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fp-tools — regulatory footprinting

PyPI CI License: MIT

Documentation · Output demo with ENCODE cancer cell lines · GUI demo · PyPI

fp-tools is a command-first toolkit for footprinting Tn5-based chromatin profiling data, including ATAC-seq, CUT&Tag, and related assays. It provides bias correction, motif analysis, replicate-aware comparisons, and single-cell footprint signatures. The GUI and YAML runner call the same commands.

Install

Choose one route:

Route Best for Start
Desktop executable GUI without Python Download for Windows, macOS, or Linux
Complete container GUI plus raw-read and motif-discovery programs docker run --rm -p 8891:8891 ghcr.io/oncologylab/fp-tools:latest
Python package Direct commands in an existing Python environment python -m pip install fp-tools-bio

Python package example:

python -m pip install --pre fp-tools-bio
fp-tools-gui

Python 3.11–3.13 is supported on Windows, macOS, and Linux. The container is the complete environment for raw FASTQ processing and external MEME tools.

Bulk ATAC-seq

bulk-footprinting runs the complete analysis from aligned BAM and peak files. FASTQ preparation remains available separately through prepare-atac.

bulk-footprinting \
  --sample-table samples.tsv \
  --comparison-table comparisons.tsv \
  --genome hg38.fa.gz \
  --blacklist hg38.blacklist.bed \
  --outdir project \
  --cores 8

The wrapper runs atac-correct, call-footprints, match-motifs, diff-footprints, and review-multi-comparisons. Each command can also be run directly. diff-footprints --comparison-axis regions compares matched genomic region sets within one sample or across biological replicates.

Single-cell ATAC-seq

sc-footprinting groups fragments, runs pseudobulk footprinting, and produces per-cell KNN footprint-signature heatmaps and UMAPs.

sc-footprinting \
  --fragments fragments.tsv.gz \
  --annotations cell_annotations.tsv \
  --h5ad embedding.h5ad \
  --group-by cell_type \
  --genome-sizes hg38.chrom.sizes \
  --genome hg38.fa.gz \
  --peaks merged_peaks.bed \
  --outdir project/single_cell

Main commands

Area Commands
Core analysis prepare-atac, atac-correct, call-footprints, match-motifs, diff-footprints, normalize-bigwig
Workflows bulk-footprinting, sc-footprinting, run-yaml-workflow, fp-tools-gui
Reports plot-aggregate, review-multi-comparisons
De novo motifs discover-motifs, summarize-motifs
Single-cell utilities pseudobulk-fragments, find-signature-fp

Use <command> --help for complete options. Practical examples and the API reference are available in the documentation.

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