PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) is a tool for predicting functional abundances based only on marker gene sequences.
Read more about the tool: https://github.com/picrust/picrust2/wiki
Reads in a sequence abundance table (the abundances of OTUs or ASVs in BIOM, TSV, or mothur shared file format), the predicted marker gene abundances, and the predicted gene family abundances (these last two files are output by hsp.py).
Per-sample metagenome functional profiles are generated based on the predicted functions for each study sequence. Note that typically these sequences correspond to OTUs or ASVs. The specified sequence abundance table will be normalized by the predicted number of marker gene copies before outputting the final files by default. The sample metagenome table stratified by contributing ASVs can optionally also be output.
The sequence abundances should be in read counts and not relative abundances. It will normalize the input sequence abundance table by the predicted number of marker genes. It will then determine the predicted functional profiles per sample. Output stratified by sequence ids (i.e. taxonomic contributors) will also be output if the --strat_out option is used. Also, rare ASVs can be collapsed into the same category in the stratified output table based on the --min_reads and --min_samples options. Note the output files are tab-delimited even if the input files was in BIOM format. The normalized sequence abundance table and the weighted nearest-sequenced taxon index values per-sample will also be output to the output directory as separate files.
Table of sequence abundances (BIOM, TSV, or mothur shared file format).