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.

The FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing.

Next-Generation sequencing machines usually produce FASTA or FASTQ files, containing multiple short-reads sequences. The main processing of such FASTA/FASTQ files is mapping the sequences to reference genomes. However, it is sometimes more productive to preprocess the files before mapping the sequences to the genome---manipulating the sequences to produce better mapping results. The FASTX-Toolkit tools perform some of these preprocessing tasks.

Drop-seq is a technology to enable biologists to analyze RNA expression genome-wide in thousands of individual cells at once. This package provides tools to perform Drop-seq analyses.

This package provides a companion annotation file to the IlluminaHumanMethylationEPICmanifest package based on the same annotation 1.0B5.

This package implements the method csSAM that computes cell-specific differential expression from measured cell proportions using SAM.

t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensionality reduction and visualization of high dimensional datasets. A popular implementation of t-SNE uses the Barnes-Hut algorithm to approximate the gradient at each iteration of gradient descent. This package is a Cython wrapper for FIt-SNE.

Screed parses FASTA and FASTQ files and generates databases. Values such as sequence name, sequence description, sequence quality and the sequence itself can be retrieved from these databases.

This package provides a collection of useful functions for working with DNA methylation micro-array data.

This is a Python package for the interactive visualization of bulk RNA-seq data. It provides a range of plotting functions and interactive tools to explore and analyze bulk RNA-seq data.

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.

FAN-C provides a pipeline for analysing Hi-C data starting at mapped paired-end sequencing reads.

Presto is a python toolkit for processing raw reads from high-throughput sequencing of B cell and T cell repertoires.

Logomaker is a Python package for generating publication-quality sequence logos. Logomaker can generate both standard and highly customized logos illustrating the properties of DNA, RNA, or protein sequences. Logos are rendered as vector graphics embedded within native matplotlib Axes objects, making them easy to style and incorporate into multi-panel figures.

PRANK is a probabilistic multiple sequence alignment program for DNA, codon and amino-acid sequences. It is based on a novel algorithm that treats insertions correctly and avoids over-estimation of the number of deletion events. In addition, PRANK borrows ideas from maximum likelihood methods used in phylogenetics and correctly takes into account the evolutionary distances between sequences. Lastly, PRANK allows for defining a potential structure for sequences to be aligned and then, simultaneously with the alignment, predicts the locations of structural units in the sequences.

MethylDackel will process a coordinate-sorted and indexed BAM or CRAM file containing some form of BS-seq alignments and extract per-base methylation metrics from them. MethylDackel requires an indexed fasta file containing the reference genome as well.

Picard is a set of Java command line tools for manipulating high-throughput sequencing (HTS) data and formats. Picard is implemented using the HTSJDK Java library to support accessing file formats that are commonly used for high-throughput sequencing data such as SAM, BAM, CRAM and VCF.

DelayedArray based image operations.

Python scripts to find enrichment of GO terms. In addition, this package is used for processing the obo-formatted file from Gene Ontology website. The data structure is a directed acyclic graph that allows easy traversal from leaf to root.

CGAT-core is a set of libraries and helper functions used to enable researchers to design and build computational workflows for the analysis of large-scale data-analysis.

ParDRe is a parallel tool to remove duplicate genetic sequence reads. Duplicate reads can be seen as identical or nearly identical sequences with some mismatches. This tool lets users avoid the analysis of unnecessary reads, reducing the time of subsequent procedures with the dataset (e.g. assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters.

InDelFixer is a sensitive aligner for 454, Illumina and PacBio data, employing a full Smith-Waterman alignment against a reference. This Java command line application aligns Next-Generation Sequencing (NGS) and third-generation reads to a set of reference sequences, by a prior fast k-mer matching and removes indels, causing frame shifts. In addition, only a specific region can be considered. An iterative refinement of the alignment can be performed, by alignment against the consensus sequence with wobbles. The output is in SAM format.

This package implements bindings for zarr store that are compatible with Bioconductor S4 data structures, namely the DataFrame and DelayedArray. This allows Zarr-backed data to be easily used as data frames with arbitrary sets of columns.

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.

Scallop is a reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts.