DESEQ2 IHW and Apelgm method for Shrinkage (adding s values to FDR)
1
0
Entering edit mode
kcarey • 0
@b626d890
Last seen 10 hours ago
United States

Hello,

I am having a hard time interpreting the IHW and Shrinkage method results. I have read the paper, and also vignette and other various other question threads. I understand the purpose of the methods, however, not sure how to interpret their results.

I have currently run a code:

dds<- DESeqDataSetFromMatrix(countData = counts_DE_subset, 
                             colData = batch_condition_numericMeta,
                             design = ~ batch + Subtype_mRNA)
#IHW
LFC_DiffervsImmuno<-results(dds,name="Subtype_mRNA_Differentiated_vs_Immunoreactive", lfcThreshold= 1, alpha = 0.05, filterFun = ihw)
LFC_ProlifvsImmuno<-results(dds,name = "Subtype_mRNA_Proliferative_vs_Immunoreactive",lfcThreshold= 1, alpha = 0.05, filterFun = ihw)
LFC_MesenvsImmuno<-results(dds,name="Subtype_mRNA_Mesenchymal_vs_Immunoreactive",lfcThreshold= 1, alpha = 0.05, filterFun = ihw)
#Shrinkage
DvI_shrinkage_LFCT<-lfcShrink(dds,coef ="Subtype_mRNA_Differentiated_vs_Immunoreactive", type = "apeglm",lfcThreshold = 1, format = "DataFrame")
PvI_shrinkage_LFCT<-lfcShrink(dds,coef= "Subtype_mRNA_Proliferative_vs_Immunoreactive",lfcThreshold= 1, format = "DataFrame")
MvI_shrinkage_LFCT<-lfcShrink(dds,coef = "Subtype_mRNA_Mesenchymal_vs_Immunoreactive",lfcThreshold= 1, format = "DataFrame")```

The results I obtained for IHW is what I anticipated to see, however, I got many p values that had "1.000000e+00" and padj "1" and stat of "0" when I added the Log threshold of LFC >1 and LFC < -1...is this normal? Also, for my s-values for shrinkage, I got many 0's...is this what is to be expected? I figured this may have been because the values were so small, this is what the algorithm placed them as 0.

I received different gene lists for each condition (which the paper says I should expect). Some genes were similar, and I made note of those genes for deeper evaluation, as they were found in both methods. I had been creating visualizations using volcano plots and MA plots for both methods. However, after reading online, it was suggested for others to add the s-values to the IHW DF for the particular gene. In this case, I have four different conditions for each of my subtypes, with immunoreactive being my reference level. Would I add the s-values obtained for each condition to the IHW data frame) how would I report both?

Many thanks for all your help!

Signed, a stressed out Graduate student!

DESeq2 RNAseq • 142 views
ADD COMMENT
0
Entering edit mode
@mikelove
Last seen 10 hours ago
United States

I got many p values that had "1.000000e+00" and padj "1" and stat of "0" when I added the Log threshold of LFC >1 and LFC < -1...is this normal?

Yes.

For example, suppose you have a gene with estimated LFC ~= 0 and low SE.

Then you ask about the null hypothesis abs(LFC) < 1.

p-value of 1 seems reasonable right?

I got many 0's...is this what is to be expected?

Yes, genes with estimated LFCs consistent with 0 are often shrunk to 0, this can be seen in the plots in paper and vignette.

You don't need to use the s-values, you can just work with IHW genes and report their shrunken LFC if you want.

ADD COMMENT

Login before adding your answer.

Traffic: 396 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6