Dear all,
On receiving transcriptome data for my bacterial samples, I obtained around 400 differentially regulated genes for each treatment (total 3 different treatments were done). However, since the total number of differentially expressed genes obtained is quite high, what is the most reported/accepted number of genes that I can validate by qRT-PCR, and how would I justify this?
Hi Joyleen
it really depends on the study and the analysis
the point after processing transcriptomics is to reduce the signature enough to rely on the genes you'll select to address a sample in its right category, and also to avoid waisting time and money of course.
selecting a high FC with good Pval giving you a list of about 20 genes is enough.
all the best
fred
Hello Joyleen Maryann Fernandes,
The "validation" of RNA-Seq by qRT-PCR type techniques does not seem to me to be relevant anymore.
Indeed, quality controls inherent to the RNA extraction technique & its quantity / quality (Qubit Fluorometric Quantitation, Agilent Bioanalyzer, Nanodrop, RNA Integrity Number [RIN], etc...) coupled with an adapted sequencing technique does not require any more at the present time validation by qRT--PCR.
However, it is still interesting to focus on genes of interest (those with a strong adjusted p-value coupled to high fold-change) presented among the numerous DEGs.
Do not forget that there are analyses that can help in this choice (GO Terms, KEGGs Pathways, GSEA, Volcano plots representation, etc...).
Hoping that this comment will be useful. Feel free to discuss or share some informations about your RNA-Seq validations / assessment studies.
Ludovic Dumont, Ph.D.
Technically, you don't need to validate anything. After all, it's Sequencing.
In case if you really want to, then focus on interesting genes belonging to particular pathway/pathways that you see modulated/dysregulated in all the treatment groups.
Thank you all for your suggestions and valuable input! Will include all of these into my analysis!
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