RNA-seq RPKM >=1 increases after downsampling but RPKM >= 0.1 decreases after downsampling

Question

[yarrowmadrona]

Seven million reads were downsampled to 2.3 million. The RPKM >= 1 increased from 12979 to 13247. Meanwhile, RPKM >= 0.1 decreased from 20311 to 18847. This behavior was consistent across four experiments. I'm sorry I cannot provide more information as this experiment was presented by a colleague and I don't have the raw data at the moment. Why is this happening?

From reading biostars bioinformatics for dummys, RPKM = 10^9 * Ni / (sum) * 1/ L Ni is the total number of reads mapped to transcript i and sum is the sum of all transcripts mapped in millions of reads (10^6). 1/L is the length of the transcript in kilobases (10^3). The factor 10^9 comes from using the units millions of reads (10^6, and kilobases, 10^3)

Since RPKM units are 1/length of transcript, does this mean that downsampling preferentially removed shorter transcripts? Or that there were many more short transcripts so they were more likely to be removed upon downsampling than larger transcripts?

[yarrowmadrona]

Thanks. Do you have any resources/guides on how to run a chi-square test in this context?

[Istvan Albert]

Any chi-square tool will do, there are many online, that you could use. What you are testing for is whether the pairs

12979  20311
13247  18847

could be consistent with a random sampling.

[yarrowmadrona]

Thank you, Very helpful (sorry for the delay in response). Just wanted to check. You are right, looks like random variation

Answer 1

[Istvan Albert]

The random sampling means that your numbers will vary, they have to as there is a chance of hitting transcripts unevenly.

Even without running a chi-square test I'd say that your numbers fall well into the expected range of variation.