Pindel: A pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads

  • Kai Ye
  • , Marcel H. Schulz
  • , Quan Long
  • , Rolf Apweiler
  • , Zemin Ning

Research output: Contribution to journalArticlepeer-review

1644 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)2865-2871
Number of pages7
JournalBioinformatics
Volume25
Issue number21
DOIs
StatePublished - 2009
Externally publishedYes

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