Question: Deseq2 polysome profiling analysis
0
gravatar for irene.diaz
4 months ago by
irene.diaz0
irene.diaz0 wrote:

Hello everybody! I have a question about an analysis of my polysome profiling experiment. In my case I have to conditions (with and without treatment) and two sample types for each condition, the mRNAs bound to the monosomal fractions (only to a single ribosome, or its preinitiation forms) and mRNAs bound to polysomal fractions (more than one ribosome). I want to compare the translation efficiency, that is defined as the ratio between the polysomal/monosomal lectures os each gene, in my treatmets, so I think I have to do a ratio of ratios. I also want to add the bath effect due to each sample type is from the same sample, and I have replicates. I'm using DESeq2, and my script is:

data <- DESeqDataSetFromMatrix(countData = countData,colData = colData,design = ~ batch + sampleType + condition + sampleType:condition) dds <- DESeq(data, reduced = ~ batch + condition + sampleType, test="LRT")

I'm not sure if I'm doing properly. Also, I don't undestand at all what's the meaning of the log2foldchange and the pvales that the DESeq2 returns for this analysis, because I read that for the LTR test there are no direct correlation between them, so I'm not sure how to interpret them.

Thank you very much in advance!!

rnaseq deseq2 • 117 views
ADD COMMENTlink modified 4 months ago by Michael Love24k • written 4 months ago by irene.diaz0
Answer: Deseq2 polysome profiling analysis
0
gravatar for Michael Love
4 months ago by
Michael Love24k
United States
Michael Love24k wrote:

Have you seen this post yet:

https://support.bioconductor.org/p/61509/

Let me know if you have any remaining questions after reading that post.

ADD COMMENTlink modified 4 months ago • written 4 months ago by Michael Love24k

Hello Michael, Yes, this post gave me the idea of how to do the analysis. My questions are, do I add the batch effect correctly?and whats the meaning of the pvalues in this kind of analisys? I've read this about the LTR test: "The p-values are determined solely by the difference in deviance between the ‘full’ and ‘reduced’ model formula (not log2 fold changes)" So could I assume that the p-value of one gene is saying that foldchange in that gene has that statistic significance? The vulcano plot of this analysis is very strange for me, and it's confusing.

Thank you very much for your time!!

Irene

ADD REPLYlink written 4 months ago by irene.diaz0

Have you read the vignette section on the LRT?

ADD REPLYlink written 4 months ago by Michael Love24k
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