This package offers a quick and straight-forward way to explore and perform basic analysis of single cell sequencing data coming from droplet sequencing. It has been particularly tailored for Drop-seq.

This package Copynumber KAryotyping of Tumors infers genomic copy number and subclonal structure of human tumors using integrative Bayesian approaches to identify genome-wide aneuploidy at 5MB resolution in single cells data. It separates tumor cells and tumor subclones from normal cells using high-throughput sc-RNAseq data.

Kaiju is a program for sensitive taxonomic classification of high-throughput sequencing reads from metagenomic whole genome sequencing experiments.

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.

Smithlab CPP is a C++ library that includes functions used in many of the Smith lab bioinformatics projects, such as a wrapper around Samtools data structures, classes for genomic regions, mapped sequencing reads, etc.

Cooler is a support library for a sparse, compressed, binary persistent storage format, called cool, used to store genomic interaction data, such as Hi-C contact matrices.

Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats, including optionally gzip'ed BED, GFF, SAM, VCF, FASTA/Q and TAB-delimited formats with column names. It also adds a few built-in functions and a command line option to use TAB as the input/output delimiter. When the new functionality is not used, bioawk is intended to behave exactly the same as the original BWK awk.

This package provides accelerated functions for the CIRI toolkit. It also provides the ccs executable to scan for circular consensus sequences.

This helper package implements the HiCMatrix class for the HiCExplorer and pyGenomeTracks packages.

LAMMPS is a classical molecular dynamics simulator designed to run efficiently on parallel computers. LAMMPS has potentials for solid-state materials (metals, semiconductors), soft matter (biomolecules, polymers), and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale.

Psupertime is supervised pseudotime for single cell RNAseq data. It uses single cell RNAseq data, where the cells have a known ordering. This ordering helps to identify a small number of genes which place cells in that known order. It can be used for discovery of relevant genes, for identification of subpopulations, and characterization of further unknown or differently labelled data.

Bismark is a program to map bisulfite treated sequencing reads to a genome of interest and perform methylation calls in a single step. The output can be easily imported into a genome viewer, such as SeqMonk, and enables a researcher to analyse the methylation levels of their samples straight away. Its main features are:

• Bisulfite mapping and methylation calling in one single step

• Supports single-end and paired-end read alignments

• Supports ungapped and gapped alignments

• Alignment seed length, number of mismatches etc are adjustable

• Output discriminates between cytosine methylation in CpG, CHG and CHH context

This tool offers a pipeline for inferring gene expression programs from scRNA-Seq. It takes a count matrix (N cells X G genes) as input and produces a (K x G) matrix of gene expression programs (GEPs) and a (N x K) matrix specifying the usage of each program for each cell in the data.

Salmon is a program to produce highly-accurate, transcript-level quantification estimates from RNA-seq data. Salmon achieves its accuracy and speed via a number of different innovations, including the use of lightweight alignments (accurate but fast-to-compute proxies for traditional read alignments) and massively-parallel stochastic collapsed variational inference.

This is a Python module for analyzing cell-hashing/nucleus-hashing data. It is the demultiplexing module of Pegasus, which is used by Cumulus in the demultiplexing step.

This framework facilitates the execution of differential junction usage (DJU) methods. Additionally, it enables the integration of results from multiple DJU methods.

This is a set of functions for processing raw scDam&T-seq data. scDam&T-seq is a method to simultaneously measure protein-DNA interactions and transcription from single cells (Rooijers et al., 2019). It combines a DamID-based method to measure protein-DNA interactions and an adaptation of CEL-Seq to measure transcription. The starting point of the workflow is raw sequencing data and the end result are tables of UMI-unique DamID and CEL-Seq counts.

The SRA Toolkit from NCBI is a collection of tools and libraries for reading of sequencing files from the Sequence Read Archive (SRA) database and writing files into the .sra format.

Pegasusio is a Python package for reading or writing single-cell genomics data.

DNA Features Viewer is a Python library to visualize DNA features, e.g. from GenBank or Gff files, or Biopython SeqRecords.

Bandage is a program for visualising de novo assembly graphs. It allows users to interact with the assembly graphs made by de novo assemblers such as Velvet, SPAdes, MEGAHIT and others. De novo assembly graphs contain not only assembled contigs but also the connections between those contigs, which were previously not easily accessible. Bandage visualises assembly graphs, with connections, using graph layout algorithms. Nodes in the drawn graph, which represent contigs, can be automatically labelled with their ID, length or depth. Users can interact with the graph by moving, labelling and colouring nodes. Sequence information can also be extracted directly from the graph viewer. By displaying connections between contigs, Bandage opens up new possibilities for analysing and improving de novo assemblies that are not possible by looking at contigs alone.

HMMER is used for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs).

Vcflib provides methods to manipulate and interpret sequence variation as it can be described by VCF. It is both an API for parsing and operating on records of genomic variation as it can be described by the VCF format, and a collection of command-line utilities for executing complex manipulations on VCF files.

WhatsHap is software for phasing genomic variants using DNA sequencing reads, also called read-based phasing or haplotype assembly. It is especially suitable for long reads, but works also well with short reads.