histoneHMM is a software to analyse ChIP-seq data of histone modifications with broad genomic footprints like H3K27me3. It allows for calling modified regions in single samples as well as for calling differentially modified regions in a comparison of two samples.
HMCan is Hidden Markov Model based tool that is developed to detect histone modification in cancer ChIP-seq data. It applies three correction steps to the data: copy number correction, GC bias correction and noise level correction.
HMCan-diff is a method designed specially to detect changes of histone modifications in ChIP-seq cancer samples or between a cancer sample and a normal control. HMCan-diff explicitly corrects for copy number bias as well as for other ChIP-seq technical biases such as GC-content and mappability biases, and variable levels of signal-to-noise in different samples. HMCan-diff uses a three state hidden Markov model to detect regions of differential histone modifications.
CoreBoost is a program for predicting the location of transcription start sites for human polymerase II promoters. It is based on two classifiers, one for CpG related promoters and the other for non-CpG related promoters. Both classifiers apply boosting techniques with stumps and select important small scale as well as large scale sequence features such as position specific core promoter elements and the flexibility of promoter sequences. The current version has more than 30% sensitivity and positive predictive value at 50 bp resolution.
CoreBoost_HMis a program for predicting the location of human polymerase II (Pol II) core-promoters. It is developed based on human Pol II core-promoter predictor CoreBoost by integrating specific histone modification profiles and the DNA sequence features together. Same as Coreboost, CoreBoost_HM is based on two classifiers, one for CpG related promoters and the other for non-CpG related promoters. Both classifiers apply boosting techniques with stumps and select important sequence features and histone modification features. Our analysis suggested that integrating histone modification profiles can provide much higher sensitivity, specificity and high resolution for human core-promoter prediction.
