Differential peak calling software tools | ChIP sequencing data analysis
Increasing number of ChIP-seq experiments are investigating transcription factor binding under multiple experimental conditions, for example, various treatment conditions, several distinct time points and different treatment dosage levels. Hence, identifying differential binding sites across multiple conditions is of practical importance in biological and medical research.
Allows processing ChIP-seq data enriched for genomic loci where specific protein/DNA binding occurs. DiffBind is applicable to peak sets identified by ChIP-seq peak callers and aligned sequence read datasets. It is able to find sites that are differentially bound between two sample groups. This tool is useful to manage the results of multiple peak callers. It can serve to merge peak sets and count sequencing reads overlapping intervals in peak sets.
Permits users to compare ChIP-Seq data sets. MAnorm is an application designed for quantitative comparison of ChIP-Seq data sets that have a substantial number of peak regions in common. This method is useful for both epigenetic modifications and transcription factors. This application can serve for obtaining cell type-specific and cell state-specific regulation during organism development and disease onset.
Enables comparative analysis of nucleosome physical organization at single-nucleotide resolution. DANPOS is a bioinformatics pipeline allowing dynamic analysis of nucleosome position and occupancy. The software is useful for detecting functionally relevant dynamic nucleosomes, not only in promoters in yeast, but also in distal regulatory regions with more fuzzy nucleosomes, in complex genomes such as those of mammalian.
Detects differential sites from two comparison groups of ChIP-seq samples. diffReps allows annotation of the differential sites and the finding of chromatin modification “hotspots”. The software is independent of any peak calling program and provides several statistical tests to take advantage of the biological replicates. It was used to study the differential sites of H3K4me3 between human embryonic stem cells(hESC) and leukemia cells (K562) from ENCODE, and applied to ChIP-seq data of chronic cocaine-regulated H3K9me3 in mouse nucleus accumbens (NAc).
Analyzes ChIP6Seq data and identifies genomic domains marked by diffusive histone modification markers. RSEG doesn’t need control sample to run and can be used to find regions with differential histone modifications patterns with either comparison between two cell types or between two kinds of histone modifications. It can also detect high-quality domain boundaries.
An algorithm for the computational inference of combinatorial chromatin state dynamics across an arbitrary number of conditions. ChromstaR uses a multivariate Hidden Markov Model to determine the number of discrete combinatorial chromatin states using multiple ChIP-seq experiments as input and assigns every genomic region to a state based on the presence/absence of each modification in every condition. chromstaR is a versatile computational tool that facilitates a deeper biological understanding of chromatin organization and dynamics.
Allows the detection of differences between sequence count data sets. MMDiff is a multivariate nonparametric approach for testing significant differences in profile patterns between peaks in different conditions. The software can identify localized changes which alter the shape of a peak. It methodologically belongs to the family of Kernel based method. MMDiff can be useful for bioinformaticians and biologists interested in epigenomic data analysis.