Literature DB >> 24072733

MATE-CLEVER: Mendelian-inheritance-aware discovery and genotyping of midsize and long indels.

Tobias Marschall1, Iman Hajirasouliha, Alexander Schönhuth.   

Abstract

MOTIVATION: Accurately predicting and genotyping indels longer than 30 bp has remained a central challenge in next-generation sequencing (NGS) studies. While indels of up to 30 bp are reliably processed by standard read aligners and the Genome Analysis Toolkit (GATK), longer indels have still resisted proper treatment. Also, discovering and genotyping longer indels has become particularly relevant owing to the increasing attention in globally concerted projects.
RESULTS: We present MATE-CLEVER (Mendelian-inheritance-AtTEntive CLique-Enumerating Variant findER) as an approach that accurately discovers and genotypes indels longer than 30 bp from contemporary NGS reads with a special focus on family data. For enhanced quality of indel calls in family trios or quartets, MATE-CLEVER integrates statistics that reflect the laws of Mendelian inheritance. MATE-CLEVER's performance rates for indels longer than 30 bp are on a par with those of the GATK for indels shorter than 30 bp, achieving up to 90% precision overall, with >80% of calls correctly typed. In predicting de novo indels longer than 30 bp in family contexts, MATE-CLEVER even raises the standards of the GATK. MATE-CLEVER achieves precision and recall of ∼63% on indels of 30 bp and longer versus 55% in both categories for the GATK on indels of 10-29 bp. A special version of MATE-CLEVER has contributed to indel discovery, in particular for indels of 30-100 bp, the 'NGS twilight zone of indels', in the Genome of the Netherlands Project.
AVAILABILITY AND IMPLEMENTATION: http://clever-sv.googlecode.com/

Mesh:

Year:  2013        PMID: 24072733      PMCID: PMC3842759          DOI: 10.1093/bioinformatics/btt556

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  31 in total

1.  Detecting genomic indel variants with exact breakpoints in single- and paired-end sequencing data using SplazerS.

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Journal:  Bioinformatics       Date:  2012-01-11       Impact factor: 6.937

2.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Authors:  Aaron McKenna; Matthew Hanna; Eric Banks; Andrey Sivachenko; Kristian Cibulskis; Andrew Kernytsky; Kiran Garimella; David Altshuler; Stacey Gabriel; Mark Daly; Mark A DePristo
Journal:  Genome Res       Date:  2010-07-19       Impact factor: 9.043

3.  High-quality draft assemblies of mammalian genomes from massively parallel sequence data.

Authors:  Sante Gnerre; Iain Maccallum; Dariusz Przybylski; Filipe J Ribeiro; Joshua N Burton; Bruce J Walker; Ted Sharpe; Giles Hall; Terrance P Shea; Sean Sykes; Aaron M Berlin; Daniel Aird; Maura Costello; Riza Daza; Louise Williams; Robert Nicol; Andreas Gnirke; Chad Nusbaum; Eric S Lander; David B Jaffe
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-27       Impact factor: 11.205

4.  PRISM: pair-read informed split-read mapping for base-pair level detection of insertion, deletion and structural variants.

Authors:  Yue Jiang; Yadong Wang; Michael Brudno
Journal:  Bioinformatics       Date:  2012-07-31       Impact factor: 6.937

5.  Fast gapped-read alignment with Bowtie 2.

Authors:  Ben Langmead; Steven L Salzberg
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6.  Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads.

Authors:  Kai Ye; Marcel H Schulz; Quan Long; Rolf Apweiler; Zemin Ning
Journal:  Bioinformatics       Date:  2009-06-26       Impact factor: 6.937

Review 7.  Genome structural variation discovery and genotyping.

Authors:  Can Alkan; Bradley P Coe; Evan E Eichler
Journal:  Nat Rev Genet       Date:  2011-03-01       Impact factor: 53.242

8.  BreakDancer: an algorithm for high-resolution mapping of genomic structural variation.

Authors:  Ken Chen; John W Wallis; Michael D McLellan; David E Larson; Joelle M Kalicki; Craig S Pohl; Sean D McGrath; Michael C Wendl; Qunyuan Zhang; Devin P Locke; Xiaoqi Shi; Robert S Fulton; Timothy J Ley; Richard K Wilson; Li Ding; Elaine R Mardis
Journal:  Nat Methods       Date:  2009-08-09       Impact factor: 28.547

9.  A framework for variation discovery and genotyping using next-generation DNA sequencing data.

Authors:  Mark A DePristo; Eric Banks; Ryan Poplin; Kiran V Garimella; Jared R Maguire; Christopher Hartl; Anthony A Philippakis; Guillermo del Angel; Manuel A Rivas; Matt Hanna; Aaron McKenna; Tim J Fennell; Andrew M Kernytsky; Andrey Y Sivachenko; Kristian Cibulskis; Stacey B Gabriel; David Altshuler; Mark J Daly
Journal:  Nat Genet       Date:  2011-04-10       Impact factor: 38.330

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Journal:  PLoS Biol       Date:  2007-09-04       Impact factor: 8.029

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  18 in total

1.  Whole-genome sequence variation, population structure and demographic history of the Dutch population.

Authors: 
Journal:  Nat Genet       Date:  2014-06-29       Impact factor: 38.330

2.  A genome-wide approach for detecting novel insertion-deletion variants of mid-range size.

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Journal:  Nucleic Acids Res       Date:  2016-06-20       Impact factor: 16.971

Review 3.  Copy number variation and disease resistance in plants.

Authors:  Aria Dolatabadian; Dhwani Apurva Patel; David Edwards; Jacqueline Batley
Journal:  Theor Appl Genet       Date:  2017-10-17       Impact factor: 5.699

4.  Varlociraptor: enhancing sensitivity and controlling false discovery rate in somatic indel discovery.

Authors:  Johannes Köster; Louis J Dijkstra; Tobias Marschall; Alexander Schönhuth
Journal:  Genome Biol       Date:  2020-04-28       Impact factor: 13.583

Review 5.  Structural variation discovery in the cancer genome using next generation sequencing: computational solutions and perspectives.

Authors:  Biao Liu; Jeffrey M Conroy; Carl D Morrison; Adekunle O Odunsi; Maochun Qin; Lei Wei; Donald L Trump; Candace S Johnson; Song Liu; Jianmin Wang
Journal:  Oncotarget       Date:  2015-03-20

6.  SV-AUTOPILOT: optimized, automated construction of structural variation discovery and benchmarking pipelines.

Authors:  Wai Yi Leung; Tobias Marschall; Yogesh Paudel; Laurent Falquet; Hailiang Mei; Alexander Schönhuth; Tiffanie Yael Maoz Moss
Journal:  BMC Genomics       Date:  2015-03-25       Impact factor: 3.969

Review 7.  Detection of Genomic Structural Variants from Next-Generation Sequencing Data.

Authors:  Lorenzo Tattini; Romina D'Aurizio; Alberto Magi
Journal:  Front Bioeng Biotechnol       Date:  2015-06-25

8.  Characteristics of de novo structural changes in the human genome.

Authors:  Wigard P Kloosterman; Laurent C Francioli; Fereydoun Hormozdiari; Tobias Marschall; Jayne Y Hehir-Kwa; Abdel Abdellaoui; Eric-Wubbo Lameijer; Matthijs H Moed; Vyacheslav Koval; Ivo Renkens; Markus J van Roosmalen; Pascal Arp; Lennart C Karssen; Bradley P Coe; Robert E Handsaker; Eka D Suchiman; Edwin Cuppen; Djie Tjwan Thung; Mitch McVey; Michael C Wendl; André Uitterlinden; Cornelia M van Duijn; Morris A Swertz; Cisca Wijmenga; GertJan B van Ommen; P Eline Slagboom; Dorret I Boomsma; Alexander Schönhuth; Evan E Eichler; Paul I W de Bakker; Kai Ye; Victor Guryev
Journal:  Genome Res       Date:  2015-04-16       Impact factor: 9.043

9.  Viral quasispecies assembly via maximal clique enumeration.

Authors:  Armin Töpfer; Tobias Marschall; Rowena A Bull; Fabio Luciani; Alexander Schönhuth; Niko Beerenwinkel
Journal:  PLoS Comput Biol       Date:  2014-03-27       Impact factor: 4.475

10.  GINDEL: accurate genotype calling of insertions and deletions from low coverage population sequence reads.

Authors:  Chong Chu; Jin Zhang; Yufeng Wu
Journal:  PLoS One       Date:  2014-11-25       Impact factor: 3.240

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