Hi,
Normalized counts from the matrix table are transformed to log2 values by metagenomeseq, aren´t they? My question is about the zeros in the count matrix. How are they transformed to allow statistical analysis? (as log2 of zero gives an error). Thanks!
To extract raw, or normalized counts, the MRcounts function is used. If you just type MRcounts you'll see that we use a continuity-correction pseudocount of 1. This maps 0s --> 0s in log-space.
Activity on a post you are following on support.bioconductor.orgUser PJ wrote C: metagenomeSeq log transformation:
Thanks Joseph for the quick answer. What about the negative tansformed log values? Is the program taking the absolute values for statistics?
Post tags: metagenomeseq, logtransformation
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Yes, you are right. I added a second normalization step based on reference gene length and 16S bacterial reads so I am not using the read counts. Could this affect the statistical output? Where can I see the actual formula to calculate average expression? Thanks again!
This normalization step is not expected input for metagenomeSeq and it was not designed for that. The method was designed for read counts that you can read up on in the supplementary material here: http://www.nature.com/nmeth/journal/v10/n12/full/nmeth.2658.html. Or in the vignette.
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In addition, how is it possible that features with negative log2 values in the transformed count matrix come up with positive average expression values in the statistical output? Thanks!