MsPAC: A tool for haplotype-phased structural variant detection

Oscar L. Rodriguez; Anna Ritz; Andrew J. Sharp; Ali Bashir

doi:10.1093/bioinformatics/btz618

MsPAC: A tool for haplotype-phased structural variant detection

Oscar L. Rodriguez, Anna Ritz, Andrew J. Sharp, Ali Bashir

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Summary: While next-generation sequencing (NGS) has dramatically increased the availability of genomic data, phased genome assembly and structural variant (SV) analyses are limited by NGS read lengths. Long-read sequencing from Pacific Biosciences and NGS barcoding from 10x Genomics hold the potential for far more comprehensive views of individual genomes. Here, we present MsPAC, a tool that combines both technologies to partition reads, assemble haplotypes (via existing software) and convert assemblies into high-quality, phased SV predictions. MsPAC represents a framework for haplotype-resolved SV calls that moves one step closer to fully resolved, diploid genomes.

Original language	English
Pages (from-to)	922-924
Number of pages	3
Journal	Bioinformatics
Volume	36
Issue number	3
DOIs	https://doi.org/10.1093/bioinformatics/btz618
State	Published - 1 Feb 2020

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title = "MsPAC: A tool for haplotype-phased structural variant detection",

abstract = "Summary: While next-generation sequencing (NGS) has dramatically increased the availability of genomic data, phased genome assembly and structural variant (SV) analyses are limited by NGS read lengths. Long-read sequencing from Pacific Biosciences and NGS barcoding from 10x Genomics hold the potential for far more comprehensive views of individual genomes. Here, we present MsPAC, a tool that combines both technologies to partition reads, assemble haplotypes (via existing software) and convert assemblies into high-quality, phased SV predictions. MsPAC represents a framework for haplotype-resolved SV calls that moves one step closer to fully resolved, diploid genomes.",

author = "Rodriguez, {Oscar L.} and Anna Ritz and Sharp, {Andrew J.} and Ali Bashir",

note = "Funding Information: This work was supported in part by the NIH [R21AI117407 to A.B., NS105781 to A.S. and 1F31NS108797 to O.L.R.]. This work was supported in part through the computational resources and staff expertise provided by the Scientific Computing at the Icahn School of Medicine at Mount Sinai. Publisher Copyright: {\textcopyright} 2019 The Author(s) 2019. Published by Oxford University Press. All rights reserved.",

year = "2020",

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doi = "10.1093/bioinformatics/btz618",

language = "English",

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AU - Ritz, Anna

AU - Sharp, Andrew J.

AU - Bashir, Ali

N1 - Funding Information: This work was supported in part by the NIH [R21AI117407 to A.B., NS105781 to A.S. and 1F31NS108797 to O.L.R.]. This work was supported in part through the computational resources and staff expertise provided by the Scientific Computing at the Icahn School of Medicine at Mount Sinai. Publisher Copyright: © 2019 The Author(s) 2019. Published by Oxford University Press. All rights reserved.

PY - 2020/2/1

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N2 - Summary: While next-generation sequencing (NGS) has dramatically increased the availability of genomic data, phased genome assembly and structural variant (SV) analyses are limited by NGS read lengths. Long-read sequencing from Pacific Biosciences and NGS barcoding from 10x Genomics hold the potential for far more comprehensive views of individual genomes. Here, we present MsPAC, a tool that combines both technologies to partition reads, assemble haplotypes (via existing software) and convert assemblies into high-quality, phased SV predictions. MsPAC represents a framework for haplotype-resolved SV calls that moves one step closer to fully resolved, diploid genomes.

AB - Summary: While next-generation sequencing (NGS) has dramatically increased the availability of genomic data, phased genome assembly and structural variant (SV) analyses are limited by NGS read lengths. Long-read sequencing from Pacific Biosciences and NGS barcoding from 10x Genomics hold the potential for far more comprehensive views of individual genomes. Here, we present MsPAC, a tool that combines both technologies to partition reads, assemble haplotypes (via existing software) and convert assemblies into high-quality, phased SV predictions. MsPAC represents a framework for haplotype-resolved SV calls that moves one step closer to fully resolved, diploid genomes.

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MsPAC: A tool for haplotype-phased structural variant detection

Abstract

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