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README.md

footprint-tools: de novo genomic footprint detection

footprint-tools is a python module for de novo detection of genomic footprints from DNase I data by simulating expected cleavage rates using a 6-mer DNase I cleavage preference model combined with density smoothing. Statistical significance of per-nucleotide cleavages are computed from a series emperically fit negative binomial distribution.

Requirements

footprint-tools requires Python (>=3.5) and depends on the following additional packages:

We also recommend these non-python analysis tools:

Installation

To install the latest release, type:

pip install footprint-tools

Documentation & usage

User manual, API and examples can be found here

Citation

Vierstra2020 Vierstra, J., Lazar, J., Sandstrom, R. et al. Global reference mapping of human transcription factor footprints. Nature 583, 729–736 (2020)

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