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

This package provides Python bindings for spoa, a C++ implementation of the partial order alignment (POA) algorithm (as described in 10.1093/bioinformatics/18.3.452) which is used to generate consensus sequences

Ritornello is a ChIP-seq peak calling algorithm based on signal processing that can accurately call binding events without the need to do a pair total DNA input or IgG control sample. It has been tested for use with narrow binding events such as transcription factor ChIP-seq.

This package lets you read and write files in Generic Feature Format (GFF) with Biopython integration.

The package graph implements graph manipulation functions.

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.

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 program searches for and removes remnant adapter sequences from High-Throughput Sequencing (HTS) data and (optionally) trims low quality bases from the 3' end of reads following adapter removal. AdapterRemoval can analyze both single end and paired end data, and can be used to merge overlapping paired-ended reads into (longer) consensus sequences. Additionally, the AdapterRemoval may be used to recover a consensus adapter sequence for paired-ended data, for which this information is not available.

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

Express Beta Diversity (EBD) calculates ecological beta diversity (dissimilarity) measures between biological communities. EBD implements a variety of diversity measures including those that make use of phylogenetic similarity of community members.

This package provides several programs that perform operations on SAM/BAM files. All of these programs are built into a single executable called bam.

Kraken is a taxonomic sequence classifier that assigns taxonomic labels to DNA sequences. Kraken examines the k-mers within a query sequence and uses the information within those k-mers to query a database. That database maps k-mers to the lowest common ancestor (LCA) of all genomes known to contain a given k-mer.

pySCENIC is a Python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

This package allows building the hierarchy of domains starting from Hi-C data. Each hierarchical level is identified by a minimum value of physical insulation between neighboring domains.

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

This is an R package that integrates the installation of doublet-detection methods. In addition, this tool is used for execution and benchmark of those eight mentioned methods.

METAL is a tool for meta-analysis genomewide association scans. METAL can combine either test statistics and standard errors or p-values across studies (taking sample size and direction of effect into account). METAL analysis is a convenient alternative to a direct analysis of merged data from multiple studies. It is especially appropriate when data from the individual studies cannot be analyzed together because of differences in ethnicity, phenotype distribution, gender or constraints in sharing of individual level data imposed. Meta-analysis results in little or no loss of efficiency compared to analysis of a combined dataset including data from all individual studies.

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.

Mosaicatcher counts Strand-seq reads and classifies strand states of each chromosome in each cell using a Hidden Markov Model.

PySnpTools is a library for reading and manipulating genetic data. It can, for example, efficiently read whole PLINK *.bed/bim/fam files or parts of those files. It can also efficiently manipulate ranges of integers using set operators such as union, intersection, and difference.

This package provides necessary tools for the analysis of the genomic interaction data stored in .cool format. This collection of tools includes operations like compartment, insulation or peak calling.

This package converts the output of the Sailfish and Salmon RNA-seq quantification tools so that it can be used with the Sleuth differential analysis package.

CodeAndRoll2 is a set of more than 130 productivity functions. These functions are used by MarkdownReports, ggExpress, and SeuratUtils.

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.