agent-browser
Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test w…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is needed from 16S data without shotgun metagenomics sequencing.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-microbiome-functional-prediction
Skill Snapshot
Source Doc
library(phyloseq)
library(Biostrings)
ps <- readRDS('phyloseq_object.rds')
## Export ASV sequences as FASTA
seqs <- refseq(ps) # Or extract from ASV names if stored there
writeXStringSet(seqs, 'asv_seqs.fasta')
picrust2_pipeline.py
-s asv_seqs.fasta
-i asv_table.tsv
-o picrust2_output
-p 4
--stratified
--per_sequence_contrib
Related skills
Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test w…
Access 20+ years of global financial data: equities, options, forex, crypto, commodities, economic indicators, and 50+ technical indicators.
Filter alignments by flag, quality, region, or paired status.
Index BAM/CRAM files with samtools index for random access.