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.

MCView creates a Shiny app facilitating interactive exploration and annotation of Metacell models.

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 subset of the Regulatory Sequence Analysis Tools (RSAT).

CAT and BAT are pipelines for the taxonomic classification of long DNA sequences and MAGs of both known and (highly) unknown microorganisms, as generated by contemporary metagenomics studies. The core algorithm of both programs involves gene calling, mapping of predicted ORFs against the nr protein database, and voting-based classification of the entire contig / MAG based on classification of the individual ORFs. CAT and BAT can be run from intermediate steps if files are formated appropriately.

MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets.

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.

This package provides a new way of computing bootstrap supports in large phylogenies.

scvi-tools (single-cell variational inference tools) is a package for probabilistic modeling and analysis of single-cell omics data, built on top of PyTorch and AnnData.

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.

This package provides the reference implementation of CGP workflow for CaVEMan SNV analysis.

This package provides a python implementation of DESeq2.

This package provides a tool to extract assembly statistics from FASTA and FASTQ files.

The IQ-TREE software was created as the successor of IQPNNI and TREE-PUZZLE (thus the name IQ-TREE). IQ-TREE was motivated by the rapid accumulation of phylogenomic data, leading to a need for efficient phylogenomic software that can handle a large amount of data and provide more complex models of sequence evolution. To this end, IQ-TREE can utilize multicore computers and distributed parallel computing to speed up the analysis. IQ-TREE automatically performs checkpointing to resume an interrupted analysis.

As input IQ-TREE accepts all common sequence alignment formats including PHYLIP, FASTA, Nexus, Clustal and MSF. As output IQ-TREE will write a self-readable report file (name suffix .iqtree), a NEWICK tree file (.treefile) which can be visualized by tree viewer programs such as FigTree, Dendroscope or iTOL.

Key features of IQ-TREE:

• Fast and effective stochastic algorithm to reconstruct phylogenetic trees by maximum likelihood;

• An ultrafast bootstrap approximation (UFBoot) to assess branch supports;

• An ultrafast and automatic model selection (ModelFinder);

• A flexible simulator (AliSim) which can simulate sequence alignments under more realistic models than Seq-Gen and INDELible;

• Several fast branch tests like SH-aLRT and aBayes test and tree topology tests like the approximately unbiased (AU) test.

This package provides IQ-TREE version 2.

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

Spoa (SIMD POA) is a c++ implementation of the partial order alignment (POA) algorithm, which is used to generate consensus sequences. It supports three alignment modes: local (Smith-Waterman), global (Needleman-Wunsch) and semi-global alignment (overlap), and three gap modes: linear, affine and convex (piecewise affine).

This module provides code coverage metrics for Perl. Code coverage metrics describe how thoroughly tests exercise code. By using Devel::Cover you can discover areas of code not exercised by your tests and determine which tests to create to increase coverage.