footprint-tools 1.1.3

Genomic footprint detection

footprint-tools: de novo genomic footprint detection

footprint-tools is a python module for de novo detection of genomic footprints from DNase I data.

Footprint-tools detects footprints 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:

• cython (>=0.22)
• numpy (>=1.10)
• scipy (>=0.16)
• statsmodels
• pysam
• genome_tools (1.0.1) (http://www.github.com/jvierstra/genome_tools)
• pyfaidx (https://github.com/mdshw5/pyfaidx)
• pwlf (https://github.com/cjekel/piecewise_linear_fit_py)

We also recommend these non-python analysis tools:

• samtools
• BEDOPS
• kentUtils

Installation

To install the latest release, type:

pip install footprint-tools

Documentation & usage

User manual, API and examples can be found here

Citation

Vierstra2020 Global reference mapping and dynamics of human transcription factor footprints. Vierstra J et al. (2020) bioRxiv.