WIPE

Web of life Integrated Processing Ecosystem (WIPE) is a lightweight CLI toolkit for processing large genome collections (e.g., WoL-style genome indices). It provides batch utilities for genome QC, annotation, summary compilation, and reference/functional database helpers.

Designed for HPC-style workflows where per-genome outputs are written to organized directories and later “compiled” into summary tables.

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Installation

Option A: Install from source (editable)

git clone https://github.com/sherlyn99/wipe.git
cd wipe
pip install -e .

Option B: Conda environment (recommended on clusters)

Create from wipe.yml (recommended)

git clone https://github.com/sherlyn99/wipe.git
cd wipe
conda env create -f wipe.yml
conda activate wipe
pip install -e .

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Quickstart

Check that the CLI is available:

wipe --help

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Command overview

WIPE is a click CLI with top-level commands plus two subgroups: gsearch and uniref.

Top-level commands

wipe metadata

Process/merge metadata tables (behavior depends on which optional file paths are provided).

wipe metadata -m metadata.tsv -o OUTDIR

wipe qc

Run CheckM2 QC over genomes described by a metadata TSV.

wipe qc \
  -m metadata.tsv \
  -o OUTDIR \
  -db /path/to/CheckM2_database \
  -t 16

wipe compile

Compile per-genome outputs into summary tables.

wipe compile \
  -i RESULTS_DIR \
  -o OUTDIR \
  --checkm2 --linearization --kofamscan --barrnap --proteins \
  -c

wipe linearize

Batch genome linearization / standardization utilities.

wipe linearize -o OUTDIR

Optional examples:

wipe linearize -o OUTDIR --metadata metadata.tsv
wipe linearize -o OUTDIR --gap "N*20" # stitch contigs together with 20 'N's
wipe linearize -o OUTDIR --filt "plasmid,phage" # filter out plasmids and phages

wipe annotate

Batch 16S and phylogenetic marker gene annotation using KO profiles + KO list (and other configured resources).

wipe annotate \
  --metadata metadata.tsv \
  -o OUTDIR \
  --rrna-cutoff 0.67 \
  --ko-profiles ko_profiles.tsv \
  --ko-list ko_list.tsv \
  --tmp-dir /scratch/tmp \
  --nthreads 16

wipe annotate-ko

Per-genome KO annotation (only) helper driven by metadata.tsv.

wipe annotate-ko \
  --metadata metadata.tsv \
  -o OUTDIR \
  --ko-profiles ko_profiles.tsv \
  --ko-list ko_list.tsv \
  --tmp-dir /scratch/tmp \
  --nthreads 16

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gsearch subgroup

Gsearch is an ultra-fast and scalable genome search / classification tool for finding the closest matches of query genomes against very large reference collections (hundreds of thousands of genomes).

wipe gsearch create

Create a genome-search database.

wipe gsearch create -i GENOMES_DIR -o DB_OUTDIR -t 8

wipe gsearch update

Update an existing genome-search database.

wipe gsearch update \
  -i NEW_GENOMES_DIR \
  -db EXISTING_DB_DIR \
  -o DB_OUTDIR \
  -t 8 \
  -b BACKUP_DIR

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uniref subgroup

This subgropu of commands allow users to generate uniref annotations of genomes, which can then be used to generate genome-function stratified tables using Woltka.

wipe uniref download

Download UniRef from UniProt.

wipe uniref download --level 90 -o uniref90_download/

wipe uniref build

Build a DIAMOND database from UniRef FASTA.

wipe uniref build -i uniref90.fasta.gz -o db/uniref90.dmnd -t 16

wipe uniref process

Process UniRef XML → TSV.

wipe uniref process -i uniref90.xml.gz -o uniref90.tsv

wipe uniref blastp

Run DIAMOND blastp against the UniRef DB.

wipe uniref blastp -i PROTEIN_DIR -db db/uniref90.dmnd -o OUTDIR -t 16

wipe uniref merge-maps

Merge UniRef90 and UniRef50 mapping files.

wipe uniref merge-maps \
  --uniref90-map uniref90.map.tsv \
  --uniref50-map uniref50.map.tsv \
  -o merged.map.tsv \
  --simplify

wipe uniref extract-names

Extract UniRef names for IDs in a mapping file.

wipe uniref extract-names \
  --map-file merged.map.tsv \
  --uniref90-names uniref90_names.tsv \
  --uniref50-names uniref50_names.tsv \
  -o merged.names.tsv

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Input conventions

Many commands assume a metadata TSV with at least:

• genome_id
• lgenome_path (path to genome FASTA, often .fna.gz)

Additional required columns depend on the workflow stage and enabled modules.

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Output layout

Most commands write:

• per-genome outputs under OUTDIR/<genome_id>/...
• compiled summary tables in OUTDIR/
• logs and “failed genome IDs” lists when applicable