Cell2cell is a Python library for cell communication analysis. This is a method to calculate, visualize and analyze communication between cell types. Cell2cell is suitable for single-cell RNA sequencing (scRNA-seq) data.

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads.

This package provides a GFF/GTF file parsing utility providing format conversions, region filtering, FASTA sequence extraction and more.

The WiggleTools package allows genomewide data files to be manipulated as numerical functions, equipped with all the standard functional analysis operators (sum, product, product by a scalar, comparators), and derived statistics (mean, median, variance, stddev, t-test, Wilcoxon's rank sum test, etc).

This is a drop-in replacement for the IlluminaHumanMethylationEPIC package. It utilizes a Manifest based on 1.0B5 annotation. As of version 0.3.0, the IlluminaHumanMethylationEPIC package still employs the 1.0B2 annotation manifest. A corresponding annotation package, IlluminaHumanMethylationEPICanno.ilm10b5.hg38, is available to ensure proper annotation. The decision to maintain the same name is due to complications in downstream processing caused by array name lookup in certain preprocessing options.

Pybiomart provides a simple pythonic interface to biomart.

SNAP is a fast and accurate aligner for short DNA reads. It is optimized for modern read lengths of 100 bases or higher, and takes advantage of these reads to align data quickly through a hash-based indexing scheme.

MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of gene regulation, providing a quantitative summary of the temporal relationship between epigenomic and transcriptomic changes.

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.

Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. Its features include:

1. Simple, easy to use pipeline to screen genes in Genome-wide CRISPR-Cas9 Knockout experiments;

2. High sensitivity and low false discovery rate;

3. Fully utilize the screening data by performing both positive and negative screening in one dataset;

4. Provide statistical evaluation in genes, sgRNAs and pathways;

5. Require as few as 2 samples;

6. Identify cell-type specific targets;

7. A set of visualization features that generate publication standard figures.

ctxcore is part of the SCENIC suite of tools. It provides core functions for pycisTarget and SCENIC.

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.

This package is a collection of Perl, Python, and R scripts for manipulating 3C/4C/5C/Hi-C data.

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

Hotspot is a tool for identifying informative genes (and gene modules) in a single-cell dataset. Importantly, "informative" is decided based on how well a gene's variation agrees with some cell metric---some similarity mapping between cells. Genes which are informative are those whose expression varies in similar way among cells which are nearby in the given metric.

This package provides graphical user interfaces to organize and visualize Nanopore sequencing data.

PDBFixer is designed to rectify issues in Protein Data Bank files. Its intuitive interface simplifies the process of resolving problems encountered in PDB files prior to simulation tasks.

PLINK is a whole genome association analysis toolset, designed to perform a range of basic, large-scale analyses in a computationally efficient manner. The focus of PLINK is purely on analysis of genotype/phenotype data, so there is no support for steps prior to this (e.g. study design and planning, generating genotype or CNV calls from raw data). Through integration with gPLINK and Haploview, there is some support for the subsequent visualization, annotation and storage of results.

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.

CellTypist is an automated cell type annotation tool for scRNA-seq datasets on the basis of logistic regression classifiers optimised by the stochastic gradient descent algorithm. CellTypist allows for cell prediction using either built-in (with a current focus on immune sub-populations) or custom models, in order to assist in the accurate classification of different cell types and subtypes.

The Maxprobes package collects cross-reactive probes of Illumina methylation array 450K and EPIC/850K.

Scregseg (Single-Cell REGulatory landscape SEGmentation) is a tool that facilitates the analysis of single cell ATAC-seq data by an HMM-based segmentation algorithm. Scregseg uses an HMM with Dirichlet-Multinomial emission probabilities to segment the genome either according to distinct relative cross-cell accessibility profiles or (after collapsing the single-cell tracks to pseudo-bulk tracks) to capture distinct cross-cluster accessibility profiles.

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