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2 hours ago by

Hi- I have analyzed metagenomic (WGS) data with MetaPhlAn pipeline which gives relative abundance (out of 100) data of each taxon. I have two groups of data: control and test. I want to find out the Mean, Standard Error (SE), sample number (N) of the control, and test group. My data is not normally distributed and for that I want it to be log transformed. For that, I have used the following function and transformed my dataset:

mk_logit <- function(x) log(x)

But, as my dataset is zero-inflated, all of the zeros (0) log-transformed into -Inf. When they were used for further mean, SD calculation, most of them are producing NaN and Inf. As a result, I am not getting proper result.
Can anyone please give me any solution/suggestion in order to get rid of this problem?


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