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.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.The binary code and a short user manual
can be freely downloaded from http://www.ebi.ac.uk/ approximately
kye/pindel/.k.ye@lumc.nl; zn1@sanger.ac.uk.
%0 Journal Article
%1 Ye2009Pindelpatterngrowth
%A Ye, Kai
%A Schulz, Marcel H
%A Long, Quan
%A Apweiler, Rolf
%A Ning, Zemin
%D 2009
%J Bioinformatics
%K Algorithms; Analysis, Biology, Breakpoints; Breaks; Chromosome Computational DNA DNA; Genome; INDEL Mutation; Sequence Software methods;
%N 21
%P 2865--2871
%R 10.1093/bioinformatics/btp394
%T Pindel: a pattern growth approach to detect break points of large
deletions and medium sized insertions from paired-end short reads.
%U http://dx.doi.org/10.1093/bioinformatics/btp394
%V 25
%X 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.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.The binary code and a short user manual
can be freely downloaded from http://www.ebi.ac.uk/ approximately
kye/pindel/.k.ye@lumc.nl; zn1@sanger.ac.uk.
@article{Ye2009Pindelpatterngrowth,
abstract = {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.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.The binary code and a short user manual
can be freely downloaded from http://www.ebi.ac.uk/ approximately
kye/pindel/.k.ye@lumc.nl; zn1@sanger.ac.uk.},
added-at = {2014-05-13T15:48:44.000+0200},
author = {Ye, Kai and Schulz, Marcel H and Long, Quan and Apweiler, Rolf and Ning, Zemin},
biburl = {https://www.bibsonomy.org/bibtex/2adf246570a7f2f46a6499418e06999cd/gwotto},
doi = {10.1093/bioinformatics/btp394},
file = {:Ye2009Pindelpatterngrowth.pdf:PDF},
institution = {EMBL Outstation European Bioinformatics Institute{\,} Wellcome Trust
Genome Campus{\,} Hinxton{\,} Cambridge{\,} UK. k.ye@lumc.nl},
interhash = {c169a6b9af3c58ef9b0b67eddf14b5cf},
intrahash = {adf246570a7f2f46a6499418e06999cd},
journal = {Bioinformatics},
keywords = {Algorithms; Analysis, Biology, Breakpoints; Breaks; Chromosome Computational DNA DNA; Genome; INDEL Mutation; Sequence Software methods;},
language = {eng},
medline-pst = {ppublish},
month = Nov,
number = 21,
owner = {gotto},
pages = {2865--2871},
pii = {btp394},
pmid = {19561018},
timestamp = {2014-05-13T15:48:44.000+0200},
title = {Pindel: a pattern growth approach to detect break points of large
deletions and medium sized insertions from paired-end short reads.},
url = {http://dx.doi.org/10.1093/bioinformatics/btp394},
volume = 25,
year = 2009
}