Indel caller using pattern growth

A major part of the genetic difference between individuals is encoded in the form of short indels and structural variations, such as large deletions, duplications, inversions and translocations. Recent efforts on variant detection have been fueled by next-generation high throughput sequencing. Here, we developed Pindel, a method that uses pattern growth algorithms to identify the break points of short indels and complex structural variants. The early version of Pindel was a pure split-read method. Since late 2011, a read-pair approach has been included to further boost sensitivity and specificity. Currently, Pindel is widely used by numerous research groups, institutes and commercial companies in various genome sequencing projects such as the 1,000 Genomes Project and The Cancer Genome Atlas.


  • June 2009: ‘Best Paper’ presented at the Short-SIG on Next-Generation Sequence and Algorithms for Short Read Analysis, ISMB/ECCB, Stockholm, Sweden. 500 GBP
  • July 2011: VENI grant from Dutch research organization, 'Novel algorithms to detect indels and structural variants from next- and third-generation sequencing data,' the Netherlands. 250k EURO



How to compile Pindel from source code and run it with provided demo data.


The following is a list of invited talks about Pindel:
* October 2012: Wuhan University, Wuhan, China
* December 2011: Peking University, Beijing, China
* December 2011: Chinese Academic of Science, Beijing, China
* December 2011: Huazhong University of Science and Technology, Wuhan, China
* December 2011: Beijing Forestry University, Beijing, China
* December 2011: 301 hospital, Beijing, China
* November 2010: University of Washington, Seattle, WA
* October 2010: EMBL, Heidelberg, Germany
* September 2010: Gregor Mendel Institute of Molecular Plant Biology, Austria
* July 2010: Boston College, Boston, MA
* May 2010: The Genome Institute at Washington University, St. Louis, MO
* October 2009: Max Planck Research School for Computational Biology and Scientific Computing, Berlin, Germany