Bam-readcount - rapid generation of basepair-resolution sequence metrics.

Bam-readcount is a utility for generating low-level information about sequencing data at specific nucleotide positions. Originally designed to help filter genomic mutation calls, the metrics it outputs are useful as input for variant detection tools and for resolving ambiguity between variant callers. In addition, it has found broad applicability in diverse fields including tumor evolution, single-cell genomics, climate change ecology, and tracking community spread of SARS-CoV-2.

Genome Modeling System: A Knowledge Management Platform for Genomics.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system.

Using SomaticSniper to Detect Somatic Single Nucleotide Variants.

Detecting somatic single nucleotide variants (SNVs) is an essential component of cancer research with next generation sequencing data. This protocol describes how to run the SomaticSniper somatic SNV detector and then filter the output to eliminate most false positives. It also includes support protocols detailing the compilation of the software.

BreakDancer: Identification of Genomic Structural Variation from Paired-End Read Mapping.

The advent of the next-generation sequencing data has made it possible to cost-effectively detect and characterize genomic variation in human genomes. Structural variation, including deletion, duplication, insertion, inversion and translocation, is of great importance to human genetics due to its association with many genetic diseases. BreakDancer is a bioinformatics tool that relates paired-end read alignments from a test genome to the reference genome for the purpose of comprehensively and accurately detecting various types of structural variation.

SomaticSniper: identification of somatic point mutations in whole genome sequencing data.

Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.

Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs.