TY - JOUR T1 - Indel variant analysis of short-read sequencing data with Scalpel JF - bioRxiv DO - 10.1101/028050 SP - 028050 AU - Han Fang AU - Ewa A. Grabowska AU - Kanika Arora AU - Vladimir Vacic AU - Michael C. Zody AU - Ivan Iossifov AU - Jason A. O’Rawe AU - Yiyang Wu AU - Laura T Jimenez Barron AU - Julie Rosenbaum AU - Michael Ronemus AU - Yoon-ha Lee AU - Zihua Wang AU - Gholson J. Lyon AU - Michael Wigler AU - Michael C. Schatz AU - Giuseppe Narzisi Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/10/01/028050.abstract N2 - 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. ER -