We have extracted RNA from our fungal strain, growing in three different carbon source growth conditions. We have received the RNA-Seq data and have carried out different gene expression analysis (DESeq) between either two of the growth conditions.
Now we are interested in the absolute gene expression levels across all the growth conditions apart from DESeq.
I have the raw hit-counts files ready in a table, first column is gene ID, 2-10 columns are the three replicates of condition 1, condition2 and condition3, respectively.
The next step would be normalization of the read counts and generate the absolute gene expression levels. However, I have limited knowledge of R, in this case, can I do it manually or have to use R to do that? Is there any package (including normalization) I can use? How can I generate a table or even a plot such as heatmap of the top 10 genes?
Thank you very much. Any hint or guide will be very much appreciated.
Hello Tiantian Fu,
DESeq2 can generate such files, usually the best one is VST normalized table, where you plot each gene alone with very little variations among samples.
Regarding the top 10, they are the 10 genes with the lowest FDR values from the DESeq2 results table, then you can go back to the VST normalized table and calculate the Z scores of the top 10 genes. After that you can use GraphPad prism to plot a heatmap.
Hope this helps
If you are familiar with the basics and just need the tools, Galaxy has all you need (usegalaxy.org)
If you have no/limited experience, RobiNA is a great beginner-friendly start-to-finish RNA-seq analysis tool
https://mapman.gabipd.org/robin
Sequencing based methods can not provide you information about the absolute gene expression and all the methods of analysis will give you the relative gene expressions. For the expression analysis of absolute values, you need to look into qPCR based methods.
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