Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
European Bioinformatics Institute · Wellcome Sanger Institute · +1 more institution
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.
Citation impact
- FWCI
- 25.43
- Percentile
- 100%
- References
- 15
Authors
5- KYKai YeCorresponding
European Bioinformatics Institute, Wellcome Sanger Institute, Max Planck Institute for Molecular Genetics
- MHMarcel H. Schulz
European Bioinformatics Institute, Wellcome Sanger Institute, Max Planck Institute for Molecular Genetics
- QLQuan Long
European Bioinformatics Institute, Wellcome Sanger Institute, Max Planck Institute for Molecular Genetics
- RARolf Apweiler
European Bioinformatics Institute, Wellcome Sanger Institute, Max Planck Institute for Molecular Genetics
- ZNZemin Ning
European Bioinformatics Institute, Wellcome Sanger Institute, Max Planck Institute for Molecular Genetics
Topics & keywords
- Indel
- Computer science
- Sanger sequencing
- Breakpoint
- Identification (biology)
- Computational biology
- Data mining
- Biology