Debian Med Covid-19 packages

ABACAS (Algorithm Based Automatic Contiguation of Assembled Sequences) intends to rapidly contiguate (align, order, orientate), visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence.

ABACAS uses MUMmer to find alignment positions and identify syntenies of assembled contigs against the reference. The output is then processed to generate a pseudomolecule taking overlapping contigs and gaps in to account. ABACAS generates a comparison file that can be used to visualize ordered and oriented contigs in ACT. Synteny is represented by red bars where colour intensity decreases with lower values of percent identity between comparable blocks. Information on contigs such as the orientation, percent identity, coverage and overlap with other contigs can also be visualized by loading the outputted feature file on ACT.

ABySS is a de novo, parallel, sequence assembler that is designed for short reads. It may be used to assemble genome or transcriptome sequence data. Parallelization is achieved using MPI, OpenMP and pthread.

Support code for NGS copy number algorithms. Takes a file of locations and a [cr|b]am file and generates a count of coverage of each allele [ACGT] at that location (given any filter settings).

The alleleCount package primarily exists to prevent code duplication between some other projects, specifically AscatNGS and Battenberg.

Get statistics from a list of files.

Detection of FASTA or FASTQ format of each file is automatic from the file contents, so file names and extensions are irrelevant.

The default output format is human readable. You can change the output format and ignore sequences shorter than a given length.

The nextstrain project is an attempt to make flexible informatic pipelines and visualization tools to track ongoing pathogen evolution as sequence data emerges. The nextstrain project derives from nextflu, which was specific to influenza evolution.

nextstrain is comprised of three components:

• fauna: database and IO scripts for sequence and serological data
• augur: informatic pipelines to conduct inferences from raw data
• auspice: web app to visualize resulting inferences

Remove gene-specific primer sequences from SAM/BAM alignments of PCR amplicons by soft-clipping.

bamclipper.sh soft-clips gene-specific primers from BAM alignment file based on genomic coordinates of primer pairs in BEDPE format.

This package provides some Python3 tools for common BAM file manipulations.

The BBTools are a collection of small programs to solve recurrent tasks for the creative handling of short biological RNA/DNA sequences. This suite may be best known for its mapper, which is also the name of the project on sourceforge, but several tools have been added over time. All tools are multi-threaded, implemented platform-independently in Java:

BBMap: Short read aligner for DNA and RNA-seq data. Capable of handling arbitrarily large genomes with millions of scaffolds. Handles Illumina, PacBio, 454, and other reads; very high sensitivity and tolerant of errors and numerous large indels.

BBNorm: Kmer-based error-correction and normalization tool.

Dedupe: Simplifies assemblies by removing duplicate or contained subsequences that share a target percent identity.

Reformat: Reformats reads between fasta/fastq/scarf/fasta+qual/sam, interleaved/paired, and ASCII-33/64, at over 500 MB/s.

BBDuk: Filters, trims, or masks reads with kmer matches to an artifact/contaminant file.

A bioinformatics tool for constructing the compacted de Bruijn graph from sequencing data.

This is the parallel version of the BCALM software using gatb-core library.

BCFtools is a set of utilities that manipulate variant calls in the Variant Call Format (VCF) and its binary counterpart BCF. All commands work transparently with both VCFs and BCFs, both uncompressed and BGZF-compressed.

The BEDTools utilities allow one to address common genomics tasks such as finding feature overlaps and computing coverage. The utilities are largely based on four widely-used file formats: BED, GFF/GTF, VCF, and SAM/BAM. Using BEDTools, one can develop sophisticated pipelines that answer complicated research questions by streaming several BEDTools together.

The groupBy utility is distributed in the filo package.

This package contains some tools for processing BAM files, including

  bamsormadup:  parallel sorting and duplicate marking
  bamcollate2:  reads BAM and writes BAM reordered such that alignment
                or collated by query name
  bammarkduplicates: reads BAM and writes BAM with duplicate alignments
                marked using the BAM flags field
  bammaskflags: reads BAM and writes BAM while masking (removing) bits
                from the flags column
  bamrecompress: reads BAM and writes BAM with a defined compression
                 setting. This tool is capable of multi-threading.
  bamsort:       reads BAM and writes BAM resorted by coordinates or
                 query name
  bamtofastq:    reads BAM and writes FastQ; output can be collated
                 or uncollated by query name

is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters, and particularly good at aligning to relatively long (e.g. mammalian) genomes.

Bowtie 2 indexes the genome with an FM Index to keep its memory footprint small: for the human genome, its memory footprint is typically around 3.2 GB. Bowtie 2 supports gapped, local, and paired-end alignment modes

Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs (BUSCO).

• Automated selection of lineages issued from https://www.orthodb.org/
• Automated download of all necessary files and datasets to conduct a run
• Use prodigal for non-eukaryotic genomes

This package contains BUStools program, it can be used to error correct barcodes, collapse UMIs, produce gene count or transcript compatibility count matrices

BWA is a software package for mapping low-divergent sequences against a large reference genome, such as the human genome. It consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. The first algorithm is designed for Illumina sequence reads up to 100bp, while the rest two for longer sequences ranged from 70bp to 1Mbp. BWA-MEM and BWA-SW share similar features such as long-read support and split alignment, but BWA-MEM, which is the latest, is generally recommended for high-quality queries as it is faster and more accurate. BWA-MEM also has better performance than BWA-backtrack for 70-100bp Illumina reads.

Contig Annotation Tool (CAT) and Bin Annotation Tool (BAT) are pipelines for the taxonomic classification of long DNA sequences and metagenome assembled genomes (MAGs/bins) 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 formatted appropriately.

Centrifuge is a very rapid and memory-efficient system for the classification of DNA sequences from microbial samples, with better sensitivity than and comparable accuracy to other leading systems. The system uses a novel indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index, optimized specifically for the metagenomic classification problem. Centrifuge requires a relatively small index (e.g., 4.3 GB for ~4,100 bacterial genomes) yet provides very fast classification speed, allowing it to process a typical DNA sequencing run within an hour. Together these advances enable timely and accurate analysis of large metagenomics data sets on conventional desktop computers.

Change-O is a collection of tools for processing the output of V(D)J alignment tools, assigning clonal clusters to immunoglobulin (Ig) sequences, and reconstructing germline sequences.

Dramatic improvements in high-throughput sequencing technologies now enable large-scale characterization of Ig repertoires, defined as the collection of trans-membrane antigen-receptor proteins located on the surface of B cells and T cells. Change-O is a suite of utilities to facilitate advanced analysis of Ig and TCR sequences following germline segment assignment. Change-O handles output from IMGT/HighV-QUEST and IgBLAST, and provides a wide variety of clustering methods for assigning clonal groups to Ig sequences. Record sorting, grouping, and various database manipulation operations are also included.

This package installs the library for Python 3.

The ChIP-Seq software provides a set of tools performing common genome- wide ChIP- seq analysis tasks, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. These tools exist as stand-alone C programs and perform the following tasks:

 1. Positional correlation analysis and generation of an aggregation
    plot (AP) (chipcor),
 2. Extraction of specific genome annotation features around reference
    anchor points (chipextract),
 3. Read centering or shifting (chipcenter),
 4. Narrow peak caller using a fixed width peak size (chippeak),
 5. Broad peak caller used for large regions of enrichment (chippart),
 6. Feature selection tool based on a read count threshold (chipscore).

Because the ChIP-Seq tools are primarily optimized for speed, they use their own compact format for ChIP-seq data representation called SGA (Simplified Genome Annotation). SGA is a line-oriented, tab-delimited plain text format.

ClonalFrameML is a software package that performs efficient inference of recombination in bacterial genomes. ClonalFrameML was created by Xavier Didelot and Daniel Wilson. ClonalFrameML can be applied to any type of aligned sequence data, but is especially aimed at analysis of whole genome sequences. It is able to compare hundreds of whole genomes in a matter of hours on a standard Desktop computer. There are three main outputs from a run of ClonalFrameML: a phylogeny with branch lengths corrected to account for recombination, an estimation of the key parameters of the recombination process, and a genomic map of where recombination took place for each branch of the phylogeny.

ClonalFrameML is a maximum likelihood implementation of the Bayesian software ClonalFrame which was previously described by Didelot and Falush (2007). The recombination model underpinning ClonalFrameML is exactly the same as for ClonalFrame, but this new implementation is a lot faster, is able to deal with much larger genomic dataset, and does not suffer from MCMC convergence issues

Cutadapt helps with biological sequence clean tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

This package contains the user interface.

This is the reference implementation of the Common Workflow Language standards.

The CWL open standards are for describing analysis workflows and tools in a way that makes them portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. CWL is designed to meet the needs of data-intensive science, such as Bioinformatics, Medical Imaging, Astronomy, Physics, and Chemistry.

The CWL reference implementation (cwltool) is intended to be feature complete and to provide comprehensive validation of CWL files as well as provide other tools related to working with CWL descriptions.

DCMTK includes a collection of libraries and applications for examining, constructing and converting DICOM image files, handling offline media, sending and receiving images over a network connection, as well as demonstrative image storage and worklist servers.

This package contains the DCMTK utility applications.

Note: This version was compiled with libssl support.

Delly performs Structural variant discovery by integrated paired-end and split-read analysis. It discovers, genotypes and visualizes deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. It uses paired-ends, split-reads and read-depth to sensitively and accurately delineate genomic rearrangements throughout the genome.

Dextractor commands allow one to pull exactly and only the information needed for assembly and reconstruction from the source HDF5 files produced by the PacBio RS II sequencer, or from the source BAM files produced by the PacBio Sequel sequencer.

For each of the three extracted file types -- fasta, quiva, and arrow -- the library contains commands to compress the given file type, and to decompress it, which is a reversible process delivering the original uncompressed file. The compressed .fasta files, with the extension .dexta, consume 1/4 byte per base. The compressed .quiva files, with the extension .dexqv, consume 1.5 bytes per base on average, and the compressed .arrow files, with the extension .dexar, consume 1/4 byte per base

For more information, please view the available documentation at https://github.com/thegenemyers/DEXTRACTOR

DIAMOND is a sequence aligner for protein and translated DNA searches and functions as a drop-in replacement for the NCBI BLAST software tools. It is suitable for protein-protein search as well as DNA-protein search on short reads and longer sequences including contigs and assemblies, providing a speedup of BLAST ranging up to x20,000.

Software discoSnp is designed for discovering Single Nucleotide Polymorphism (SNP) from raw set(s) of reads obtained with Next Generation Sequencers (NGS).

Note that number of input read sets is not constrained, it can be one, two, or more. Note also that no other data as reference genome or annotations are needed.

The software is composed by two modules. First module, kissnp2, detects SNPs from read sets. A second module, kissreads, enhance the kissnp2 results by computing per read set and for each found SNP:

 1) its mean read coverage
 2) the (phred) quality of reads generating the polymorphism.

This program is superseded by DiscoSnp++.

This software provide for core computational analysis of Drop-seq data, which shows you how to transform raw sequence data into an expression measurement for each gene in each individual cell.

The FASTA programs find regions of local or global similarity between Protein or DNA sequences, either by searching Protein or DNA databases, or by identifying local duplications within a sequence. Other programs provide information on the statistical significance of an alignment. Like BLAST, FASTA can be used to infer functional and evolutionary relationships between sequences as well as help identify members of gene families.

• Protein
• Protein-protein FASTA
• Protein-protein Smith-Waterman (ssearch)
• Global Protein-protein (Needleman-Wunsch) (ggsearch)
• Global/Local protein-protein (glsearch)
• Protein-protein with unordered peptides (fasts)

• Protein-protein with mixed peptide sequences (fastf)

• Nucleotide

• Nucleotide-Nucleotide (DNA/RNA fasta)
• Ordered Nucleotides vs Nucleotide (fastm)

• Un-ordered Nucleotides vs Nucleotide (fasts)

• Translated

• Translated DNA (with frameshifts, e.g. ESTs) vs Proteins (fastx/fasty)
• Protein vs Translated DNA (with frameshifts) (tfastx/tfasty)

• Peptides vs Translated DNA (tfasts)

• Statistical Significance

• Protein vs Protein shuffle (prss)
• DNA vs DNA shuffle (prss)

• Translated DNA vs Protein shuffle (prfx)

• Local Duplications

• Local Protein alignments (lalign)
• Plot Protein alignment "dot-plot" (plalign)
• Local DNA alignments (lalign)
• Plot DNA alignment "dot-plot" (plalign)

This software is often used via a web service at the EBI with readily indexed reference databases at http://www.ebi.ac.uk/Tools/fasta/.

ANI is defined as mean nucleotide identity of orthologous gene pairs shared between two microbial genomes. FastANI supports pairwise comparison of both complete and draft genome assemblies.

All-in-one FASTQ preprocessor, fastp provides functions including quality profiling, adapter trimming, read filtering and base correction. It supports both single-end and paired-end short read data and also provides basic support for long-read data.

FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.

The main functions of FastQC are

• Import of data from BAM, SAM or FastQ files (any variant)
• Providing a quick overview to tell you in which areas there may be problems
• Summary graphs and tables to quickly assess your data
• Export of results to an HTML based permanent report
• Offline operation to allow automated generation of reports without running the interactive application

Filtlong is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter.

FLASH (Fast Length Adjustment of SHort reads) is a very fast and accurate software tool to merge paired-end reads from next-generation sequencing experiments. FLASH is designed to merge pairs of reads when the original DNA fragments are shorter than twice the length of reads. The resulting longer reads can significantly improve genome assemblies. They can also improve transcriptome assembly when FLASH is used to merge RNA-seq data.

Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PacBio / ONT reads as input and outputs polished contigs. Flye also has a special mode for metagenome assembly.

FreeBayes is a Bayesian genetic variant detector designed to find small polymorphisms, specifically SNPs (single-nucleotide polymorphisms), indels (insertions and deletions), MNPs (multi-nucleotide polymorphisms), and complex events (composite insertion and substitution events) smaller than the length of a short-read sequencing alignment.

The GenomeTools contains a collection of useful tools for biological sequence analysis and -presentation combined into a single binary.

The toolkit contains binaries for sequence and annotation handling, sequence compression, index structure generation and access, annotation visualization, and much more.

Gffread is a GFF/GTF parsing utility providing format conversions, region filtering, FASTA sequence extraction and more.

Ginkgo CADx provides a complete DICOM viewer solution with advanced capabilities and support for extensions.

• Easy and customizable interface through profiles.
• Full featured DICOM image visualization.
• Complete tool set (measure, markers, text, ...).
• Multiple modalities support (Neurological, Radiological, Dermatological, Ophthalmological, Ultrasound, Endoscopy, ...)
• Dicomization support from JPEG, PNG, GIF and TIFF.
• Full EMH integration support: HL7 standard and IHE compliant workflows.
• PACS Workstation (C-FIND, C-MOVE, C-STORE...)
• Extensible through custom extensions.
• Retinal image mosaic composition.
• Automatic retinal analysis diagnostics.
• Psoriasis automatic diagnostics.

This is the GNUmed Electronic Medical Record. Its purpose is to enable doctors to keep a medically sound record on their patients' health. It does not currently provide functionality for stock keeping. Clinical features are well-tested by real doctors in the field.

While the GNUmed team has taken the utmost care to make sure the medical records are safe at all times you still need to make sure you are taking appropriate steps to backup the medical data to a safe place at appropriate intervals. Do not forget to test your recovery procedures, too !

Protect your data! GNUmed itself comes without any warranty whatsoever. You have been warned.

This package contains the wxpython client.

This is the GNUmed Electronic Medical Record. Its purpose is to enable doctors to keep a medically sound record on their patients' health. It does not currently provide functionality for billing and stock keeping. Clinical features are well-tested by real doctors in the field.

While the GNUmed team has taken the utmost care to make sure the medical records are safe at all times you still need to make sure you are taking appropriate steps to backup the medical data to a safe place at appropriate intervals. Do not forget to test your recovery procedures, too !

Protect your data! GNUmed itself comes without any warranty whatsoever. You have been warned.

This package contains the PostgreSQL server part.

Note: The package does currently NOT build the GNUmed database but just installs the needed SQL files. Please see README.Debian.

GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.

It is primarily designed for biochemical molecules like proteins and lipids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non- biological systems, e.g. polymers.

This package contains variants both for execution on a single machine, and using the MPI interface across multiple machines.

Gubbins supports rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences.

Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively identifies loci containing elevated densities of base substitutions while concurrently constructing a phylogeny based on the putative point mutations outside of these regions. Simulations demonstrate the algorithm generates highly accurate reconstructions under realistic models of short-term bacterial evolution, and can be run in only a few hours on alignments of hundreds of bacterial genome sequences.

It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window.

It can calculate area and pixel value statistics of user-defined selections. It can measure distances and angles. It can create density histograms and line profile plots. It supports standard image processing functions such as contrast manipulation, sharpening, smoothing, edge detection and median filtering.

Spatial calibration is available to provide real world dimensional measurements in units such as millimeters. Density or gray scale calibration is also available.

ImageJ is developed by Wayne Rasband (wayne@codon.nih.gov), is at the Research Services Branch, National Institute of Mental Health, Bethesda, Maryland, USA.

iVar is a computational package that contains functions broadly useful for viral amplicon-based sequencing. Additional tools for metagenomic sequencing are actively being incorporated into iVar. While each of these functions can be accomplished using existing tools, iVar contains an intersection of functionality from multiple tools that are required to call iSNVs and consensus sequences from viral sequencing data across multiple replicates. iVar provided the following functions:

 1. trimming of primers and low-quality bases,
 2. consensus calling,
 3. variant calling - both iSNVs and insertions/deletions, and
 4. identifying mismatches to primer sequences and excluding the
    corresponding reads from alignment files.

Kalign is a command line tool to perform multiple alignment of biological sequences. It employs the Muth-Manber string-matching algorithm, to improve both the accuracy and speed of the alignment. It uses global, progressive alignment approach, enriched by employing an approximate string-matching algorithm to calculate sequence distances and by incorporating local matches into the otherwise global alignment.

Kallisto is a program for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment. On benchmarks with standard RNA-Seq data, kallisto can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build. Pseudoalignment of reads preserves the key information needed for quantification, and kallisto is therefore not only fast, but also as accurate than existing quantification tools. In fact, because the pseudoalignment procedure is robust to errors in the reads, in many benchmarks kallisto significantly outperforms existing tools.

Kraken 2 is the newest version of Kraken, a taxonomic classification system using exact k-mer matches to achieve high accuracy and fast classification speeds. This classifier matches each k-mer within a query sequence to the lowest common ancestor (LCA) of all genomes containing the given k-mer. The k-mer assignments inform the classification algorithm. [see: Kraken 1's Webpage for more details].

Kraken 2 provides significant improvements to Kraken 1, with faster database build times, smaller database sizes, and faster classification speeds. These improvements were achieved by the following updates to the Kraken classification program:

 1. Storage of Minimizers: Instead of storing/querying entire k-mers,
    Kraken 2 stores minimizers (l-mers) of each k-mer. The length of
    each l-mer must be ≤ the k-mer length. Each k-mer is treated by
    Kraken 2 as if its LCA is the same as its minimizer's LCA.
 2. Introduction of Spaced Seeds: Kraken 2 also uses spaced seeds to
    store and query minimizers to improve classification accuracy.
 3. Database Structure: While Kraken 1 saved an indexed and sorted list
    of k-mer/LCA pairs, Kraken 2 uses a compact hash table. This hash
    table is a probabilistic data structure that allows for faster
    queries and lower memory requirements. However, this data structure
    does have a <1% chance of returning the incorrect LCA or returning
    an LCA for a non-inserted minimizer. Users can compensate for this
    possibility by using Kraken's confidence scoring thresholds.
 4. Protein Databases: Kraken 2 allows for databases built from amino
    acid sequences. When queried, Kraken 2 performs a six-frame
    translated search of the query sequences against the database.
 5. 16S Databases: Kraken 2 also provides support for databases not
    based on NCBI's taxonomy. Currently, these include the 16S
    databases: Greengenes, SILVA, and RDP.

LASTZ is a drop-in replacement for BLASTZ, and is backward compatible with BLASTZ’s command-line syntax. That is, it supports all of BLASTZ’s options but also has additional ones, and may produce slightly different alignment results.

BBHash is a simple library for building minimal perfect hash function. It is designed to handle large scale datasets. The function is just a little bit larger than other state-of-the-art libraries, it takes approximately 3 bits / elements (compared to 2.62 bits/elem for the emphf lib), but construction is faster and does not require additional memory.

libchipcard provides an API for accessing smartcards. Examples are memory cards, as well as HBCI (home banking), German GeldKarte (electronic small change), and KVK (health insurance) cards.

This package contains the development files for libchipcard.

This is an eclectic gathering of (mostly) C++ code which upstream used for some bioinformatics projects. The main idea is to provide lean code and efficient data structures, trying to avoid too many code dependencies of heavy libraries while minimizing production cycles (and this also implies a decent compile/build time -- looking at you, bloated configure scripts and lengthy compile times of Boost code or other heavy C++ template code..).

This code was gathered even before the C++ STL had been fully adopted as a cross-platform "standard". Since STL by itself is a bit heavier for most of the C++ needs, it is preferred to use simpler&leaner C++ classes or templates for basic strings, containers, basic algorithms etc.

Header files of Genome Code Lib. It is mainly known for being used by StringTie but with its own release cycle.

Grassroots DiCoM is a C++ library for DICOM medical files. It is automatically wrapped to python/C#/Java (using swig). It supports RAW,JPEG (lossy/lossless),J2K,JPEG-LS, RLE and deflated.

Install this package for the gdcmanon, gdcmclean, gdcmconv, gdcmdiff, gdcmdump, gdcmpap3, gdcmgendir, gdcmimg, gdcminfo, gdcmpdf, gdcmraw, gdcmscanner, gdcmscu, gdcmtar, gdcmxml programs.

This library implements the custom CRAM codecs used for "EXTERNAL" block types. These consist of two variants of the rANS codec (8-bit and 16-bit renormalisation, with run-length encoding and bit-packing also supported in the latter), a dynamic arithmetic coder, and custom codecs for name/ID compression and quality score compression derived from fqzcomp.

They come with small command line test tools to act as both compression exploration programs and as part of the test harness.

This package contains the development headers

This is the reference library for ICS (Image Cytometry Standard), an open standard for writing images of any dimensionality and data type to file, together with associated information regarding the recording equipment or recorded subject.

This package contains the libraries needed to build ICS applications.

Libmaus2 is a collection of data structures and algorithms. It contains

• I/O classes (single byte and UTF-8)
• bitio classes (input, output and various forms of bit level manipulation)
• text indexing classes (suffix and LCP array, fulltext and minute (FM), ...)
• BAM sequence alignment files input/output (simple and collating)

and many lower level support classes.

This package contains header files and static libraries.

A helping Java package adopted by a range of Open Source tools for the analysis of B and T cell repertoires.

SeqAn is a C++ template library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. This library applies a unique generic design that guarantees high performance, generality, extensibility, and integration with other libraries. SeqAn is easy to use and simplifies the development of new software tools with a minimal loss of performance.

This package contains the developer files.

Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.

LUMPY, a novel SV discovery framework that naturally integrates multiple SV signals jointly across multiple samples. LUMPY yields improved sensitivity, especially when SV signal is reduced owing to either low coverage data or low intra-sample variant allele frequency.

An improved version of MECAT. It is an ultra-fast and accurate mapping and error correcting de novo assembly tools for single molecula sequencing (SMRT) reads. MECAT2 consists of the following three modules:

 1. mecat2map: a fast and accurate alignment tool for SMRT reads.
 2. mecat2cns: correct noisy reads based on their pairwise overlaps.
 3. fsa: a string graph based assembly tool.

Megahit is an ultra-fast and memory-efficient NGS assembler. It is optimized for metagenomes, but also works well on generic single genome assembly (small or mammalian size) and single-cell assembly.

The software was praised in a Briefings in Bioinformatics 5/2020 review (DOI: 10.1093/bib/bbaa085).

MetaBAT integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. It automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node.

What was referred to as "next-generation" DNA sequencing up to the year 2020 delivered only "short" reads up to ~600 base pairs in length that would then have to be puzzled by random overlaps in their sequence towards a complete genome. This is the genome assembly. And there are many biological pitfalls on long stretches of low complexity regions and copy number variations and other sorts of redundancies that render this difficult.

This package provides a short-read DNA sequence assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day.

The output of Minia is a set of contigs, i.e. stretches of gap-free linear overlaps of short reads. In the best possible case this is a whole chromosome.

Minia produces results of similar contiguity and accuracy to other de Bruijn assemblers (e.g. Velvet).

Minimap2 is a versatile sequence alignment program that aligns DNA or mRNA sequences against a large reference database. Typical use cases include: (1) mapping PacBio or Oxford Nanopore genomic reads to the human genome; (2) finding overlaps between long reads with error rate up to ~15%; (3) splice-aware alignment of PacBio Iso-Seq or Nanopore cDNA or Direct RNA reads against a reference genome; (4) aligning Illumina single- or paired-end reads; (5) assembly-to-assembly alignment; (6) full- genome alignment between two closely related species with divergence below ~15%.

For ~10kb noisy reads sequences, minimap2 is tens of times faster than mainstream long-read mappers such as BLASR, BWA-MEM, NGMLR and GMAP. It is more accurate on simulated long reads and produces biologically meaningful alignment ready for downstream analyses. For >100bp Illumina short reads, minimap2 is three times as fast as BWA-MEM and Bowtie2, and as accurate on simulated data. Detailed evaluations are available from the minimap2 paper or the preprint.

MacroMoleculeBuilder, previously known as RNABuilder, can be used for morphing, homology modeling, folding (e.g. using base pairing contacts), redesigning complexes, fitting to low-resolution density maps, predicting local rearrangements upon mutation, and many other applications.

MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge proteins/nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

The sequencing of DNA or RNA with current high-throughput technologies involves an array of tools and these are applied over a range of samples. It is easy to loose oversight. And gathering the data and forwarding them in a readable manner to the individuals who took the samples is a challenge for a tool in itself. Well. Here it is. MultiQC aggregates the output of multiple tools into a single report.

Reports are generated by scanning given directories for recognised log files. These are parsed and a single HTML report is generated summarising the statistics for all logs found. MultiQC reports can describe multiple analysis steps and large numbers of samples within a single plot, and multiple analysis tools making it ideal for routine fast quality control.

MUSCLE is a multiple alignment program for protein sequences. MUSCLE stands for multiple sequence comparison by log-expectation. In the authors tests, MUSCLE achieved the highest scores of all tested programs on several alignment accuracy benchmarks, and is also one of the fastest programs out there.

Muscle v5 is a major re-write of MUSCLE based on new algorithms.

Users should be aware that command line arguments compared to version 3.x of MUSCLE have changed!

Highest accuracy, scalable to thousands of sequences

Compared to previous versions, Muscle v5 is much more accurate, is often faster, and scales to much larger datasets. At the time of writing (late 2021), Muscle v5 has the highest scores on multiple alignment benchmarks including Balibase, Bralibase, Prefab and Balifam. It can align tens of thousands of sequences with high accuracy on a low-cost commodity computer (say, an 8-core Intel CPU with 32 Gb RAM). On large datasets, Muscle v5 is 20-30% more accurate than MAFFT and Clustal-Omega.

Alignment ensembles

Muscle v5 can generate ensembles of high-accuracy alternative alignments. All replicates have equal average accuracy on benchmark test, including the MSA made with default parameters. By comparing results of downstream analysis (trees, structure prediction...) on different replicates, you can assess the effects of alignment errors on your study.

MUSCLE is a multiple alignment program for protein sequences. MUSCLE stands for multiple sequence comparison by log-expectation. In the authors tests, MUSCLE achieved the highest scores of all tested programs on several alignment accuracy benchmarks, and is also one of the fastest programs out there.

This is version 3 of the muscle program. It is a different program than muscle version 5 which is packaged as muscle in Debian.

Filtering and trimming of long read sequencing data. 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.

Intended to be used:

 1. directly after fastq extraction.
 2. prior to mapping.
 3. in a stream between extraction and mapping.

NanoLyse is a tool for rapid removal of contaminant DNA, using the Minimap2 aligner through the mappy Python binding. A typical application would be the removal of the lambda phage control DNA fragment supplied by ONT, for which the reference sequence is included in the package. However, this approach may lead to unwanted loss of reads from regions highly homologous to the lambda phage genome.

NanoOK is a flexible, multi-reference software for pre- and post- alignment analysis of nanopore sequencing data, quality and error profiles.

NanoOK (pronounced na-nook) is a tool for extraction, alignment and analysis of Nanopore reads. NanoOK will extract reads as FASTA or FASTQ files, align them (with a choice of alignment tools), then generate a comprehensive multi-page PDF report containing yield, accuracy and quality analysis. Along the way, it generates plain text files which can be used for further analysis, as well as graphs suitable for inclusion in presentations and papers.

Nanopolish uses a signal-level hidden Markov model for consensus calling of nanopore genome sequencing data. It can perform signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more.

NanoSV is a software package that can be used to identify structural genomic variations in long-read sequencing data, such as data produced by Oxford Nanopore Technologies’ MinION, GridION or PromethION instruments, or Pacific Biosciences RSII or Sequel sequencers. NanoSV has been extensively tested using Oxford Nanopore MinION sequencing data.