footprint-tools: digital genomic footprint detection and analysis#

A Python package for de novo detection of genomic footprints from DNase I data.

Features:

  • De novo footprint detection

  • Consensus footprint detection (emperical Bayes)

  • Differential footprinting

  • API for programmatic access to cleavage data directly from sequence alignment files

Warning

Please note that is documentation is a work in progress. Please contact us with any questions.

Contents#

Pre-processed data#

As part of the ENCODE Consortium we have generated digital genomic footprinting data for >240 cell types and tissues. These data and their metadata are hosted at both http://vierstra.org/resources/dgf and ZENDODO.

Citation#

Vierstra2020

Vierstra, J., Lazar, J., Sandstrom, R. et al. Global reference mapping of human transcription factor footprints. Nature 583, 729–736 (2020) https://doi.org/10.1101/2020.01.31.927798