XHMM (eXome-Hidden Markov Model)

The XHMM C++ software suite was written to call copy number variation (CNV) from next-generation sequencing projects, where exome capture was used (or targeted sequencing, more generally).

XHMM uses principal component analysis (PCA) normalization and a hidden Markov model (HMM) to detect and genotype copy number variation (CNV) from normalized read-depth data from targeted sequencing experiments.

XHMM was explicitly designed to be used with targeted exome sequencing at high coverage (at least 60x - 100x) using Illumina HiSeq (or similar) sequencing of at least ~50 samples. However, no part of XHMM explicitly requires these particular experimental conditions, just high coverage of genomic regions for many samples.