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 growt...

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Detalles Bibliográficos
Autores principales: Ye, Kai, Schulz, Marcel H., Long, Quan, Apweiler, Rolf, Ning, Zemin
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Ismb/Eccb 2009 Special Interest Group on Short Read Sequencing
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2781750/
https://www.ncbi.nlm.nih.gov/pubmed/19561018
http://dx.doi.org/10.1093/bioinformatics/btp394
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author Ye, Kai
Schulz, Marcel H.
Long, Quan
Apweiler, Rolf
Ning, Zemin
author_facet Ye, Kai
Schulz, Marcel H.
Long, Quan
Apweiler, Rolf
Ning, Zemin
author_sort Ye, Kai
collection PubMed
description 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
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spelling pubmed-27817502009-11-25 Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads Ye, Kai Schulz, Marcel H. Long, Quan Apweiler, Rolf Ning, Zemin Bioinformatics Ismb/Eccb 2009 Special Interest Group on Short Read Sequencing 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 2009-11-01 2009-06-26 /pmc/articles/PMC2781750/ /pubmed/19561018 http://dx.doi.org/10.1093/bioinformatics/btp394 Text en © The Author(s) 2009. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Ismb/Eccb 2009 Special Interest Group on Short Read Sequencing
Ye, Kai
Schulz, Marcel H.
Long, Quan
Apweiler, Rolf
Ning, Zemin
Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
title Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
title_full Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
title_fullStr Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
title_full_unstemmed Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
title_short Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
title_sort pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
topic Ismb/Eccb 2009 Special Interest Group on Short Read Sequencing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2781750/
https://www.ncbi.nlm.nih.gov/pubmed/19561018
http://dx.doi.org/10.1093/bioinformatics/btp394
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