HMMcopy is a package for making bias-free copy number estimation by correcting for GC-content and mappability bias in HTS readcounts. It also contains an implementation of the Hidden Markov Model to robustly segment a copy number profile into non-overlapping segments predicted to be of the same copy number state, and attributes a biological copy number aberration events to the segments.
Takes in a copy number profile and segments it into predicted regions of equal copy number, and assigns a biologically motivated copy number state to each region using a Hidden Markov Model (HMM). This is an extension to the HMM described in Shah et al., 2006.
Loads WIG files for readcount, GC, and mappability data for non-overlapping windows of fixed length (i.e. bins), and returns a structure ready to used for readcount correction. See Details for specifics about file assumptions.
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