Hello Biostars!
I (and collaborators) recently performed a patch-seq experiment... That is, we did patch-clamp recording of neuronal firing, then aspirated the contents of recorded cells, and made RNA seq compatible libraries.
Data look alright - certainly there is a lot of PCR duplication. Probably a combined effect of too many PCR cycles and no UMIs in the kit we used.
To analyze, I did a STAR -> deduplicate -> htseq-count -> DESeq2 pipeline. I think I am getting meaningful results and cells that are expected to be similar cluster together.
But I have an odd MA plot that is giving me some pause:
The low expression transcripts are DRAMATICALLY skewed toward one group. I am thinking that this must be an artifact. In my downstream analyses, I have filtered based on a minimum of normalized counts, but I am wondering if anyone has encountered an odd graph like this and how you have dealt with it? Should I filter raw reads before performing DESeq? Thanks very much in advance!
Can you show the unshrunken MA-plot? This is apeglm right? How many replicates is this?
Thanks for responding!
Replicates are 3 in one condition, 4 in the other.
Sorry, do you mean MA-plot with non-shrunken LFC values? I am still running my alignments and DESeq on usegalaxy. As far as I can tell, the LFC values are not shrunken by default.
Yes that is what I meant. This here is most likely a shrunken MA plot. Unshrunken plots have highest logFC at low average expression while shrunken ones tends to shrink low expressed genes towards LFC of 0 (this is from my limited understanding at least the basic idea of shrinkage in this context). I would try DESeq2 in R outside Galaxy to have better control over all parameters. It is computationally not expensive, every laptop can do it. Doing so you can produce the unshrunken MA-plot.
What you can also do is to post this question over at the Bioconductor support forum so that the DESeq2 maintainer (Mike Love) can have a look. Still I would try via R on a local machine first so that you can post exact code.
This is helpful information... I have a decent amount of experience with R, but I did my first seq analyses on galaxy, and so... if it aint broke, don't fix it, right? Well, I guess now it's broke, lol. Will give it a shot. Cheers
You can follow pretty much 100% the example code for DESeq2 from the manual for standard analysis. It is just a few lines of code.