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

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

doi:10.1093/bioinformatics/btp394

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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.

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Schulz, Marcel H.
Max Planck Society;

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Citation

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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-7D68-D

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.