Reveel: a large-scale population genotyper using low-coverage sequencing data

Please contact Lin Huang <linhuang@cs.stanford.edu> for questions or comments

Overview

Reveel is an ultrafast tool for single nucleotide variant calling and genotyping of large cohorts that have been sequenced at low coverage. The studied cohort size can be tens to tens of thousands or even larger. The initial version of Reveel uses BAM files as inputs, and produces a list of likely polymorphic sites and the genotypes of each sample at those sites. In addition, we are going to release a version which can takes genotype likelihoods calculated using SAMtools as inputs shortly.

Reveel leverages the underlying complex LD structure by employing a simplified model that scales linearly with the number of individuals in a cohort for a given number of imputed SNPs, while producing highly accurate genotype calls for both high- and low-frequency SNPs.

Highlighted features

  • Ultrafast

  • High genotyping accuracy

Publication

Lin Huang, Bo Wang, Ruitang Chen, Sivan Bercovici, and Serafim Batzoglou, "Reveel: large-scale population genotyping using low-coverage sequencing data", High Throughput Sequencing Algorithms & Applications (HiTSeq) 2015, accepted for publication in Bioinformatics.

Latest release