TopHat is a fast splice junction mapper for nucleotide sequence reads produced by the RNA-Seq method. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons.

This package addresses the challenge of handling large amounts of data that are now routinely generated from DNA sequencing centers. deepTools contains useful modules to process the mapped reads data for multiple quality checks, creating normalized coverage files in standard bedGraph and bigWig file formats, that allow comparison between different files. Finally, using such normalized and standardized files, deepTools can create many publication-ready visualizations to identify enrichments and for functional annotations of the genome.

This package provides an accurate VCF/GFF3/GTF LiftOver tool for new genome assemblies.

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

LIANA provides a number of methods and resource for ligand-receptor interaction inference from scRNA-seq data.

Circe is a Python package for inferring co-accessibility networks from single-cell ATAC-seq data, using skggm for the graphical lasso and python-scanpy for data processing.

The loom file format is an efficient format for very large omics datasets, consisting of a main matrix, optional additional layers, a variable number of row and column annotations. Loom also supports sparse graphs. This library makes it easy to work with .loom files for single-cell RNA-seq data.

This package lets you perform unsupervised clustering of amplicon sequencing data in microbiome studies with the Dirichlet-tree Multinomial Mixtures.

This package provides Python bindings for lib2bit to access 2bit files with Python.

This package implements methods for batch correction and integration of scRNA-seq datasets, based on the Seurat anchor-based integration framework. In particular, STACAS is optimized for the integration of heterogeneous datasets with only limited overlap between cell sub-types (e.g. TIL sets of CD8 from tumor with CD8/CD4 T cells from lymphnode), for which the default Seurat alignment methods would tend to over-correct biological differences. The 2.0 version of the package allows the users to incorporate explicit information about cell-types in order to assist the integration process.

The subread package contains the following tools: subread aligner, a general-purpose read aligner; subjunc aligner: detecting exon-exon junctions and mapping RNA-seq reads; featureCounts: counting mapped reads for genomic features; exactSNP: a SNP caller that discovers SNPs by testing signals against local background noises.

This package builds on Seurat's Doheatmap function code to produce a heatmap from a Seurat object with multiple annotation bars.

Fastp is a tool designed to provide fast all-in-one preprocessing for FastQ files. This tool has multi-threading support to afford high performance.

Cyvcf2 is a Cython wrapper around htslib built for fast parsing of Variant Call Format (VCF) files.

Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by the Prokka program) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. Roary is not intended for metagenomics or for comparing extremely diverse sets of genomes.

DNA Features Viewer is a Python library to visualize DNA features, e.g. from GenBank or Gff files, or Biopython SeqRecords.

CoolBox is a toolkit for visual analysis of genomics data. It aims to be highly compatible with the Python ecosystem, easy to use and highly customizable with a well-designed user interface. It can be used in various visualization situations, for example, to produce high-quality genome track plots or fetch common used genomic data files with a Python script or command line, interactively explore genomic data within Jupyter environment or web browser.

PSIplot is an R package for generating plots of percent spliced-in (PSI) values of alternatively-spliced exons that were computed by vast-tools, an RNA-Seq pipeline for alternative splicing analysis. The plots are generated using ggplot2.

Cooler is a support library for a sparse, compressed, binary persistent storage format, called cool, used to store genomic interaction data, such as Hi-C contact matrices.

TSIS is used for detecting transcript isoform switches in time-series data. Transcript isoform switches occur when a pair of alternatively spliced isoforms reverse the order of their relative expression levels. TSIS characterizes the transcript switch by defining the isoform switch time-points for any pair of transcript isoforms within a gene. In addition, this tool describes the switch using five different features or metrics. Also it filters the results with user’s specifications and visualizes the results using different plots for the user to examine further details of the switches.

PAIRADISE is a method for detecting allele-specific alternative splicing (ASAS) from RNA-seq data. Unlike conventional approaches that detect ASAS events one sample at a time, PAIRADISE aggregates ASAS signals across multiple individuals in a population. By treating the two alleles of an individual as paired, and multiple individuals sharing a heterozygous SNP as replicates, PAIRADISE formulates ASAS detection as a statistical problem for identifying differential alternative splicing from RNA-seq data with paired replicates.

This package is a client implementation of the GA4GH htsget protocol. It provides a simple and reliable way to retrieve genomic data from servers supporting the protocol.

This package is used for demultiplexing single-cell sequencing experiments of pooled cells. These cells are labeled with barcode oligonucleotides. The package implements methods to fit regression mixture models for a probabilistic classification of cells, including multiplet detection. Demultiplexing error rates can be estimated, and methods for quality control are provided.

This tool offers a pipeline for inferring gene expression programs from scRNA-Seq. It takes a count matrix (N cells X G genes) as input and produces a (K x G) matrix of gene expression programs (GEPs) and a (N x K) matrix specifying the usage of each program for each cell in the data.