[Bioc-devel] new version with extensive updates: mosaics

[Dongjun Chung]

Hi all,

We would like to announce a new version of our package, mosaics 
(MOdel-based one and two Sample Analysis and Inference for ChIP-Seq), 
with extensive updates.

R package mosaics implements MOSAiCS, a statistical framework for the 
analysis of ChIP-seq data, proposed in Kuan et al. (2011), JASA, 106: 
891-903. MOSAiCS stands for "MOdel-based one and two Sample Analysis and 
Inference for ChIP-Seq Data". It implements a flexible parametric 
mixture modeling approach for detecting peaks, i.e., enriched regions, 
in one-sample (ChIP sample) or two-sample (ChIP and control samples) 
ChIP-seq data. It accounts for mappability and GC content biases that 
arise in ChIP-seq data.

This new version of the mosaics package (ver 1.2.5) provides many new 
features and improvements, including:

- New model for deeply sequenced ChIP-Seq data.
- Supports for various aligned read file formats (eland_result, 
eland_extended, eland_export, bowtie, SAM, BED, CSEM).
- Preprocessing of aligned read files can be done within the R 
environment using constructBins().
- Easier model fitting for the two sample analysis using mosaicsRunAll().
- Preprocessing and model fitting become much faster (Rcpp).
- Parallel processing is now supported (multicore).

Please check the vignette of the package and 'package?mosaics' for 
further details. The package is available at 
http://bioconductor.org/packages/2.9/bioc/html/mosaics.html.

Please post any questions or comments at our mosaics google group 
(http://groups.google.com/group/mosaics_user_group). Any comments or 
suggestions would be very helpful.

Best,
Dongjun

PhD Candidate
Department of Statistics
Univerisity of Wisconsin at Madison