Source
EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. k.ye@lumc.nl
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/ approximately kye/pindel/.
CONTACT:
k.ye@lumc.nl; zn1@sanger.ac.uk.