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why expression value must be log2 transformed before further analysis, such differential analysis?

Hi, just as the title.

When using microarray, the intensity should be log transformed, that is partly because the intensity values are relative numbers. But in RNA-Seq, why must RPKM be log transformed?

I also notice that the differential analysis results are largely different with/without log transform. why? anyone tell me? thank you.

expression log
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updated by Ram Ram • written by jlshi.nudt jlshi.nudt

Who told you this? Log transformed expression are easier to detect DEG with low expression level. However, I never heard it's a must to log transformed them.

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updated by Ram Ram • written by Xingyu Yang Xingyu Yang

I just saw this transformation on many papers resolved with RPKM and microarray expression data. It seems to be a usual convention.

Btw, I guess that low expression levels are not believable, so I always to filter with some threshold value.

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written by jlshi.nudt jlshi.nudt

2 answers

The general reason to log-transform data (log2 or otherwise) is to make variation similar across orders of magnitude. This isn't really a must, but usually makes things more convenient. Having said that, tools like limma are expecting log2 values, so if you're going to plug your RPKMs into it then it'd be a very good idea to log2 them first.

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written by Devon Ryan Devon Ryan

Indeed microarray values and RPKM/FPKM values are better correlated when log-transformed. The reason for it is that the distribution of RPKM/FPKM values is skewed, and by log-transforming it we could bring it closer to normal distribution. It is needless to say that many statistical tests require normally-distributed data..

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written by mikhail.shugay mikhail.shugay

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