Dear list,
I encountered a strange problem when using the DESeqDataSetFromMatrix command from DESeq2. I have set up the countData and colData in the required format the same as the sample data described in the tutorial. The column names of the countdata refer to samples, while the row names refer to genes. The row number of colData is the same as the samples. What causes the problem and how to fix it?
Any input would be very appreciated! Thank you!
Thanks,
Xiayu
> colData
condition
HOSC1-cellline HPVpos
UD-SCC2 HPVpos
UM-SCC104 HPVpos
UM-SCC47 HPVpos
UPCI_SCC090 HPVpos
UPCI_SCC152 HPVpos
UPCI_SCC154 HPVpos
UT-SCC45 HPVpos
VU-147T HPVpos
1483 HPVneg
183 HPVneg
....
> head(countdata[,1:11])
HOSC1-cellline UD-SCC2 UM-SCC104 UM-SCC47 UPCI_SCC090 UPCI_SCC152
A1BG 2 0 1 0 80 65
A1CF 0 0 0 0 0 0
A2M 3 0 0 0 1 0
A2ML1 157 1 190 21 759 747
A4GALT 625 0 780 590 346 1134
A4GNT 0 0 0 0 1 0
UPCI_SCC154 UT-SCC45 VU-147T 1483 183
A1BG 6 9 3 53 30
A1CF 0 0 0 1 5
A2M 1 0 1 2 1
A2ML1 1 32 4 14 2280
A4GALT 630 235 1414 107 2072
A4GNT 2 0 0 1 1
> dds <- DESeqDataSetFromMatrix(countData = countdata, colData = colData, design = ~ condition)
Error in validObject(.Object) :
invalid class RangesList?object: number of rows in DataTable 'mcols(x)' must match length of 'x'
> sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-unknown-linux-gnu (64-bit)
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] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] DESeq2_1.6.3 RcppArmadillo_0.4.320.0 Rcpp_0.11.3
[4] GenomicRanges_1.16.4 GenomeInfoDb_1.0.2 IRanges_1.22.10
[7] S4Vectors_0.4.0 BiocGenerics_0.12.1
loaded via a namespace (and not attached):
[1] acepack_1.3-3.3 annotate_1.42.1 AnnotationDbi_1.26.1
[4] base64enc_0.1-2 BatchJobs_1.3 BBmisc_1.8
[7] Biobase_2.24.0 BiocParallel_0.6.1 brew_1.0-6
[10] checkmate_1.5.1 cluster_1.15.3 codetools_0.2-9
[13] colorspace_1.2-4 DBI_0.3.1 digest_0.6.4
[16] fail_1.2 foreach_1.4.2 foreign_0.8-61
[19] Formula_1.1-2 genefilter_1.46.1 geneplotter_1.42.0
[22] ggplot2_1.0.0 grid_3.1.0 gtable_0.1.2
[25] Hmisc_3.14-6 iterators_1.0.7 lattice_0.20-29
[28] latticeExtra_0.6-26 locfit_1.5-9.1 MASS_7.3-35
[31] munsell_0.4.2 nnet_7.3-8 plyr_1.8.1
[34] proto_0.3-10 RColorBrewer_1.1-2 reshape2_1.4.1
[37] rpart_4.1-8 RSQLite_0.11.4 scales_0.2.4
[40] sendmailR_1.2-1 splines_3.1.0 stringr_0.6.2
[43] survival_2.37-7 tools_3.1.0 XML_3.98-1.1
[46] xtable_1.7-4 XVector_0.4.0
> dim(countdata)
[1] 20587 69
> dim(colData)
[1] 69 1
> class(colData)
[1] "data.frame"
Thank you for your reply!