scHMM (correlated hidden Markov models) is a package for analyzing sequence read count data in multiple ChIPseq experiments using sparsely correlated hidden Markov models (HMM).
SeqSite was developed for detecting transcription factor binding sites from ChIP-seq data.SeqSite is an efficient and easy-to-use software tool implementing a novel method for identifying and pinpointing transcription factor binding sites. It first detects transcription factor binding regions by clustering tags and statistical hypothesis testing, and locates every binding site in detected binding regions by modeling the tag profiles. It can pinpoint closely spaced adjacent binding sites from ChIP-seq data.
ChIPmeta is a software for the joint analysis of ChIP-seq and ChIP-chip data. Individual channel-level analysis and joint analysis are performed using hidden Markov models.
ChIPDiff provides a solution for the identification of Differential Histone Modification Sites (DHMSs) by comparing two ChIP-seq libraries (L1 and L2). An HMM is employed in ChIPDiff to infer the states of histone modification changes
Qeseq is an algorithm to detect regions of increased ChIP read density relative to background. Qeseq employs critical novel elements, such as iterative recalibration and neighbor joining of reads to identify enriched regions of any length.