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Haystack: systematic analysis of the variation of epigenetic states and cell-type specific regulatory elements.
Bioinformatics 2018 June 2
Motivation: With the increasing amount of genomic and epigenomic data in the public domain, a pressing challenge is to integrate these data to investigate the role of epigenetic mechanisms in regulating gene expression and maintenance of cell-identity. To this end, we have implemented a computational pipeline to systematically study epigenetic variability and uncover regulatory DNA sequences.
Results: Haystack is a bioinformatics pipeline to identify hotspots of epigenetic variability across different cell-types, cell-type specific cis-regulatory elements, and associated transcription factors. Haystack is generally applicable to any epigenetic mark and provides an important tool to investigate the mechanisms underlying epigenetic switches during development. This software is accompanied by a set of precomputed tracks, which may be used as a valuable resource for functional annotation of the human genome.
Availability and implementation: The Haystack pipeline is implemented as an open-source, multiplatform, Python package called haystack_bio freely available at https://github.com/pinellolab/haystack_bio.
Contact: [email protected] or [email protected].
Supplementary information: Supplementary data are available at Bioinformatics online.
Results: Haystack is a bioinformatics pipeline to identify hotspots of epigenetic variability across different cell-types, cell-type specific cis-regulatory elements, and associated transcription factors. Haystack is generally applicable to any epigenetic mark and provides an important tool to investigate the mechanisms underlying epigenetic switches during development. This software is accompanied by a set of precomputed tracks, which may be used as a valuable resource for functional annotation of the human genome.
Availability and implementation: The Haystack pipeline is implemented as an open-source, multiplatform, Python package called haystack_bio freely available at https://github.com/pinellolab/haystack_bio.
Contact: [email protected] or [email protected].
Supplementary information: Supplementary data are available at Bioinformatics online.
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