Indel variant analysis of short-read sequencing data with Scalpel
Han FangiD, Ewa A. Grabowska, Kanika Arora, Vladimir VaciciD, Michael C. ZodyiD, Ivan Iossifov, Jason A. ORawe, Yiyang Wu, Laura T Jimenez Barron, Julie Rosenbaum, Michael RonemusiD, Yoon-ha Lee, Zihua Wang, Gholson J. LyoniD, Michael Wigler, Michael C. SchatziD, Giuseppe NarzisiiD
Abstract
As the second most common type of variations in the human genome, insertions and deletions (indels) have been linked to many diseases, but indels of more than a few bases are still challenging to discover from short-read sequencing data. Scalpel (http://scalpel.sourceforge.net) is open-source software for reliable indel detection based on the micro-assembly technique. To date, it has been successfully used to discover mutations in novel candidate genes for autism, and is extensively used in other large-scale studies of human diseases. This protocol gives an overview of the algorithm and describes how to use Scalpel to perform highly accurate indel calling from whole genome and exome sequencing data. We provide detailed instructions for an exemplary family-based de novo study, but we also characterize the other two supported modes of operation for single sample and somatic analysis. Indel normalization, visualization, and annotation of the mutations are also illustrated. Using a standard server, indel discovery and characterization in the exonic regions of the example sequencing data can be finished in ~6 hours after read mapping.
02 /Specification & Classification
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