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