[Bioc-devel] Broken pathway in graphite package?

Hello,

this problem is caused by the presence of interaction type 
"control(In(INHIBITION-COMPETITIVE))" which is missing in the 
unexported spiaConv table and that leads to NA's during the 
processing. It must be fixed by package maintainer. You will run into 
same problems with these pathways:

Insulin receptor signalling cascade                      IRS 
activation                  IRS-related events                      
SHC activation
651                                 691                                
693 1197
                 SHC-related events       Signaling by Insulin 
receptor                  Signaling Pathways
                               1203 1235  
                              1263


Ivana


Dne 2015-06-16 21:17, Ryan C. Thompson napsal:

Hello,

I was attempting to run SPIA through the graphite package and ran into
an odd error when running prepareSPIA on the human Reactome pathways.
You can reproduce the error simply and quickly by:

library(graphite)
prepareSPIA(pathways("hsapiens", "reactome")["Insulin receptor 
signalling cascade"], "test", TRUE)

Insulin receptor signalling cascade
Error in Filter(Negate(is.null), lapply(db, function(p) { :
  error in evaluating the argument 'x' in selecting a method for
function 'Filter': Error in if (e[1] <= e[2]) paste(e[1], e[2], sep =
"|") else paste(e[2],  :
  missing value where TRUE/FALSE needed

The traceback is not particularly informative. I don't actually see
the line of code from the error message in the traceback:

traceback()

4: Filter(Negate(is.null), lapply(db, function(p) {
       if (print.names)
           cat(p at title, "\n")
       p <- convertIdentifiers(p, "entrez")
       es <- edges(p)
       if (NROW(es) == 0 || NROW(unique(es[, 1:2])) < 5)
           return(NULL)
       ns <- nodes(p)
       es <- merge(es, spiaConv, all.x = TRUE)[c("src", "dest",
           "direction", "spiaType")]
       l <- sapply(spiaAttributes, simplify = FALSE, USE.NAMES = TRUE,
           function(edgeType) {
               est <- es[es[, 4] == edgeType, , drop = FALSE]
               gnl <- buildGraphNEL(ns, est, TRUE)
               t(as(gnl, "matrix"))
           })
       l$title <- p at title
       l$nodes <- ns
       l$NumberOfReactions <- 0
       return(l)
   }))
3: .prepareSPIA(db at entries, pathwaySetName, print.names)
2: prepareSPIA(pathways("hsapiens", "reactome")["Insulin receptor
signalling cascade"],
       "test", TRUE)
1: prepareSPIA(pathways("hsapiens", "reactome")["Insulin receptor
signalling cascade"],
       "test", TRUE)

I guess for now I will remove the offending pathway, but it seems
unexpected that graphite cannot handle a pathway included in its own
package.

-Ryan Thompson

sessionInfo()

R version 3.2.0 (2015-04-16)
Platform: x86_64-unknown-linux-gnu (64-bit)
Running under: Ubuntu 14.04.2 LTS

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] grDevices datasets  parallel  graphics  stats4    stats utils
[8] methods   base

other attached packages:
 [1] org.Hs.eg.db_3.1.2        GSEABase_1.30.2
 [3] graph_1.46.0              annotate_1.46.0
 [5] XML_3.98-1.2              graphite_1.14.0
 [7] openxlsx_2.5.10           DESeq2_1.8.1
 [9] RcppArmadillo_0.5.200.1.0 Rcpp_0.11.6
[11] edgeR_3.10.2              limma_3.24.10
[13] magrittr_1.5              dplyr_0.4.1
[15] biomaRt_2.24.0            functional_0.6
[17] sqldf_0.4-10              RSQLite_1.0.0
[19] DBI_0.3.1                 gsubfn_0.6-6
[21] proto_0.3-10              GenomicFeatures_1.20.1
[23] AnnotationDbi_1.30.1      chipseq_1.18.0
[25] BSgenome_1.36.0           inline_0.3.14
[27] affy_1.46.1               rtracklayer_1.28.4
[29] Biobase_2.28.0            ShortRead_1.26.0
[31] GenomicAlignments_1.4.1   BiocParallel_1.3.16
[33] Rsamtools_1.20.4          Biostrings_2.36.1
[35] XVector_0.8.0             GenomicRanges_1.20.5
[37] GenomeInfoDb_1.4.0        doParallel_1.0.8
[39] iterators_1.0.7           foreach_1.4.2
[41] plyr_1.8.3                stringr_1.0.0
[43] IRanges_2.2.4             ggplot2_1.0.1
[45] S4Vectors_0.6.0           BiocGenerics_0.14.0
[47] BiocInstaller_1.18.3

loaded via a namespace (and not attached):
 [1] splines_3.2.0         assertthat_0.1 Formula_1.2-1
 [4] latticeExtra_0.6-26   lattice_0.20-31 chron_2.3-45
 [7] digest_0.6.8          RColorBrewer_1.1-2 colorspace_1.2-6
[10] preprocessCore_1.30.0 genefilter_1.50.0 zlibbioc_1.14.0
[13] xtable_1.7-4          scales_0.2.5 affyio_1.36.0
[16] lazyeval_0.1.10       nnet_7.3-9 survival_2.38-2
[19] MASS_7.3-40           hwriter_1.3.2 foreign_0.8-63
[22] tools_3.2.0           munsell_0.4.2 locfit_1.5-9.1
[25] cluster_2.0.1         lambda.r_1.1.7 compiler_3.2.0
[28] futile.logger_1.4.1   grid_3.2.0 RCurl_1.96-0
[31] bitops_1.0-6          gtable_0.1.2 codetools_0.2-11
[34] reshape2_1.4.1        gridExtra_0.9.1 Hmisc_3.16-0
[37] futile.options_1.0.0  stringi_0.4-1 geneplotter_1.46.0
[40] rpart_4.1-9           acepack_1.3-3.3