Calculating standard deviation for a few genes using RNAseq data
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marhabaie • 0
@marhabaie-16361
Last seen 3.6 years ago

Is there a way to calculate standard deviation, standard error, or 95% confidence intervals for a few genes (~10) from RNAseq data? I am comparing RNAseq fold change values with qPCR ddCts and need to show some measure of uncertainty for RNAseq FC values. Need to add error bars to this graph I was hoping to be able to get some measure of uncertainty from edgeR (that I used to get DE genes) but as far as I found edgeR uses dispersion which is not what I need.

Thank you,

edger RNAseq • 1.5k views
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I am not an expert on this, but AFAIK it is is not possible to obtain errors or confidence intervals. See this thread. https://support.bioconductor.org/p/61640/

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This does not seem to be related to any Bioconductor package (?), even though you have tagged EdgeR. It seems that you may want geom_errorbar() from ggplot2, but, again, this is not related specifically to any Bioconductor package.

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Sorry for not being clear. I just edited the question. I was hoping to be able to get it out of edgeR that I used to get DE genes. My question is not how to plot, but is what data to use to calculate errors.

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After looking more carefully, I realized that ultimately I want to calculate the correlation between qPCR and RNAseq data. For this, I do NOT need error bars as they are not relevant here in calculating the correlation. Am I correct?

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@steve-lianoglou-2771
Last seen 14 months ago
United States

One way to get confidence intervals for logFC estimates from RNA-seq data is to use limma::voom.

Run the standard voom -> lmFit -> eBayes -> topTable analysis pipeline, and set the confint parameter in the topTable() function to TRUE. You'll get CI.L and CI.R columns that provide the lower and upper 95% confidence intervals you're after.

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