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Probabilistic Inference for ChIP-Seq PICS

A package for identifying regions bound by transcription factors from aligned reads. PICS identifies binding event locations by modeling local concentrations of directional reads, and uses DNA fragment length prior information to discriminate closely adjacent binding events via a Bayesian hierarchical t-mixture model. It uses precalculated, whole-genome read mappability profiles and a truncated t-distribution to adjust binding event models for reads that are missing due to local genome repetitiveness. PICS estimates uncertainties in model parameters that can be used to define confidence regions on binding event locations and to filter estimates. Finally, it calculates a per-event enrichment score relative to a control sample, and can use a control sample to estimate a false discovery rate. Because it is based on mixture models and accounts for missing reads, PICS is computationally intensive.

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PICS forum

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PICS classification

PICS specifications

Software type:
Package/Module
Restrictions to use:
None
Programming languages:
R
Computer skills:
Advanced
Stability:
Stable
Maintained:
Yes
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
Artistic License version 2.0
Version:
2.16.0
Requirements:
BiocGenerics

PICS distribution

versioning

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No versioning.

PICS support

Documentation

Credits

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Publications

Institution(s)

Department of Statistics, University of British Columbia, Vancouver, BC, Canada; BC Cancer Agency Genome Sciences Centre, Vancouver, BC, Canada; Bioinformatics Training Program, University of British Columbia, Vancouver, BC, Canada; Clinical Research Institute of Montreal (IRCM), Montreal, QC, Canada; Université de Montreal, Montreal, QC, Canada

Funding source(s)

An NSERC Discovery Grant

Link to literature

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