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.

The goal of bedtorch is to provide a fast BED file manipulation tool suite native in R.

This package is a library to enable flexible and scalable operations on genomic interval dataframes in Python. Bioframe enables access to a rich set of dataframe operations. Working in Python enables rapid visualization and iteration of genomic analyses. The philosophy underlying bioframe is to enable flexible operations. Instead of creating a function for every possible use-case, we encourage users to compose functions to achieve their goals.

Logomaker is a Python package for generating publication-quality sequence logos. Logomaker can generate both standard and highly customized logos illustrating the properties of DNA, RNA, or protein sequences. Logos are rendered as vector graphics embedded within native matplotlib Axes objects, making them easy to style and incorporate into multi-panel figures.

This package provides procedures for efficient pythonic random access to fasta subsequences.

The SCDE package implements a set of statistical methods for analyzing single-cell RNA-seq data. SCDE fits individual error models for single-cell RNA-seq measurements. These models can then be used for assessment of differential expression between groups of cells, as well as other types of analysis. The SCDE package also contains the pagoda framework which applies pathway and gene set overdispersion analysis to identify aspects of transcriptional heterogeneity among single cells.

This is an R package to query and expand DisGeNET data, and to visualize the results within R framework. The disgenet2r package is designed to retrieve data from DisGeNET v6.0 (Jan, 2019).

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.

Screed parses FASTA and FASTQ files and generates databases. Values such as sequence name, sequence description, sequence quality and the sequence itself can be retrieved from these databases.

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.

This package provides a converter between .hic files (from juicer) and single-resolution or multi-resolution .cool files (for cooler). Both hic and cool files describe Hi-C contact matrices.

GSEApy is a Python/Rust implementation for GSEA and wrapper for Enrichr. GSEApy can be used for RNA-seq, ChIP-seq, Microarray data. It can be used for convenient GO enrichment and to produce publication quality figures in Python.

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.

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. MetaBAT is an automated metagenome binning software, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency.

Picard is a set of Java command line tools for manipulating high-throughput sequencing (HTS) data and formats. Picard is implemented using the HTSJDK Java library to support accessing file formats that are commonly used for high-throughput sequencing data such as SAM, BAM, CRAM and VCF.

This package provides data for the book "Computational Genomics with R".

MUSIC is an algorithm for identification of enriched regions at multiple scales in the read depth signals from ChIP-Seq experiments.

This package provides a Variant Effect Predictor, which predicts the functional effects of genomic variants. It also provides Haplosaurus, which uses phased genotype data to predict whole-transcript haplotype sequences, and Variant Recoder, which translates between different variant encodings.

HMMER is used for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs).

Bio::Kseq provides ruby bindings to the kseq.h FASTA and FASTQ parsing code. It provides a fast iterator over sequences and their quality scores.

Pyani provides a package and script for calculation of genome-scale average nucleotide identity.

This package provides a library and collection of scripts to work with Illumina paired-end data (for CASAVA 1.8+).

This is a Ligand-Receptor inference framework. The framework enables the use of any LR method with any resources.

PiGx BSseq is a data processing pipeline for raw fastq read data of bisulfite experiments; it produces reports on aggregate methylation and coverage and can be used to produce information on differential methylation and segmentation.