Question: stageR with input from DRIMSeq
gravatar for sdvie
6 months ago by
sdvie0 wrote:

Dear all,

I am trying to follow the protocol to input DRIMSeq results into stageR, as described in the DRIMSeq manual , page 16 f. Some of my DRIMSeq p-values are NA, so I used:

stageRObjadj <- stageWiseAdjustment(object = stageRObj, method = "dtu", alpha = 0.05, allowNA=TRUE)

However, I get the following message:

Removing 15 features with NA screening hypothesis p-values. Error in pConfirmation[id, ] : incorrect number of dimensions

My input data are formatted like this:

head(pScreen) ENSMUSG00000033845.13 ENSMUSG00000025903.14 ENSMUSG00000033813.15 0.2724130 0.4104909 0.5927421 ENSMUSG00000033793.12 ENSMUSG00000025907.14 ENSMUSG00000033740.17 0.9635464 0.5629003 0.6726753

dim(pScreen) NULL


head(pConfirmation) [,1] ENSMUST00000130201.7 0.1271833 ENSMUST00000156816.6 0.2192786 ENSMUST00000045689.13 0.5070968 ENSMUST00000115538.4 0.4540733 ENSMUST00000192286.1 0.1580764 ENSMUST00000146665.2 0.4084662

dim(pConfirmation) [1] 36217 1

Does someone have experience with these two packages and can tell what is is that I am missing? I would be very grateful for any hints and suggestions. Many thanks, best, Sophia

sessionInfo() R version 3.5.1 (2018-07-02) Platform: x8664-condacos6-linux-gnu (64-bit) Running under: Ubuntu 18.04.2 LTS Matrix products: default BLAS/LAPACK: /project/miniconda3/envs/transcriptometutorial/lib/R/lib/ locale: [1] LCCTYPE=enUS.UTF-8 LCNUMERIC=C
[11] LCMEASUREMENT=enUS.UTF-8 LCIDENTIFICATION=enUS.UTF-8 attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets [8] methods base
other attached packages: [1] ShortRead1.40.0 GenomicAlignments1.18.0
[3] Rsamtools1.34.0 Biostrings2.50.1
[5] XVector0.22.0 stageR1.4.0
[7] kableExtra1.0.1 digest0.6.18
[9] xlsx0.6.1 session1.0.3
[11] tidyr0.8.2 ggplot23.1.0
[13] usethis1.4.0 devtools2.0.1
[15] DEXSeq1.28.0 RColorBrewer1.1-2
[17] DESeq21.22.1 SummarizedExperiment1.12.0 [19] DelayedArray0.8.0 matrixStats0.54.0
[21] BiocParallel1.16.2 edgeR3.24.1
[23] limma3.38.3 dplyr0.8.0.1
[25] GenomicFeatures1.34.1 GenomicRanges1.34.0
[27] GenomeInfoDb1.18.1 AnnotationDbi1.44.0
[29] IRanges2.16.0 S4Vectors0.20.1
[31] Biobase2.42.0 BiocGenerics0.28.0
[33] DRIMSeq1.10.0 yaml2.2.0
loaded via a namespace (and not attached): [1] colorspace1.4-0 hwriter1.3.2 rprojroot1.3-2
[4] htmlTable
1.13.1 base64enc0.1-3 fs1.2.6
[7] rstudioapi0.9.0 remotes2.0.2 bit640.9-7
[10] xml2
1.2.0 splines3.5.1 geneplotter1.60.0
[13] knitr1.21 pkgload1.0.2 Formula1.2-3
[16] rJava
0.9-10 annotate1.60.0 cluster2.0.7-1
[19] readr1.3.1 compiler3.5.1 httr1.4.0
[22] backports
1.1.3 assertthat0.2.0 Matrix1.2-15
[25] lazyeval0.2.1 cli1.0.1 acepack1.4.1
[28] htmltools
0.3.6 prettyunits1.0.2 tools3.5.1
[31] gtable0.2.0 glue1.3.0 GenomeInfoDbData1.2.0 [34] reshape21.4.3 Rcpp1.0.0 rtracklayer1.42.1
[37] xfun0.5 stringr1.4.0 ps1.3.0
[40] xlsxjars
0.6.1 rvest0.3.2 statmod1.4.30
[43] XML3.98-1.16 zlibbioc1.28.0 scales1.0.0
[46] hms
0.4.2 memoise1.1.0 gridExtra2.3
[49] biomaRt2.38.0 rpart4.1-13 latticeExtra0.6-28
[52] stringi
1.2.4 RSQLite2.1.1 genefilter1.64.0
[55] desc1.2.0 checkmate1.8.5 pkgbuild1.0.2
[58] rlang
0.3.1 pkgconfig2.0.2 bitops1.0-6
[61] evaluate0.12 lattice0.20-38 purrr0.2.5
[64] htmlwidgets
1.3 bit1.1-12 tidyselect0.2.5
[67] processx3.2.1 plyr1.8.4 magrittr1.5
[70] R6
2.4.0 Hmisc4.1-1 DBI1.0.0
[73] pillar1.3.1 foreign0.8-71 withr2.1.2
[76] survival
2.43-3 RCurl1.95-4.11 nnet7.3-12
[79] tibble2.0.1 crayon1.3.4 rmarkdown1.11
[82] progress
1.2.0 locfit1.5-9.1 grid3.5.1
[85] data.table1.11.6 blob1.1.1 callr3.1.1
[88] webshot
0.5.1 xtable1.8-3 munsell0.5.0
[91] viridisLite0.3.0 sessioninfo1.1.1

drimseq stager • 129 views
ADD COMMENTlink modified 6 months ago by Koen Van den Berge170 • written 6 months ago by sdvie0
Answer: stageR with input from DRIMSeq
gravatar for Koen Van den Berge
6 months ago by
Ghent University, Belgium
Koen Van den Berge170 wrote:

Hi Sophia,

The message about the removal of NA p-values is simply there for your information to check how many features have been removed prior to the analysis. Note that, even though you set allowNA=TRUE, nothing can be said about NA p-values, so they must be removed. Hence you can safely continue your analysis. Let me know if this does not answer your question.

ADD COMMENTlink written 6 months ago by Koen Van den Berge170
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