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3.3 years ago by
sjs02820
sjs02820 wrote:

Hello Everyone,

I'm very new to the RNAseq Field. I'm trying to adjust for Sex and Age within our Dataset. I have 11 case and 12 Control samples that we have generated RNA seq data for. We've used tophat and DESEQ for the analysis. However, our samples are post mortem human brain tissue and we would want to know if there is a way to adjust for Sex and Age as each sample is either male or female and also if' it's possible to adjust for age. Does anyone know of a way to include these covariates within the analysis pipeline. Any guidance would be of great help.

Thanks,

Shantanu J. Shewale

sjs0282@live.unthsc.edu

Department of Molecular and Medical Genetics
University of North Texas Health Science Center

modified 3.3 years ago by Michael Love24k • written 3.3 years ago by sjs02820
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3.3 years ago by
Michael Love24k
United States
Michael Love24k wrote:

I'd recommend you use the newer methodology DESeq2 as opposed to DESeq.

In the software vignette we show how to include additional covariates in the design, by just adding these to the beginning of the formula: ~sex + age.bin + condition

library("DESeq2")
vignette("DESeq2")

Make sure that you also read the FAQ at the end of the vignette, where I discuss my recommendation for including continuous covariates like age, using the cut() function, to produce categorical data.

Thank you so much for your prompt response Michael. I'll look at DESeq2 and get back to you if I have any questions.

Thank you so much for your prompt response Michael. I'll look at DESeq2 and get back to you if I have any questions.