Analyzing dataset with counts and TMM values?

Question

[trkfs]

Hello! To preface, I am a total beginner to bioinformatics.

I am analyzing a dataset of Alzheimer's disease for my project. The dataset contains a number of genes and their counts and TMM values across 6 different samples.

I have analyzed a different dataset containing genes and their logFC values to determine the upregulated and downregulated genes, so I have some idea how to analyze datasets like that, but this is the first time I'm encountering TMM values and I'm a little unsure how to go about analyzing gene expression levels (or if that is the next step at all). I would really appreciate any tips, resources, tutorials, etc. Thank you so much!

Answer 1

[nhaus]

Hey trkfs,

I assume you are talking about bulk RNAseq samples? In this case, I recommand you take a look at the extremely useful and comprehensive DESeq2 vignette. This will give you an idea how to get from counts to a table which contains differentially expressed genes. Alternatively, you can also use edgeR. A useful pointer for this, would be this paper.

On a side note, TMM values are very useful for visualizing the expression differences between samples for a given gene. However, if you are interested in identifiying differentially expressed genes (which is almost always the case) all state-of-the-art tools/methods use raw counts.

[trkfs]

Hi nhaus, yes the dataset is RNAseq samples. And thank you so much for your answer! Really grateful for the resources you've provided and your explanations. Helped clear up my confusion :)