Literature DB >> 25686638

RAPTR-SV: a hybrid method for the detection of structural variants.

Derek M Bickhart1, Jana L Hutchison1, Lingyang Xu1, Robert D Schnabel1, Jeremy F Taylor1, James M Reecy1, Steven Schroeder1, Curt P Van Tassell1, Tad S Sonstegard1, George E Liu1.   

Abstract

MOTIVATION: Identification of structural variants (SVs) in sequence data results in a large number of false positive calls using existing software, which overburdens subsequent validation.
RESULTS: Simulations using RAPTR-SV and other, similar algorithms for SV detection revealed that RAPTR-SV had superior sensitivity and precision, as it recovered 66.4% of simulated tandem duplications with a precision of 99.2%. When compared with calls made by Delly and LUMPY on available datasets from the 1000 genomes project, RAPTR-SV showed superior sensitivity for tandem duplications, as it identified 2-fold more duplications than Delly, while making ∼85% fewer duplication predictions.
AVAILABILITY AND IMPLEMENTATION: RAPTR-SV is written in Java and uses new features in the collections framework in the latest release of the Java version 8 language specifications. A compiled version of the software, instructions for usage and test results files are available on the GitHub repository page: https://github.com/njdbickhart/RAPTR-SV. CONTACT: derek.bickhart@ars.usda.gov. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

Mesh:

Year:  2015        PMID: 25686638     DOI: 10.1093/bioinformatics/btv086

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


  7 in total

1.  Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals.

Authors:  Jeremy F Taylor; Lynsey K Whitacre; Jesse L Hoff; Polyana C Tizioto; JaeWoo Kim; Jared E Decker; Robert D Schnabel
Journal:  Genet Sel Evol       Date:  2016-08-17       Impact factor: 4.297

2.  Wham: Identifying Structural Variants of Biological Consequence.

Authors:  Zev N Kronenberg; Edward J Osborne; Kelsey R Cone; Brett J Kennedy; Eric T Domyan; Michael D Shapiro; Nels C Elde; Mark Yandell
Journal:  PLoS Comput Biol       Date:  2015-12-01       Impact factor: 4.475

3.  Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus) and the Scaled Quail (Callipepla squamata) Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size.

Authors:  David L Oldeschulte; Yvette A Halley; Miranda L Wilson; Eric K Bhattarai; Wesley Brashear; Joshua Hill; Richard P Metz; Charles D Johnson; Dale Rollins; Markus J Peterson; Derek M Bickhart; Jared E Decker; John F Sewell; Christopher M Seabury
Journal:  G3 (Bethesda)       Date:  2017-09-07       Impact factor: 3.154

4.  Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing.

Authors:  Shunichi Kosugi; Yukihide Momozawa; Xiaoxi Liu; Chikashi Terao; Michiaki Kubo; Yoichiro Kamatani
Journal:  Genome Biol       Date:  2019-06-03       Impact factor: 13.583

5.  Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software.

Authors:  Daniel L Cameron; Leon Di Stefano; Anthony T Papenfuss
Journal:  Nat Commun       Date:  2019-07-19       Impact factor: 14.919

6.  Genomic population structure and prevalence of copy number variations in South African Nguni cattle.

Authors:  Magretha Diane Wang; Kennedy Dzama; Charles A Hefer; Farai C Muchadeyi
Journal:  BMC Genomics       Date:  2015-11-04       Impact factor: 3.969

7.  Genomic structural differences between cattle and River Buffalo identified through comparative genomic and transcriptomic analysis.

Authors:  Wenli Li; Derek M Bickhart; Luigi Ramunno; Daniela Iamartino; John L Williams; George E Liu
Journal:  Data Brief       Date:  2018-05-10
  7 in total

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