Introduction

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.

Publications

  1. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads.
    Cite this
    Ye K, Schulz MH, Long Q, Apweiler R, Ning Z, 2009-11-01 - Bioinformatics (Oxford, England)

Credits

  1. Kai Ye
    Developer

  2. Marcel H Schulz
    Developer

  3. Quan Long
    Developer

  4. Rolf Apweiler
    Developer

  5. Zemin Ning
    Investigator

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Summary
AccessionBT006280
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Submitted ByZemin Ning