Observation weights in zinbwave and it's use in deseq
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3.7 years ago
pkallurkar • 0

Hello,

I have patch-seq data (n = 16 samples). I am interested in using ZINB-WaVE along with DESeq2 to extract DE genes. I am comparing the results if I run DESeq2 only and ZINB-WaVE plus DESeq2. I don't see any difference if Observation weights = FALSE. The number of DE significant genes (p-adj < 0.01 and L2FC > 1.5) are 123 genes, for both the cases.

However, if I do set Observation weights = TRUE, the number of DE genes post-ZINB-WaVE plus DESeq2 goes up to 1515 genes. Can someone please explain how DESeq2 is using the observation weights for analysis?

Thanks in advance.

zinbwave data deseq • 886 views
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Hi, you may want to post on Bioconductor support: https://support.bioconductor.org/ When you do that, please link up the 2 questions with a comment. Thanks

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