Mixer is a mixture model approach to analyze ChIP-chip or ChIP-seq data, also with some utility functions to process DNA sequence data. It includes statistical methods for both data normalization and peak detection. The peak detection and quantification relies on a mixer model approach that dissects the distribution of background signals and the Immunoprecipitated signals. In contrast to many existing methods, mixer is more flexible by imposing less restrictive assumptions and allowing a relatively large proportion of peak regions. Robust performance on data sets predicted to contain numerous peaks is very important for the studies of the transcription factors with abundant binding sites, and common chromatin features or epigenetic marks.
CMARRT (Correlation, Moving Average, Robust and Rapid method on Tiling array) is an R package for the analysis of tiling array data that incorporates the correlation structures among probe measurements.
MeDiChI is method for the automated, model-based deconvolution of protein-DNA binding (Chromatin immunoprecipitation followed by hybridization to a genomic tiling microarray — ChIP-chip) data that discovers DNA binding sites at high resolution (higher resolution than that of the tiling array itself).
Ringo is an R package that facilitates the analysis of ChIP-chip experiments by providing functionality for data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions.
JAMIE (Joint Analysis of Multiple IP Experiments) is a R package 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.
CisGenome is a software system for analyzing genome-wide chromatin immunoprecipitation (ChIP) data. CisGenome is designed to meet all basic needs of ChIP data analyses, including visualization, data normalization, peak detection, false discovery rate computation, gene-peak association, and sequence and motif analysis. In addition to implementing previously published ChIP–microarray (ChIP-chip) analysis methods, the software contains statistical methods designed specifically for ChlP sequencing (ChIP-seq) data obtained by coupling ChIP with massively parallel sequencing. The modular design of CisGenome enables it to support interactive analyses through a graphic user interface as well as customized batch-mode computation for advanced data mining. A built-in browser allows visualization of array images, signals, gene structure, conservation, and DNA sequence and motif information.
ChIPpeakAnno is a Bioconductor package within the statistical programming environment R to facilitate batch annotation of enriched peaks identified from ChIP-seq, ChIP-chip, cap analysis of gene expression (CAGE) or any experiments resulting in a large number of enriched genomic regions.