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

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.

Discrover is a motif discovery method to find binding sites of nucleic acid binding proteins.

SlamDunk is a fully automated tool for automated, robust, scalable and reproducible SLAMseq data analysis. Diagnostic plotting features and a MultiQC plugin will make your SLAMseq data ready for immediate QA and interpretation.

This package provides a framework for the analysis and exploration of single-cell chromatin data. The Signac package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis.

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.

CENTIPEDE applies a hierarchical Bayesian mixture model to infer regions of the genome that are bound by particular transcription factors. It starts by identifying a set of candidate binding sites, and then aims to classify the sites according to whether each site is bound or not bound by a transcription factor. CENTIPEDE is an unsupervised learning algorithm that discriminates between two different types of motif instances using as much relevant information as possible.

This package is an integrated pipeline for large-scale phylogenetic profiling of genomes and metagenomes. PhyloPhlAn is an accurate, rapid, and easy-to-use method for large-scale microbial genome characterization and phylogenetic analysis at multiple levels of resolution. This software package can assign both genomes and MAGs to SGBs. PhyloPhlAn can reconstruct strain-level phylogenies using clade- specific maximally informative phylogenetic markers, and can also scale to very large phylogenies comprising >17,000 microbial species.

A streamgraph is a type of stacked area chart. It represents the evolution of a numeric variable for several groups. Areas are usually displayed around a central axis, and edges are rounded to give a flowing shape. This package provides an htmlwidget for building streamgraph visualizations.

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

This package provides a Python module creating/accessing GTF-based interval trees with associated meta-data. It is primarily used by the deeptools package.

This package adds 3D perspective plotting of points, paths, and line, 3D perspective axes, 3D perspective annotations, and wireframe plots.

This package provides a fast and accurate analysis toolkit for single cell ATAC-seq (Assay for transposase-accessible chromatin using sequencing). Single cell ATAC-seq can resolve the heterogeneity of a complex tissue and reveal cell-type specific regulatory landscapes. However, the exceeding data sparsity has posed unique challenges for the data analysis. This package r-snapatac is an end-to-end bioinformatics pipeline for analyzing large- scale single cell ATAC-seq data which includes quality control, normalization, clustering analysis, differential analysis, motif inference and exploration of single cell ATAC-seq sequencing data.

CrossMap is a program for conversion of genome coordinates or annotation files between different genome assemblies. It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

This package is analyzing TCR and BCR sequences using unselected RNA sequencing data, profiled from fluid and solid tissues, including tumors. TRUST4 performs de novo assembly on V, J, C genes including the hypervariable CDR3 and reports consensus contigs of BCR/TCR sequences. TRUST4 then realigns the contigs to IMGT reference gene sequences to identify the corresponding gene and CDR3 details. TRUST4 supports both single-end and paired-end bulk or single-cell sequencing data with any read length.

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.

This package is designed to improve and simplify the analysis of scRNA-seq data. It uses the Seurat object for this purpose. It provides an array of enhanced visualization tools, an integrated functional and pathway analysis pipeline, seamless integration with popular Python tools, and a suite of utility functions to aid in data manipulation and presentation.

This package is used for cell type identification in spatial transcriptomics. It also handles cell type-specific differential expression.

Bio++ is a set of C++ libraries for Bioinformatics, including sequence analysis, phylogenetics, molecular evolution and population genetics. This library provides phylogenetics-related modules.

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

Piranha is a peak-caller for genomic data produced by CLIP-seq and RIP-seq experiments. It takes input in BED or BAM format and identifies regions of statistically significant read enrichment. Additional covariates may optionally be provided to further inform the peak-calling process.

This package provides a collection of methods to extract gene programs from single-cell gene expression data using non-negative matrix factorization (NMF). GeneNMF contains functions to directly interact with the Seurat toolkit and derive interpretable gene program signatures.

The goal of anpan is to consolidate statistical methods for strain analysis. This includes automated filtering of metagenomic functional profiles, testing genetic elements for association with outcomes, phylogenetic association testing, and pathway-level random effects models.

BioJava is a project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats, reference implementations of popular algorithms, and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

This package provides the core libraries.