RPKM = reads per kilobase of transcript per million reads (either aligned or sequenced or left after filtering). If a microRNA is 22 bases and has 200 reads aligning to it then you're already at >9000 RPK. The M just scales that a bit. So don't expect microRNA values to be in the same range as regular genes.
I am analyzing microrna-seq dataset when I do Differential analysis of two grps of samples the rpkm values of each grp are very high ( as pasted below) I am doing this in partek genome studio. When i look at the raw reads they seems reasonable 200, 345 20 and so on.
Here are unusual values screen shot- any suggestion 1430000.00 2430000.00 2640000.00 2970000.00 1200000.00 3540000.00 952.56 1669.73 439.35 2184.37 1959.18 352.58 571.54 2504.60 878.70 1310.62 1959.18 2115.48 298778.00 1240000.00 1080000.00 741437.00 1560000.00 1170000.00
3 answers
- miRNA are tissue specific so if you're trying to compare tissues you'll get 200 vs 0 so you'll get infinity.
- Pay good attention how you normalize the libraries, if you compute RPKM and there are highly expressed genes that are changes, the miRNA will change accordingly, I suggest you'll take only the miRNA reads and just compare counts (after a normalization).
microRNAs are very small, so...
Devon Could you please complete your thoughts. I could not guess please. If microRNA are small that means reads are few base pairs?
That is also a reason why RPKM shouldn't be used for miRNA seq. Length normalization is not required for something that has almost always the same length.
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