HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data

Abstract

As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art; moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.

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

“…We follow the intuition that DASE in the transcriptome can be exploited to improve phasing power because SNP alleles within maternal and paternal haplotypes of a gene are present in the read data at (different) frequencies corresponding to the differential haplotypic expression (DHE). To solve this haplotype reconstruction problem, we introduce a new maximum-likelihood formulation which takes into account DASE (generalizing that from HapTree [2]) and is thus able to newly exploit reads covering only one SNP. This formulation results in a novel integrative algorithm, HapTree-X, which determines a haplotype of maximal likelihood based on both RNA-seq and DNA-seq read data.…”

Hap10: reconstructing accurate and long polyploid haplotypes using linked reads

“…Since for real data there is no ground truth for assessing the performance of the estimated haplotype, the mentioned metrics cannot be used. To handle this issue, another metric, the Minimum Error Correction (MEC) score, has been frequently used in the literature [5][6]: (12) in which % is the i-th pre-processed read (Section 2.1). For haplotypes with a length of , the extended Hamming distance function is defined as Ž" € % , ℎ f…”

“…Therefore, different approximative and heuristic approaches have been used to estimate haplotypes. HapTree [5] is a greedy likelihood-based algorithm in which SNPs are added incrementally while keeping the tree of possible solutions to a manageable size. SDhaP [6] solves a correlation clustering problem using a gradient method to estimate the haplotypes.…”

A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction

“…Among the aforementioned methods, only HapCompass (Aguiar 2012), SD-haP (Das 2015) and BP (Puljiz 2016) are capable of solving the haplotype assembly problem for k > 2. Other techniques that can handle reconstruction of haplotypes for both diploid and polyploid genomes include a Bayesian method HapTree (Berger 2014), a dynamic programming method H-PoP (Xie 2016) shown to be more accurate than the techniques in (Aguiar 2012;Berger 2014;Das 2015), and the matrix factorization schemes in (Cai 2016;Hashemi 2018).…”