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.

Maxent is a stand-alone Java application for modelling species geographic distributions.

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

An interval map structure that is optimized for low memory (each interval is represented by about 3 words + whatever the cargo is) and has semantics that are appropriate for genomic intervals (namely, intervals can overlap and queries will return all matches together). It also designed to be used in two phases: a construction phase + query phase).

This package lets you read and write the PLINK BED format, simply and efficiently.

This package conducts batch effects removal from a taxa read count table by a conditional quantile regression method. The distributional attributes of microbiome data - zero-inflation and over-dispersion, are simultaneously considered.

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.

Several studies focus on the inference of developmental and response trajectories from single cell RNA-Seq (scRNA-Seq) data. A number of computational methods, often referred to as pseudo-time ordering, have been developed for this task. CRISPR has also been used to reconstruct lineage trees by inserting random mutations. The tbsp package implements an alternative method to detect significant, cell type specific sequence mutations from scRNA-Seq data.

MafFilter is a program dedicated to the analysis of genome alignments. It parses and manipulates MAF files as well as more simple fasta files. This package can be used to design a pipeline as a series of consecutive filters, each performing a dedicated analysis. Many of the filters are available, from alignment cleaning to phylogeny reconstruction and population genetics analysis. Despite various filtering options and format conversion tools, MafFilter can compute a wide range of statistics (phylogenetic trees, nucleotide diversity, inference of selection, etc.).

This package provides a toolbox to process, analyze and visualize spatial single-cell expression data.

This package provides a set of R functions to parse markdown and other generic helpers.

The HH-suite is a software package for sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs).

dnaio is a Python library for fast parsing of FASTQ and also FASTA files. The code was previously part of the cutadapt tool.

Implementation of the Smith-Waterman algorithm.

This package can be used to normalize cytometry samples when a control sample is taken along in each of the batches. This is done by first identifying multiple clusters/cell types, learning the batch effects from the control samples and applying quantile normalization on all markers of interest.

This package provides a computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry and imaging data.

Bíogo is a bioinformatics library for the Go language.

This library contains the genomics components of the Bio++ sequence library. It is part of the Bio++ project.

StringTie is a fast and efficient assembler of RNA-Seq sequence alignments into potential transcripts. It uses a novel network flow algorithm as well as an optional de novo assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Its input can include not only the alignments of raw reads used by other transcript assemblers, but also alignments of longer sequences that have been assembled from those reads. To identify differentially expressed genes between experiments, StringTie's output can be processed either by the Cuffdiff or Ballgown programs.

This package implements an algorithm which increases the number of simultaneously measurable markers and in this way helps with study of the immune responses. Thus, the present algorithm, named CytoBackBone, allows combining phenotypic information of cells from different cytometric profiles obtained from different cytometry panels. This computational approach is based on the principle that each cell has its own phenotypic and functional characteristics that can be used as an identification card. CytoBackBone uses a set of predefined markers, that we call the backbone, to define this identification card. The phenotypic information of cells with similar identification cards in the different cytometric profiles is then merged.

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.

This package aims to produce high-quality genome browser tracks that are highly customizable. Currently, it is possible to plot: bigwig, bed (many options), bedgraph, links (represented as arcs), and Hi-C matrices. pyGenomeTracks can make plots with or without Hi-C data.

This is a package providing efficient operations for single cell ATAC-seq fragments and RNA counts matrices. It is interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.

This package is intended to help users to efficiently analyze genomic data resulting from various experiments.