[Bioc-sig-seq] peak calling/detection algorithm available in Bioconductor?

[Droit Arnaud]

Hello,
We have have developed a new method for the probabilistic inference of ChIP-Seq data (PICS) that is based on a Bayesian hierarchical truncated t-mixture model. PICS integrates four important components of ChIP-Seq. First, it jointly models local concentrations of directional reads. Second, it uses mixture models to distinguish closely-spaced adjacent binding events. Third, it incorporates prior information for the length distribution of immunoprecipitated DNA to help resolve closely adjacent binding events, and identifies enriched regions. Fourth, it uses pre-calculated whole-genome read ‘mappability’profiles to adjust local read densities for reads that are missing due to genome repetitiveness.
The software will be submmited this week to BioConductor and we hope available soon.
 Best Regards,
Arnaud.

Arnaud Droit, Ph.D
Computational Biology Unit
Institut de Recherches Cliniques de Montréal,IRCM
url: http://www.rglab.org<http://www.rglab.org/>
email: arnaud.droit at ircm.qc.ca<x-msg://23/arnaud.droit@ircm.qc.ca>

Le 2010-03-01 à 03:40, Johannes Rainer a écrit :

dear all,

I'm just wondering if anybody has already implemented a ChIP-seq peak
detection algorithm (like MACS, PeakSeq...) or plans to do so.

bests, jo

--
Johannes Rainer, PhD
Bioinformatics Group,
Division Molecular Pathophysiology,
Biocenter, Medical University Innsbruck,
Fritz-Pregl-Str 3/IV, 6020 Innsbruck, Austria
and
Tyrolean Cancer Research Institute
Innrain 66, 6020 Innsbruck, Austria

Tel.:     +43 512 570485 13
Email:  johannes.rainer at i-med.ac.at<mailto:johannes.rainer at i-med.ac.at>
          johannes.rainer at tcri.at<mailto:johannes.rainer at tcri.at>
URL:   http://bioinfo.i-med.ac.at

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