First time Statistical Analysis of RNA-seq
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@5c1d39af
Last seen 7 days ago
United States

OK. It is a long story. MS and a PhD in Molecular Biology, went back and got a Data Science certificate and I am tutoring and helping colleagues. Right now, I am trying to analyze a RNA-seq gene expression data set of genes related to intramuscular fat in black and White pigs to asses meat quality and see which genes are most crucial for meat quality. The genes are all over the place, expressed in different tissues, ATPases, and yes, some fat and muscle related and some more specific to intramuscular fat. The dataset already includes the p_Value for 3 Black pigs and and 3 White pigs separately, the p_value averages, and the fold change. I basically need to do a regression analysis, log2 fold change in a table, and make a log2 fold change line graph, separately. I am basically new to this and it seems like I can use edgeR? Yes, I can code a bit in R. However, this does not need to be too complex because right now, I just need to do a preliminary analysis, maybe using the most parsimonious code or method. Do I need to code in R, or can a program do it? After the preliminary analysis, I will do a larger analysis.

I have a basic idea of what I need to do, where I want to go with this, etc. but I do not want to go to far researching the most parsimonious way to do this and end up using a more complex, in depth method where I would get the same results from a quicker, more parsimonious method.

Thus, where is the best place to start. Having read a 2020 Nature paper, they used edgeR.

Any help is greatly appreciated, John

edgeR RNA-Seq log2 foldchange q_value • 87 views
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@james-w-macdonald-5106
Last seen 19 hours ago
United States

This isn't really the place to get advice on how to analyze your data. The primary intent is to help people with specific questions about specific packages.

That said, both DESeq2 and edgeR have comprehensive vignettes that might be of use. There are also workflows (for both, IIRC) that you can peruse.

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