I'm interested in removing variation in my data using RUVseq. I'm following the tutorial/vignette and was able to generate the estimated factors of unwanted variation using the RUVg function. Now I want to incorporate them into my differential expression analysis using DESeq2.
Here is what I have:
set_NHP_RUVg <- RUVg(set_NHP, empirical, k=1)
pData(set_NHP_RUVg)
key_IP_mf.Treatment W_1
1M_IP Day03 -0.2389338
2M_IP Day03 0.3677343
3M_IP Day03 -0.1828536
4M_IP Day10 -0.2924691
5M_IP Day10 0.3641969
6M_IP Uninjured -0.3050515
7M_IP Day20 0.1791624
8M_IP Day20 0.3791267
9M_IP Uninjured 0.3179415
11M_IP Day20 -0.3741618
12M_IP Uninjured -0.2146920
dds_RUVg <- DESeqDataSetFromMatrix(countData = counts(set_NHP_RUVg),
colData = pData(set_NHP_RUVg),
design = ~ W_1 + key_IP_mf$Treatment)
Error in DESeqDataSet(se, design = design, ignoreRank) : all variables in design formula must be columns in colData
But the two elements of my design are the two columns in my colData:
pData(set_NHP_RUVg)
key_IP_mf.Treatment W_1
1M_IP Day03 -0.2389338
2M_IP Day03 0.3677343
3M_IP Day03 -0.1828536
4M_IP Day10 -0.2924691
5M_IP Day10 0.3641969
6M_IP Uninjured -0.3050515
7M_IP Day20 0.1791624
8M_IP Day20 0.3791267
9M_IP Uninjured 0.3179415
11M_IP Day20 -0.3741618
12M_IP Uninjured -0.2146920
sessionInfo( )
R version 4.2.2 (2022-10-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.6.2
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] DESeq2_1.38.3 RColorBrewer_1.1-3 zebrafishRNASeq_1.18.0 RUVSeq_1.32.0
[5] edgeR_3.40.2 limma_3.54.2 EDASeq_2.32.0 ShortRead_1.56.1
[9] GenomicAlignments_1.34.1 SummarizedExperiment_1.28.0 MatrixGenerics_1.10.0 matrixStats_0.63.0
[13] Rsamtools_2.14.0 GenomicRanges_1.50.2 Biostrings_2.66.0 GenomeInfoDb_1.34.9
[17] XVector_0.38.0 IRanges_2.32.0 S4Vectors_0.36.2 BiocParallel_1.32.6
[21] Biobase_2.58.0 BiocGenerics_0.44.0
I'm just missing something. But I'm also following the vignette exactly.
Thanks! That was it... why did I think they were equivalent?