hsegHMM

Somatic copy number alternation (SCNA) is a common feature of the cancer genome and is associated with cancer etiology and prognosis. The allele-specific SCNA analysis of a tumor sample aims to identify the allele-specific copy numbers of both alleles, adjusting for the ploidy and the tumor purity. Next generation sequencing platforms produce abundant read counts at the basepair resolution across the exome or whole genome which is susceptible to hypersegmentation, a phenomenon where numerous regions with very short length are falsely identified as SCNA. This package employs a robust hidden Markov model approach that accounts for hypersegmentation for allele-specific SCNA analysis, and an efficient E-M algorithm procedure that uses a forwardbackward algorithm for evaluating the E-step. The main function that performs this method is hsegHMM_main.

• Manual
• Vignette
• License Agreement

Download Software

• Windows O/S: hsegHMM_0.0.4.zip
• Unix O/S: hsegHMM_0.0.4.tar.gz
• On github: https://github.com/wheelerb/hsegHMM

Reference

Choo-Wosoba, H., Albert, P.S., Zhu, B. hsegHMM: Hidden Markov Model-based Allele-specific Copy Number Alteration Analysis Accounting for Hypersegmentation. BMC Bioinformatics 2018 Nov 14.

Support

Questions, please contact DCEG.