[Bioc-devel] Modeling (statistic, p-value) pairs in MultiAssayExperiment
Just realized my answer yesterday went to Francesco and not the list: Since it sounds like you have two matrices of the same dimensions, why not represent these as two assays in a SummarizedExperiment? E.g.:
statvals <- matrix(rnorm(100), ncol=5) pvals <- pnorm(statvals) library(SummarizedExperiment) se <- SummarizedExperiment(list(statvals = statvals, pvals = pvals)) se
class: SummarizedExperiment dim: 20 5 metadata(0): assays(2): statvals pvals rownames: NULL rowData names(0): colnames: NULL colData names(0):
If you then have more than one of these, with different dimensions, then MultiAssayExperiment would be of use to you. (PS: this question is probably better suited for support.bioconductor.org)
On Oct 23, 2017 4:50 PM, "Vincent Carey" <stvjc at channing.harvard.edu> wrote:
no answers yet? would it work to put your matrices as separate assays in a SummarizedExperiment? as long as they are conformant in dimensions and dimnames I think that would work. That SummarizedExperiment would then work well in an MAE. On Mon, Oct 23, 2017 at 1:00 PM, Francesco Napolitano <franapoli at gmail.com
wrote:
Hi, I'm trying to build a MultiAssayExperiment. However, in my case each assay should ideally include two matrices: one with a statistic and another one with the corresponding p-value. I'm currently managing each of them simply as a list of two matrices, but assay class expects table-like data. I must also be able to quickly extract entire rows or columns from each matrix. Is there a suitable way to model this into a MultiAssayExperiment? Thank you, Francesco
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