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

Ye, K., Schulz, M. H., Long, Q., Apweiler, R., & Ning, Z. (2009). Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics, 25(21), 2865-2871. doi:10.1093/bioinformatics/btp394.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-7D68-D Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-7D69-B
Genre: Journal Article
Alternative Title : Bioinformatics

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 Creators:
Ye, Kai, Author
Schulz, Marcel H.1, Author
Long, Quan, Author
Apweiler, Rolf, Author
Ning, Zemin, Author
Affiliations:
1Max Planck Society, ou_persistent13              

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 Abstract: 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.

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Language(s): eng - English
 Dates: 2009-06-26
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: eDoc: 451276
URI: http://bioinformatics.oxfordjournals.org/cgi/reprint/btp394
DOI: 10.1093/bioinformatics/btp394
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Title: Bioinformatics
  Alternative Title : Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 25 (21) Sequence Number: - Start / End Page: 2865 - 2871 Identifier: ISSN: 1367-4803