1. HMCan Algorithm:
Histone Modification in Cancer (HMCan) is Hidden Markov Model (HMM) 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 has two main stages: data profiling stage, and peak calling stage. In data profiling stage, HMCan constructs the density profile from the aligned reads, and then normalizes it. Normalization includes: Library size normalization, copy number normalization, GC bais normalization and noise level correction.
For peak calling, HMCan estimates initial HMMs parameters using right side exact Poisson's test. Then, it applies iterative HMMs to fine tune parameters and perform final peak calling.