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

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

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

This package computes metrics and generates Interactive QC plots from the sequencing summary report generated by Oxford Nanopore technologies basecaller.

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

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 3.

This package contains functions to extract information from Oxford Nanopore sequencing data and alignments.

Primer3 is a widely used program for designing PCR primers. PCR is an essential and ubiquitous tool in genetics and molecular biology. Primer3 can also design hybridization probes and sequencing primers.

Primer3-py is a Python-abstracted API for the popular Primer3 library. The intention is to provide a simple and reliable interface for automated oligo analysis and design.

Primer3-py also includes bindings for the Primer3 primer design engine if you’d prefer to use an established pipeline. The IO parameters mirror those of the original Primer3, but you don’t have to deal with messy and slow file IO for your automated workflows.

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.

This packages provides a collection of small and efficient programs for performing some common and uncommon tasks with FASTQ files.

This package provides a phylogeny dating method using least-squares algorithms and criteria.

hiddenDomains is a suite of programs used to identify significant enrichment of ChIP-seq reads that span large domains, like HK27me3. The input data can be in BAM format, or in a tab-delimited 'reads per bin' format described below. The output is a BED formatted file the lists the enriched domains and their posterior probabilities.

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.

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.

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 provides a python implementation of DESeq2.

This package provides tools for filtering on quality and/or read length, and optional trimming after passing filters. Reads from stdin, writes to stdout. Optionally reads directly from an uncompressed file specified on the command line. It is intended to be used directly after fastq extraction, prior to mapping, or in a stream between extraction and mapping.

This package is designed to help the scientist, engineer, statistician, etc., to construct appropriate experimental designs.

This package is designed to help the scientist, engineer, statistician, etc., to construct appropriate experimental designs.

The carputils framework will be the optimal way to access openCARP for most users. This Python framework was developed to provide the means to easily encode in silico experiments including pre- and postprocessing. carputils will call the openCARP simulator.

BLT is a streamlined CMake-based foundation for Building, Linking and Testing large-scale high performance computing (HPC) application.