Literature DB >> 22730434

gSearch: a fast and flexible general search tool for whole-genome sequencing.

Taemin Song1, Kyu-Baek Hwang, Michael Hsing, Kyungjoon Lee, Justin Bohn, Sek Won Kong.   

Abstract

BACKGROUND: Various processes such as annotation and filtering of variants or comparison of variants in different genomes are required in whole-genome or exome analysis pipelines. However, processing different databases and searching among millions of genomic loci is not trivial.
RESULTS: gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner. The proposed method is not a stand-alone annotation tool with its own reference databases. Rather, it is a search utility that readily accepts public or user-prepared reference files in various formats including GVF, Generic Feature Format version 3 (GFF3), Gene Transfer Format (GTF), VCF and Browser Extensible Data (BED) format. Compared to existing tools such as ANNOVAR, gSearch runs more than 10 times faster. For example, it is capable of annotating 52.8 million variants with allele frequencies in 6 min. AVAILABILITY: gSearch is available at http://ml.ssu.ac.kr/gSearch. It can be used as an independent search tool or can easily be integrated to existing pipelines through various programming environments such as Perl, Ruby and Python.

Mesh:

Year:  2012        PMID: 22730434      PMCID: PMC3413394          DOI: 10.1093/bioinformatics/bts358

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


  8 in total

1.  VarSifter: visualizing and analyzing exome-scale sequence variation data on a desktop computer.

Authors:  Jamie K Teer; Eric D Green; James C Mullikin; Leslie G Biesecker
Journal:  Bioinformatics       Date:  2011-12-30       Impact factor: 6.937

2.  Integrated annotation and analysis of genetic variants from next-generation sequencing studies with variant tools.

Authors:  F Anthony San Lucas; Gao Wang; Paul Scheet; Bo Peng
Journal:  Bioinformatics       Date:  2011-12-02       Impact factor: 6.937

3.  Kaviar: an accessible system for testing SNV novelty.

Authors:  Gustavo Glusman; Juan Caballero; Denise E Mauldin; Leroy Hood; Jared C Roach
Journal:  Bioinformatics       Date:  2011-09-28       Impact factor: 6.937

4.  Next-generation DNA sequencing.

Authors:  Jay Shendure; Hanlee Ji
Journal:  Nat Biotechnol       Date:  2008-10       Impact factor: 54.908

5.  A probabilistic disease-gene finder for personal genomes.

Authors:  Mark Yandell; Chad Huff; Hao Hu; Marc Singleton; Barry Moore; Jinchuan Xing; Lynn B Jorde; Martin G Reese
Journal:  Genome Res       Date:  2011-06-23       Impact factor: 9.043

6.  A standard variation file format for human genome sequences.

Authors:  Martin G Reese; Barry Moore; Colin Batchelor; Fidel Salas; Fiona Cunningham; Gabor T Marth; Lincoln Stein; Paul Flicek; Mark Yandell; Karen Eilbeck
Journal:  Genome Biol       Date:  2010-08-26       Impact factor: 13.583

7.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data.

Authors:  Kai Wang; Mingyao Li; Hakon Hakonarson
Journal:  Nucleic Acids Res       Date:  2010-07-03       Impact factor: 16.971

Review 8.  Computational and statistical approaches to analyzing variants identified by exome sequencing.

Authors:  Nathan O Stitziel; Adam Kiezun; Shamil Sunyaev
Journal:  Genome Biol       Date:  2011-09-14       Impact factor: 13.583

  8 in total
  4 in total

1.  Prioritizing disease-linked variants, genes, and pathways with an interactive whole-genome analysis pipeline.

Authors:  In-Hee Lee; Kyungjoon Lee; Michael Hsing; Yongjoon Choe; Jin-Ho Park; Shu Hee Kim; Justin M Bohn; Matthew B Neu; Kyu-Baek Hwang; Robert C Green; Isaac S Kohane; Sek Won Kong
Journal:  Hum Mutat       Date:  2014-03-06       Impact factor: 4.878

2.  Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

Authors:  Kyu-Baek Hwang; In-Hee Lee; Jin-Ho Park; Tina Hambuch; Yongjoon Choe; MinHyeok Kim; Kyungjoon Lee; Taemin Song; Matthew B Neu; Neha Gupta; Isaac S Kohane; Robert C Green; Sek Won Kong
Journal:  Hum Mutat       Date:  2014-06-24       Impact factor: 4.878

3.  WhatsGNU: a tool for identifying proteomic novelty.

Authors:  Ahmed M Moustafa; Paul J Planet
Journal:  Genome Biol       Date:  2020-03-05       Impact factor: 13.583

4.  Improving the Sequence Ontology terminology for genomic variant annotation.

Authors:  Fiona Cunningham; Barry Moore; Nicole Ruiz-Schultz; Graham Rs Ritchie; Karen Eilbeck
Journal:  J Biomed Semantics       Date:  2015-07-31
  4 in total

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