DESeq2 - Design for TCGA unpaired RNAseq data
1
0
Entering edit mode
Talip Zengin ▴ 10
@talip-zengin-14290
Last seen 20 days ago
Mugla, Turkiye

Hello everybody,

I am using TCGA LUAD RNAseq data for DEG analysis. There are data of 522 patients, only 59 of them have paired (have normal and tumor sample) data without replicates. Can I compare all data of tumor samples (522) against all data of normal samples (59)? Is it possible in statistics? Or is it more logical to use paired samples? How should I design the DESeq2 analysis if it is possible to use unpaired data?

I input the data as summarized experiment and used design for paired samples as below:

> library("DESeq2")
> ddsSE <- DESeqDataSet(data, design = ~ patient + shortLetterCode)
> ddsSE$shortLetterCode <- relevel(ddsSE$shortLetterCode, ref = "NT")
> DE <- DESeq(ddsSE)
> DEresults <- results(DE)

shortLetterCode column have "NT" (Solid Tissue Normal) and "TP" (Primary Solid Tumor) sample types and I used relevel command to make "NT" as reference sample.

Should I remove "patient" from design part for unpaired samples?

Can we test for the tumor vs normal effect, controlling for patient effect by using unpaired samples?

Thanks.

DESeq2 design TCGA unpaired RNAseq • 981 views
1
Entering edit mode
@mikelove
Last seen 1 hour ago
United States

If you have a mix of paired and unpaired samples, you should use limma-voom with the duplicateCorrelation() function. There is not a good way to control for the mix of paired and unpaired with fixed effects models.

0
Entering edit mode