Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads

被引：1492

作者：

Ye, Kai ^{[1
,2
,3
,4
]}

Schulz, Marcel H. ^{[1
,5
,6
]}

Long, Quan ^{[7
]}

Apweiler, Rolf ^{[1
]}

Ning, Zemin ^{[7
]}

机构：

[1] EMBL Outstat European Bioinformat Inst, Cambridge, England

[2] Leiden Univ, Med Ctr, Dept Mol Epidemiol, Leiden, Netherlands

[3] Leiden Univ, Dept Med Stat, Med Ctr, NL-2300 RA Leiden, Netherlands

[4] Leiden Univ, Dept Bioinformat, Med Ctr, NL-2300 RA Leiden, Netherlands

[5] Max Planck Inst Mol Genet, Berlin, Germany

[6] Int Max Planck Res Sch Computat Biol & Sci Comp, Berlin, Germany

[7] Wellcome Trust Sanger Inst, Cambridge, England

来源：

BIOINFORMATICS | 2009年 / 25卷 / 21期

关键词：

D O I：

10.1093/bioinformatics/btp394

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: There is a strong demand in the genomic community to develop effective algorithms to reliably identify genomic variants. Indel detection using next-gen data is difficult and identification of long structural variations is extremely challenging. Results: We present Pindel, a pattern growth approach, to detect breakpoints of large deletions and medium-sized insertions from paired-end short reads. We use both simulated reads and real data to demonstrate the efficiency of the computer program and accuracy of the results.

引用

页码：2865 / 2871

页数：7

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