Hi there community!
For some time I was working os 16S rRNA gene survey data. For this type of analysis one could use a rarefaction approach in order to have the same depth for each sample. Having different depths for each sample is sometimes referred to as searching 1 square meter of amazon jungle and 1 square kilometer of mojave desert and then comparing OTUs, taxons, etc... It is relatively easy to employ a rarefaction, as it is implemented in many software packages: qiime, mothur.
I have now a shotgun dataset - a whole genome sequencing of microbiome. For the start I am using a microbiome helper SOP. For taxonomy assignement I use MetaPhlAn2 approach. MetaPhlAn2 wiki doesn't even mention rarefaction. Since this step might be crucial for comparative analyses, where I have two groups/categories, each containing around 30 samples I want to have each sample as "standardized" as possible. Are there any approaches two rarefy WGS data? Is there a reason why I has not been yet implemented in for example MetaPhlAn2?
I'd be grateful for any insight, comments and suggestions.