HapTree-X: An Integrative Bayesian Framework for Haplotype Reconstruction from Transcriptome and Genome Sequencing Data

Identifying phase information is biomedically important due to the association of complex haplotype effects, such as compound heterozygosity, with disease. As recent next-generation sequencing (NGS) technologies provide more read sequences, the use of diverse sequencing datasets for haplotype phasing is now possible, allowing haplotype reconstruction of a single sequenced individual using NGS data. Previous haplotype reconstruction studies have ignored differential allele-specific expression in whole transcriptome sequencing (RNA-seq) data; however, intuition suggests that the asymmetry in this data (i.e. maternal and paternal haplotypes of a gene are differentially expressed) can be exploited to improve phasing power. In this paper, we describe a novel integrative maximum-likelihood estimation framework, HapTree-X, for efficient, scalable haplotype assembly of an individual genome using transcriptomic and genomic NGS read datasets, which makes use of differential allele-specifi...

• Type: Journal
• Year: 2015
• Where: RECOMB
• Authors: Emily Berger, Deniz Yörükoglu, Bonnie Berger
• Keywords: Computational Biology, RECOMB 2015