The Spliced Transcripts Alignment to a Reference (STAR) software is based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences.

CLIPper is a tool to define peaks in CLIP-seq datasets.

This package provides a C library for parsing local and remote BigWig files.

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.

PyLiftover is a library for quick and easy conversion of genomic (point) coordinates between different assemblies.

python-cwl-upgrader is a standalone upgrader for CWL documents from version draft-3, v1.0, and v1.1 to v1.2.

This package provides Shiny apps for interactive exploration of single-cell data.

BayesPrism includes deconvolution and embedding learning modules. The deconvolution module models a prior from cell type-specific expression profiles from scRNA-seq to jointly estimate the posterior distribution of cell type composition and cell type-specific gene expression from bulk RNA-seq expression of tumor samples. The embedding learning module uses Expectation-maximization (EM) to approximate the tumor expression using a linear combination of malignant gene programs while conditional on the inferred expression and fraction of non-malignant cells estimated by the deconvolution module.

This R package lets you estimate signatures of mutational processes and their activities on mutation count data. Starting from a set of single-nucleotide variants (SNVs), it allows both estimation of the exposure of samples to predefined mutational signatures (including whether the signatures are present at all), and identification of signatures de novo from the mutation counts.

Sjcount is a utility for fast quantification of splice junctions in RNA-seq data. It is annotation-agnostic and offset-aware. This version does count multisplits.

python-cwl-utils provides python utilities and autogenerated classes for loading and parsing CWL v1.0, CWL v1.1, and CWL v1.2 documents.

Millefy is a tool for visualizing read coverage of scRNA-seq(single-cell RNA sequencing) datasets in genomic contexts. By dynamically and automatically reorder single cells based on locus-specific pseudo time, Millefy highlights cell-to-cell heterogeneity in read coverage of scRNA-seq data.

Fxtract extracts sequences from a protein or nucleotide fastx (FASTA or FASTQ) file given a subsequence. It uses a simple substring search for basic tasks but can change to using POSIX regular expressions, PCRE, hash lookups or multi-pattern searching as required. By default fxtract looks in the sequence of each record but can also be told to look in the header, comment or quality sections.

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.

Anglemania extracts genes from multi-batch scRNA-seq experiments for downstream dataset integration. It improves conventional usage of highly-variable genes for integration tasks.

FLASH (Fast Length Adjustment of SHort reads) is a 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.

MoFax is a Python package for transcription factor motif analysis. It provides convenience functions to load and visualize factor models trained with MOFA+ in Python.

dRep is a Python program for rapidly comparing large numbers of genomes. dRep can also "de-replicate" a genome set by identifying groups of highly similar genomes and choosing the best representative genome for each genome set.

This package offers a set of functions to use in order to compute communities on graphs weighted or unweighted.

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

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.

Velvet is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454. Velvet currently takes in short read sequences, removes errors then produces high quality unique contigs. It then uses paired read information, if available, to retrieve the repeated areas between contigs.

This package provides an RNA-seq workflow for differential transcript usage (DTU) following Salmon quantification. This workflow performs a DTU analysis on simulated data. It also shows how to use stageR to perform two-stage testing of DTU, a statistical framework to screen at the gene level and then confirm which transcripts within the significant genes show evidence of DTU.

bustools is a program for manipulating BUS files for single cell RNA-Seq datasets. It can be used to error correct barcodes, collapse UMIs, produce gene count or transcript compatibility count matrices, and is useful for many other tasks.