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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:
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
Descripción
Sumario: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