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Old 02-05-2015, 10:48 AM   #9
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Location: Research Triangle Park, NC

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Originally Posted by wingtec View Post
With all that said, if I am allowed to twist the question a bit.

Say, I already have some Affy microarray data and I want to better or at least confirm the array data with RNA-Seq. The Affy chip used was HG ST gene array and the experiment was done with n=3. Now we want to do also n=3 in RNA-Seq, will 20M clean read of PE2x100 have similar or better coverage than the array data?


Note that regardless of depth of coverage, you may well not be able to "confirm" some array results with an independent RNA-seq experiment. Just because you detect any given gene as significantly differentially expressed in one experiment does not mean you will do so in the other experiment. Sometimes the overlap in DEGs is great, but sometimes it can be quite low.

You may get better correspondance (better confirmation) in the end by ontology enrichment comparisons of the genes selected from the two experiments than you will with a direct comparison of signficant gene lists. Particularly given that your n=3 for biological replication is a minimally low number of replicates.

Array equivalence is a two part issue to my mind. First is the issue of equivalent sensitivity - how much RNA-seq coverage will give you equivalent statistical sensitivity of detection of change? But how much coverage do you need to pick up either the equivalent number of DEGs or largely the same set of DEGs is a different issue. Typically, coverage for the former is far less than for the latter. 5-10M reads per sample will equal or exceed array sensitivity, but you'd be better to have 30-50M reads per sample if you want a good chance of getting high overlap in detected DEGs in both experiments (in my experience).
Michael Black, Ph.D.
ScitoVation LLC. RTP, N.C.
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