Introduction

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.

For more information, visit the official XHMM website.

Programming language: C++

Brief description: tool for predicting copy number variation (CNV).

Open source license: GPL v3