%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 }