.1
        proto_0.3-10
                 [70] pkgmaker_0.22

 GenomicAlignments_1.5.8

                 Rsamtools_1.21.4
                 [73] mixOmics_5.0-4          rpart_4.1-9
          base64_1.1
                 [76] illuminaio_0.11.0       rmeta_2.16




                 Statistics is the grammar of science.
                 Karl Pearson
        <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

                          [[alternative HTML version deleted]]

Bioc-devel at r-project.org

                 mailing list

hpages at fredhutch.org>

        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>
             Phone: (206) 667-5791 <tel:%28206%29%20667-5791>
        <tel:%28206%29%20667-5791>
             Fax: (206) 667-1319 <tel:%28206%29%20667-1319>
        <tel:%28206%29%20667-1319>

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

        [[alternative HTML version deleted]]

        [[alternative HTML version deleted]]

        [[alternative HTML version deleted]]

the original workflow idea was exactly that it should go beyond a single
package.

Having domain specific cores might be controversial since we often have
multiple packages competing in the same domain.  To some extent the
GenomicRanges/Biostring/etc/etc is a special case of this, where "everyone"
is using these packages.  To me it sounds too much like an official
endorsement of a specific combination of packages.  With workflows, all one
is saying is that "you can use package A,B,C to accomplish tasks 1,2,3";
there is no official endorsement of a "winner".  I think this is worth
thinking about: I think the project does benefit from multiple attempts at
achieving the same result and the resulting competition it creates.

Best,
Kasper

On Tue, May 12, 2015 at 11:26 PM, Vincent Carey <
stvjc at channing.harvard.edu> wrote:

Agreed that the workflow vehicle should get more attention.  Do all
workflows correspond to packages?

On Tue, May 12, 2015 at 7:31 PM, Michael Lawrence <
lawrence.michael at gene.com

wrote:

I like the idea of having multiple, domain-specific cores. Those could

also

serve as a vehicle for high-level documentation, including the workflows
but also more "cheat-sheet" and/or cookbook-style documentation. Rafa

has

brought this up on the phone calls.


On Tue, May 12, 2015 at 4:10 PM, Herv? Pag?s <hpages at fredhutch.org>

wrote:

SummarizedExperiment was just an example. I agree it can be a
little challenging for end users to know where to find a particular
functionality but I'm not sure about using "meta" packages to address
that. At least I feel we should probably avoid creating new "meta"
packages out of the blue, with arbitrary limits and possibly endless
discussions about what exactly goes in them. Also I don't think there
is a single "core" but rather several domain-specific cores.

What about using the existing workflow packages instead?
A workflow package (like the variants package here
http://bioconductor.org/help/workflows/variants/)
covers a specific domain and loading it should load the "core"
for that domain. Plus the user gets a great vignette as a bonus
to get started so it's not just an empty shell.

There are probably some shortcomings with workflow packages
that would need to be addressed before they can serve as
convenient "meta" packages though e.g. they're treated too
differently from other BioC packages (e.g. they're not available
via biocLite() and don't show up under the biocViews tree here
http://bioconductor.org/packages/release/BiocViews.html).
Nothing that seems impossible to address though...

H.


On 05/12/2015 03:22 PM, Michael Lawrence wrote:

It's more general than SummarizedExperiment. I think people would
appreciate a simple way to load the core, without having to remember,
for example, that VCF reading is in VariantAnnotation.

On Mon, May 11, 2015 at 9:51 PM, Herv? Pag?s <hpages at fredhutch.org
<mailto:hpages at fredhutch.org>> wrote:

    Hi Michael,

    On 05/11/2015 05:35 PM, Michael Lawrence wrote:

        Splitting stuff into different packages is good for

modularity,

but
        tough on the mind of the user. What about having some sort of
"meta"
        package that simply loads the core infrastructure packages?

Named

        something simple like "Genomics" or "GenomicsCore".


    Don't know if we need this. For example, for all the
    SummarizedExperiment use cases I ran into, the end-user generally
    only needs to load the corresponding high-level package (DESeq2,
    VariantAnnotation, minfi, GenomicAlignments, etc...) and that

takes

    care of loading all the low-level infrastructure packages.

    H.


        On Mon, May 11, 2015 at 5:10 PM, Herv? Pag?s
        <hpages at fredhutch.org <mailto:hpages at fredhutch.org>
        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>>
wrote:

             Hi Tim,

             The SummarizedExperiment class is being replaced with

the

             RangedSummarizedExperiment class from the new
        SummarizedExperiment
             package. This is a work-in-progress and the name and

internal

             representation of the RangedSummarizedExperiment class

are

not
             finalized yet. The main goal for now is to move all the
             SummarizedExperiment stuff from GenomicRanges to its own
        package.

             Anyway, metadata() is the replacement for exptData() on
             RangedSummarizedExperiment objects. It's on my list to

add

             an exptData method for backward compatibility.

             Cheers,
             H.


             On 05/11/2015 04:37 PM, Tim Triche, Jr. wrote:

                 who determined that breaking this would be a good

idea?!?

                 R> ?SummarizedExperiment
                 Help on topic 'SummarizedExperiment' was found in

the

        following
                 packages:

                     Package               Library
                     GenomicRanges
                   /home/tim/R/x86_64-pc-linux-gnu-library/3.2
                     SummarizedExperiment

        /home/tim/R/x86_64-pc-linux-gnu-library/3.2

                    R> nrows <- 200; ncols <- 6
                 R>        counts <- matrix(runif(nrows * ncols, 1,
        1e4), nrows)
                 R>        rowRanges <- GRanges(rep(c("chr1",

"chr2"),

        c(50, 150)),
                 +                           IRanges(floor(runif(200,
        1e5, 1e6)),
                 width=100),
                 +                           strand=sample(c("+",

"-"),

        200, TRUE))
                 R>        colData <-

DataFrame(Treatment=rep(c("ChIP",

        "Input"), 3),
                 +

 row.names=LETTERS[1:6])

                 R>        sset <-

SummarizedExperiment(assays=SimpleList(counts=counts),

                 +                       rowRanges=rowRanges,
        colData=colData)
                 R>        sset
                 class: RangedSummarizedExperiment
                 dim: 200 6
                 metadata(0):
                 assays(1): counts
                 rownames: NULL
                 rowRanges metadata column names(0):
                 colnames(6): A B ... E F
                 colData names(1): Treatment
                 R>        assayNames(sset)
                 [1] "counts"
                 R>        assays(sset) <- endoapply(assays(sset),

asinh)

                 R>        head(assay(sset))
                           A    B    C    D    E    F
                 [1,] 6.89 8.81 9.46 9.20 8.88 9.44
                 [2,] 5.07 9.70 4.08 7.47 8.91 5.64
                 [3,] 9.88 9.84 8.95 9.07 9.86 9.06
                 [4,] 9.89 8.88 8.92 8.05 8.46 9.51
                 [5,] 9.75 8.48 4.73 9.86 8.43 9.86
                 [6,] 9.29 9.13 9.80 9.77 9.50 8.40
                 R> exptData(sset)
                 Error in (function (classes, fdef, mtable)  :
                     unable to find an inherited method for function
        'exptData'
                 for signature
                 '"RangedSummarizedExperiment"'



                 It's one of those things that's a handy place to put
        data when
                 you need to
                 carry it around for the same set of people/subjects

but

        don't
                 have a handy
                 multidimensional container for it.  So it's a bit

of a

        drag that
                 it now
                 breaks...


                 Bonus:

                 R> ?"exptData,SummarizedExperiment-method"

                 SummarizedExperiment-class    package:GenomicRanges

R

                 Documentation

                 SummarizedExperiment instances

                 Description:

                        The SummarizedExperiment class is a

matrix-like

        container
                 where
                        rows represent ranges of interest (as a

'GRanges

or
                        GRangesList-class') and columns represent
        samples (with
                 sample
                        data summarized as a 'DataFrame-class'). A
                 'SummarizedExperiment'
                        contains one or more assays, each represented

by a

                 matrix-like
                        object of numeric or other mode.




                 R> sessionInfo()
                 R version 3.2.0 (2015-04-16)
                 Platform: x86_64-pc-linux-gnu (64-bit)
                 Running under: Ubuntu 15.04

                 locale:
                    [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
                    [3] LC_TIME=en_US.UTF-8

LC_COLLATE=en_US.UTF-8

                    [5] LC_MONETARY=en_US.UTF-8

LC_MESSAGES=en_US.UTF-8

                    [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
                    [9] LC_ADDRESS=C               LC_TELEPHONE=C
                 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

                 attached base packages:
                    [1] grid      stats4    parallel  stats

 graphics

                 grDevices datasets
                    [8] utils     methods   base

                 other attached packages:
                    [1] disintegrator_0.4.8         vegan_2.2-1
                    [3] permute_0.8-3               CCAGFA_1.0.4
                    [5] FEM_2.3.0

 org.Hs.eg.db_3.1.2

                    [7] igraph_0.7.1                corrplot_0.73
                    [9] marray_1.47.0

 AnnotationDbi_1.31.6

                 [11] MotifDb_1.10.0              PWMEnrich_4.5.0
                 [13] SCAN.UPC_2.10.0             sva_3.15.0
                 [15] genefilter_1.51.0           mgcv_1.8-6
                 [17] nlme_3.1-120                affyio_1.37.0
                 [19] affy_1.47.0                 oligo_1.33.0
                 [21] oligoClasses_1.31.0         SRAdb_1.23.0
                 [23] RCurl_1.95-4.6              bitops_1.0-6
                 [25] graph_1.47.0                quadprog_1.5-5
                 [27] mclust_5.0.1
        ConsensusClusterPlus_1.23.0
                 [29] simulatorZ_1.5.1            CoxBoost_1.4
                 [31] prodlim_1.5.1               rsig_1.0
                 [33] survival_2.38-1             DMRcate_1.5.42
                 [35] matrixStats_0.14.0          rtracklayer_1.29.5
                 [37] Matrix_1.2-0                qvalue_2.1.0
                 [39] impute_1.43.0               DMRcatedata_1.5.0
                 [41] minfi_1.15.3                bumphunter_1.8.0
                 [43] locfit_1.5-9.1              iterators_1.0.7
                 [45] foreach_1.4.2               Biostrings_2.37.2
                 [47] XVector_0.9.1
 SummarizedExperiment_0.1.1
                 [49] GenomicRanges_1.21.9        GenomeInfoDb_1.5.2
                 [51] IRanges_2.3.8               S4Vectors_0.7.2
                 [53] lattice_0.20-31             limma_3.25.3
                 [55] ks_1.9.4                    rgl_0.95.1247
                 [57] mvtnorm_1.0-2               misc3d_0.8-4
                 [59] KernSmooth_2.23-14          dplyr_0.4.1
                 [61] GEOmetadb_1.29.0            RSQLite_1.0.0
                 [63] DBI_0.3.1                   GEOquery_2.35.4
                 [65] Biobase_2.29.1              BiocGenerics_0.15.0
                 [67] bigrquery_0.1.0.9000

BiocInstaller_1.19.5

                 [69] magrittr_1.5                gtools_3.4.2

                 loaded via a namespace (and not attached):
                    [1] Hmisc_3.16-0            plyr_1.8.2
        splines_3.2.0
                    [4] BiocParallel_1.3.9      ggplot2_1.0.1
          digest_0.6.8
                    [7] SuppDists_1.1-9.1       gdata_2.16.1
        GMD_0.3.3
                 [10] checkmate_1.5.2         BBmisc_1.9
        cluster_2.0.1
                 [13] annotate_1.47.0         siggenes_1.43.0
                   colorspace_1.2-6
                 [16] tcltk_3.2.0             registry_0.2
        gtable_0.1.2
                 [19] zlibbioc_1.15.0         RGCCA_2.0
          evd_2.3-0
                 [22] scales_0.2.4            futile.options_1.0.0
        pheatmap_1.0.2
                 [25] rngtools_1.2.4          Rcpp_0.11.6
          xtable_1.7-4
                 [28] foreign_0.8-63          bit_1.1-12
                 preprocessCore_1.31.0
                 [31] Formula_1.2-1           lava_1.4.0
        glmnet_2.0-2
                 [34] httr_0.6.1              gplots_2.17.0
                   RColorBrewer_1.1-2
                 [37] acepack_1.3-3.3         ff_2.2-13
          reshape_0.8.5
                 [40] XML_3.98-1.1            nnet_7.3-9
        reshape2_1.4.1
                 [43] munsell_0.4.2           tools_3.2.0
          stringr_1.0.0
                 [46] bootstrap_2015.2        beanplot_1.2
        caTools_1.17.1
                 [49] doRNG_1.6               nor1mix_1.2-0
          biomaRt_2.25.1
                 [52] stringi_0.4-1           superpc_1.09
                 futile.logger_1.4.1
                 [55] GenomicFeatures_1.21.2  survcomp_1.19.0
          gbm_2.1.1
                 [58] survivalROC_1.0.3       multtest_2.25.0
          R6_2.0.1
                 [61] latticeExtra_0.6-26     gridExtra_0.9.1
                   affxparser_1.41.2
                 [64] codetools_0.2-11        lambda.r_1.1.7
        seqLogo_1.35.0
                 [67] MASS_7.3-40             assertthat_0.1
        proto_0.3-10
                 [70] pkgmaker_0.22           GenomicAlignments_1.5.8
                 Rsamtools_1.21.4
                 [73] mixOmics_5.0-4          rpart_4.1-9
          base64_1.1
                 [76] illuminaio_0.11.0       rmeta_2.16




                 Statistics is the grammar of science.
                 Karl Pearson
        <http://en.wikipedia.org/wiki/The_Grammar_of_Science>

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Bioc-devel at r-project.org

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        <mailto:hpages at fredhutch.org <mailto:hpages at fredhutch.org>>
             Phone: (206) 667-5791 <tel:%28206%29%20667-5791>
        <tel:%28206%29%20667-5791>
             Fax: (206) 667-1319 <tel:%28206%29%20667-1319>
        <tel:%28206%29%20667-1319>

--
Herv? Pag?s

Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024

E-mail: hpages at fredhutch.org
Phone:  (206) 667-5791
Fax:    (206) 667-1319

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