This package provides a component of the Trinity Cancer Transcriptome Analysis Toolkit (CTAT). It uses the STAR aligner to identify candidate fusion transcripts supported by Illumina reads. It further processes the output generated by the STAR aligner to map junction reads and spanning reads to a reference annotation set.

This package contains a set of common Perl utilities for generating consistent Vcf headers. It primarily exists to prevent code duplication between some other projects.

SHARC is a pipeline for somatic SV calling and filtering from tumor-only Nanopore sequencing data. It performs mapping, SV calling, SV filtering, random forest classification, blacklist filtering and SV prioritization, followed by automated primer design for PCR amplicons of 80-120 bp that are useful to track cancer ctDNA molecules in liquid biopsies.

This package provides an implementation of the CaVEMan program. It uses an expectation maximisation approach to calling single base substitutions in paired data. It is designed for use with a compute cluster. Most steps in the program make use of an index parameter. The split step is designed to divide the genome into chunks of adjustable size to optimise for runtime/memory usage requirements.

SHARC is a pipeline for somatic SV calling and filtering from tumor-only Nanopore sequencing data. It performs mapping, SV calling, SV filtering, random forest classification, blacklist filtering and SV prioritization, followed by automated primer design for PCR amplicons of 80-120 bp that are useful to track cancer ctDNA molecules in liquid biopsies.

SHARC is a pipeline for somatic SV calling and filtering from tumor-only Nanopore sequencing data. It performs mapping, SV calling, SV filtering, random forest classification, blacklist filtering and SV prioritization, followed by automated primer design for PCR amplicons of 80-120 bp that are useful to track cancer ctDNA molecules in liquid biopsies.

This package provides a tool to download or view data in the cloud environments of ICGC.

SeqAn is a C++ library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. It contains algorithms and data structures for string representation and their manipulation, online and indexed string search, efficient I/O of bioinformatics file formats, sequence alignment, and more.

The Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.

SPAdes is an assembly toolkit containing various assembly pipelines.

This package provides a python implementation of DESeq2.

Anvi’o is a comprehensive platform that brings together many aspects of today’s computational strategies of data-enabled microbiology, including genomics, metagenomics, metatranscriptomics, pangenomics, metapangenomics, phylogenomics, and microbial population genetics in an integrated and easy-to-use fashion through extensive interactive visualization capabilities.

The goal of NicheNet is to study intercellular communication from a computational perspective. NicheNet uses human or mouse gene expression data of interacting cells as input and combines this with a prior model that integrates existing knowledge on ligand-to-target signaling paths. This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest.

Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small cohorts and somatic variation in tumor/normal sample pairs. The germline caller employs an efficient tiered haplotype model to improve accuracy and provide read-backed phasing, adaptively selecting between assembly and a faster alignment-based haplotyping approach at each variant locus. The germline caller also analyzes input sequencing data using a mixture-model indel error estimation method to improve robustness to indel noise. The somatic calling model improves on the original Strelka method for liquid and late-stage tumor analysis by accounting for possible tumor cell contamination in the normal sample. A final empirical variant re-scoring step using random forest models trained on various call quality features has been added to both callers to further improve precision.

This package contains the following programs: bamcollate2, bammarkduplicates, bammaskflags, bamrecompress, bamsort, bamtofastq.

This package provides tools for rapid prokaryotic genome annotation.

This package primarily exists to prevent code duplication between some other projects, specifically AscatNGS and Battenburg.

Scriabin aims to provide a comprehensive view of cell-cell communication (CCC). It achieves this without requiring subsampling or aggregation.

Mellon is a non-parametric cell-state density estimator based on a nearest-neighbors-distance distribution. It uses a sparse gaussian process to produce a differntiable density function that can be evaluated out of sample.