JAMIE: joint analysis of multiple ChIP-chip experiments

[biointelligence]

biointelligence                  27th July 2010

 

JAMIE: joint analysis of multiple ChIP-chip experiments

 

 

 Chromatin immunoprecipitation followed by genome tiling array hybridization (ChIP-chip) is a powerful approach to identify transcription factor binding sites (TFBSs) in target genomes. When multiple related ChIP-chip datasets are available, analyzing them jointly allows one to borrow information across datasets to improve peak detection. This is particularly useful for analyzing noisy datasets.

Results: We propose a hierarchical mixture model and develop an R package JAMIE to perform the joint analysis. The genome is assumed to consist of background and potential binding regions (PBRs). PBRs have context-dependent probabilities to become bona fide binding sites in individual datasets. This model captures the correlation among datasets, which provides basis for sharing information across experiments. Real data tests illustrate the advantage of JAMIE over a strategy that analyzes individual datasets separately.

Availability: JAMIE is freely available from http://www.biostat.jhsph.edu/hji/jamie

 

Regards,

Team Biointelligence

Biointelligence

Getting started with biosciences

Website: www.biointelligence.in

Email: in...@biointelligence.in
Tel: +91-731-420-2793