David Roazen

TL;DR: This unit describes how to use BWA and the Genome Analysis Toolkit to map genome sequencing data to a reference and produce high‐quality variant calls that can be used in downstream analyses.

TL;DR: A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.

TL;DR: Using an improved human mutation rate model, human protein-coding genes are classified along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.

TL;DR: A novel assembly-based approach to variant calling, the GATK HaplotypeCaller and Reference Confidence Model, that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously, showing that the accuracy of indel variant calling is superior in comparison to other algorithms.