Journal Article

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

Kai Ye, Marcel H. Schulz, Quan Long, Rolf Apweiler and Zemin Ning

in Bioinformatics

Volume 25, issue 21, pages 2865-2871
Published in print November 2009 | ISSN: 1367-4803
Published online June 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp394

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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.

Availability: The binary code and a short user manual can be freely downloaded from http://www.ebi.ac.uk/∼kye/pindel/.

Contact: k.ye@lumc.nl; zn1@sanger.ac.uk

Journal Article.  4625 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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