Hello,
I have a question to the DESeq2 contrast parameter of the results function. I have single end reads from 16 samples with 4 treatments (group) and 4 biological replicates (indi). However, the RNA of the replicates was isolated on different days. Can I still correct for the RNA-isolation day bias (iso)?
My meta table looks like this:
group indi iso
T1 I1 A
T1 I2 A
T1 I3 B
T1 I4 B
T2 I1 A
T2 I2 A
T2 I3 B
T2 I4 B
T3 I1 A
T3 I2 A
T3 I3 B
T3 I4 B
T4 I1 A
T4 I2 A
T4 I3 B
T4 I4 B
I followed the instructions for such case from the DESeq2 manual:
ds_txi <- DESeqDataSetFromTximport(txi = txi_salmon,
colData = meta,
design = ~ indi+group)
ds_txi$indi_n <- c("I1","I2","I1","I2","I1","I2","I1","I2","I1","I2","I1","I2","I1","I2","I1","I2")
meta$indi_n <- c("I1","I2","I1","I2","I1","I2","I1","I2","I1","I2","I1","I2","I1","I2","I1","I2")
meta$indi_n <- as.factor(meta$indi_n)
ds_txi$indi_n <- as.factor(ds_txi$indi_n)
ds_txi <- DESeqDataSetFromTximport(txi = txi_salmon,
colData = meta,
design = ~ iso+ iso:indi_n + iso:group)
Resulting in following meta table:
group indi iso indi_n
T1 I1 A I1
T1 I2 A I2
T1 I3 B I1
T1 I4 B I2
T2 I1 A I1
T2 I2 A I2
T2 I3 B I1
T2 I4 B I2
T3 I1 A I1
T3 I2 A I2
T3 I3 B I1
T3 I4 B I2
T4 I1 A I1
T4 I2 A I2
T4 I3 B I1
T4 I4 B I2
With following contrast, I get the difference between treatment T1 and T2 within Batch of isolation date A:
dds<- DESeq(ds_txi)
res<- results(dds,contrast=list("isoA.groupT1","isoA.groupT2"), alpha= p_adjust_treshold, lfcThreshold = L2FC_treshold)
But how can I get the general differences between treatment (group) T1 and T2 with elimination of the RNA-isolation date batch effect, if thats possible?
Could I maybe just do something like this:
res<- results(dds,contrast=list(c("isoA.groupT1","isoB.groupT1"),c("isoA.groupT2","isoB.groupT2")), alpha= p_adjust_treshold, lfcThreshold = L2FC_treshold)
This is may session info as requested:
> sessionInfo()
R version 3.6.2 (2019-12-12)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18362)
Matrix products: default
locale:
[1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252
[3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C
[5] LC_TIME=German_Germany.1252
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] RColorBrewer_1.1-2 pheatmap_1.0.12 scatterplot3d_0.3-41
[4] edgeR_3.28.1 limma_3.42.2 ModCon_0.2.0
[7] data.table_1.12.8 readr_1.3.1 vsn_3.54.0
[10] hexbin_1.28.1 DESeq2_1.26.0 SummarizedExperiment_1.16.1
[13] DelayedArray_0.12.3 BiocParallel_1.20.1 matrixStats_0.56.0
[16] Biobase_2.46.0 GenomicRanges_1.38.0 GenomeInfoDb_1.22.1
[19] IRanges_2.20.2 S4Vectors_0.24.4 BiocGenerics_0.32.0
[22] rjson_0.2.20 tximport_1.14.2
loaded via a namespace (and not attached):
[1] bitops_1.0-6 bit64_0.9-7 tools_3.6.2 backports_1.1.7
[5] R6_2.4.1 affyio_1.56.0 rpart_4.1-15 Hmisc_4.4-0
[9] DBI_1.1.0 colorspace_1.4-1 nnet_7.3-14 tidyselect_1.1.0
[13] gridExtra_2.3 bit_1.1-15.2 compiler_3.6.2 preprocessCore_1.48.0
[17] htmlTable_1.13.3 scales_1.1.1 checkmate_2.0.0 genefilter_1.68.0
[21] affy_1.64.0 stringr_1.4.0 digest_0.6.25 foreign_0.8-76
[25] XVector_0.26.0 base64enc_0.1-3 jpeg_0.1-8.1 pkgconfig_2.0.3
[29] htmltools_0.4.0 htmlwidgets_1.5.1 rlang_0.4.6 rstudioapi_0.11
[33] RSQLite_2.2.0 farver_2.0.3 jsonlite_1.6.1 acepack_1.4.1
[37] dplyr_0.8.5 RCurl_1.98-1.2 magrittr_1.5 GenomeInfoDbData_1.2.2
[41] Formula_1.2-3 Matrix_1.2-18 Rcpp_1.0.4.6 munsell_0.5.0
[45] lifecycle_0.2.0 stringi_1.4.6 zlibbioc_1.32.0 grid_3.6.2
[49] blob_1.2.1 crayon_1.3.4 lattice_0.20-41 splines_3.6.2
[53] annotate_1.64.0 hms_0.5.3 locfit_1.5-9.4 knitr_1.28
[57] pillar_1.4.4 geneplotter_1.64.0 XML_3.99-0.3 glue_1.4.1
[61] latticeExtra_0.6-29 BiocManager_1.30.10 png_0.1-7 vctrs_0.3.0
[65] gtable_0.3.0 purrr_0.3.4 assertthat_0.2.1 ggplot2_3.3.0
[69] xfun_0.13 xtable_1.8-4 survival_3.1-12 tibble_3.0.1
[73] AnnotationDbi_1.48.0 memoise_1.1.0 cluster_2.1.0 ellipsis_0.3.1
We discourage cross-posting to biostars and BioC without explicitly linking the posts:
https://www.biostars.org/p/444660/
A lot of the advice you had already received on biostars is appropriate here.
Hi, unfortunately there was no advice for correcting the bias, thats why I tried again with a better phrasing of the question to avoid confusion.
Thanks for calling a one-day endeavour involving two experienced users who tried to provide you with help "no advise".
I appreciate the answers very much, but the question was closed on biostars by you for "not fitting the main topic of this site", before I knew how to proceed with my analysis. So I asked the question again slightly rephrased here. Now I know, that I should just ask here for futur similar topics. Sorry, I didn't want to offend you.
No, I closed the one on Boostars after this one was posted here to avoid that even more users invest double-effort. The
...does not fit the main topic...
is a phrase that is automatically being added when a topic is closed. That all is spilled milk under the bridge now so I suggest to forget about it and proceed with our daily duties. You are always welcome to post at any community you like but it is good practice to avoid crossposting.