ArticleBMC genomics2018
Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Direct inference of haplotypes from sequencing data.Bioinformatics advances · 2025Article
- Pairwise comparative analysis of six haplotype assembly methods based on users' experience.BMC genomic data · 2023Article
- XHap: haplotype assembly using long-distance read correlations learned by transformers.Bioinformatics advances · 2023Article
- flopp: Extremely Fast Long-Read Polyploid Haplotype Phasing by Uniform Tree Partitioning.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- NCMHap: a novel method for haplotype reconstruction based on Neutrosophic c-means clustering.BMC bioinformatics · 2020Article
- Haplotype threading: accurate polyploid phasing from long reads.Genome biology · 2020Article
- ComHapDet: a spatial community detection algorithm for haplotype assembly.BMC genomics · 2020Article
- A chaotic viewpoint-based approach to solve haplotype assembly using hypergraph model.PloS one · 2020Article
- A graph-based algorithm for estimating clonal haplotypes of tumor sample from sequencing data.BMC medical genomics · 2019Article
- NGS based haplotype assembly using matrix completion.PloS one · 2019Article
- Viral quasispecies reconstruction via tensor factorization with successive read removal.Bioinformatics (Oxford, England) · 2018Article
- Selected research articles from the 2017 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC).BMC bioinformatics · 2018Article
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3 authors.
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Abstract
backgroundHaplotype assembly is the task of reconstructing haplotypes of an individual from a mixture of sequenced chromosome fragments. Haplotype information enables studies of the effects of genetic variations on an organism's phenotype. Most of the mathematical formulations of haplotype assembly are known to be NP-hard and haplotype assembly becomes even more challenging as the sequencing technology advances and the length of the paired-end reads and inserts increases. Assembly of haplotypes polyploid organisms is considerably more difficult than in the case of diploids. Hence, scalable and accurate schemes with provable performance are desired for haplotype assembly of both diploid and polyploid organisms.
resultsWe propose a framework that formulates haplotype assembly from sequencing data as a sparse tensor decomposition. We cast the problem as that of decomposing a tensor having special structural constraints and missing a large fraction of its entries into a product of two factors, U and [Formula: see text]; tensor [Formula: see text] reveals haplotype information while U is a sparse matrix encoding the origin of erroneous sequencing reads. An algorithm, AltHap, which reconstructs haplotypes of either diploid or polyploid organisms by iteratively solving this decomposition problem is proposed. The performance and convergence properties of AltHap are theoretically analyzed and, in doing so, guarantees on the achievable minimum error correction scores and correct phasing rate are established. The developed framework is applicable to diploid, biallelic and polyallelic polyploid species. The code for AltHap is freely available from https://github.com/realabolfazl/AltHap .
conclusionAltHap was tested in a number of different scenarios and was shown to compare favorably to state-of-the-art methods in applications to haplotype assembly of diploids, and significantly outperforms existing techniques when applied to haplotype assembly of polyploids.
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