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Python-airr provides a library by the AIRR community to for describing, reporting, storing, and sharing adaptive immune receptor repertoire (AIRR) data, such as sequences of antibodies and T cell receptors (TCRs).
Forester is a collection of Java libraries for phylogenomics and evolutionary biology research. It includes support for reading, writing, and exporting phylogenetic trees.
This package provides a client for the OmniPath web service and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources such as BioPlex, ConsensusPathDB, EVEX, Gene Ontology, Guide to Pharmacology (IUPHAR/BPS), Harmonizome, HTRIdb, Human Phenotype Ontology, InWeb InBioMap, KEGG Pathway, Pathway Commons, Ramilowski et al. 2015, RegNetwork, ReMap, TF census, TRRUST and Vinayagam et al. 2011. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data, and its R implementation nichenetr.
Splicekit is a modular platform for splicing analysis from short-read RNA-seq datasets. The platform also integrates pybio for genomic operations and scanRBP for RNA-protein binding studies. The whole analysis is self-contained (one single directory) and the platform is written in Python, in a modular way.
This package Copynumber KAryotyping of Tumors infers genomic copy number and subclonal structure of human tumors using integrative Bayesian approaches to identify genome-wide aneuploidy at 5MB resolution in single cells data. It separates tumor cells and tumor subclones from normal cells using high-throughput sc-RNAseq data.
Pyani provides a package and script for calculation of genome-scale average nucleotide identity.
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.
CellBender is a software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data.
This is an R package to build generic .loom files aligning with the default naming convention of the .loom format and to integrate other data types e.g.: regulons (SCENIC), clusters from Seurat, trajectory information... The package can also be used to extract data from .loom files.
This package provides tools for handling BAM, SAM, Tabix, bgzf, CRAM, CSIv1, CSIv2 and FAI files.
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:
Simple, easy to use pipeline to screen genes in Genome-wide CRISPR-Cas9 Knockout experiments;
High sensitivity and low false discovery rate;
Fully utilize the screening data by performing both positive and negative screening in one dataset;
Provide statistical evaluation in genes, sgRNAs and pathways;
Require as few as 2 samples;
Identify cell-type specific targets;
A set of visualization features that generate publication standard figures.
dnaio is a Python library for fast parsing of FASTQ and also FASTA files. The code was previously part of the cutadapt tool.
Bíogo is a bioinformatics library for the Go language.
BayesPrism includes deconvolution and embedding learning modules. The deconvolution module models a prior from cell type-specific expression profiles from scRNA-seq to jointly estimate the posterior distribution of cell type composition and cell type-specific gene expression from bulk RNA-seq expression of tumor samples. The embedding learning module uses Expectation-maximization (EM) to approximate the tumor expression using a linear combination of malignant gene programs while conditional on the inferred expression and fraction of non-malignant cells estimated by the deconvolution module.
BEDOPS is a suite of tools to address common questions raised in genomic studies---mostly with regard to overlap and proximity relationships between data sets. It aims to be scalable and flexible, facilitating the efficient and accurate analysis and management of large-scale genomic data.
BEDOPS provides tools that perform highly efficient and scalable Boolean and other set operations, statistical calculations, archiving, conversion and other management of genomic data of arbitrary scale. Tasks can be easily split by chromosome for distributing whole-genome analyses across a computational cluster.
This package provides an RNA-seq workflow for differential transcript usage (DTU) following Salmon quantification. This workflow performs a DTU analysis on simulated data. It also shows how to use stageR to perform two-stage testing of DTU, a statistical framework to screen at the gene level and then confirm which transcripts within the significant genes show evidence of DTU.
This package aims to produce high-quality genome browser tracks that are highly customizable. Currently, it is possible to plot: bigwig, bed (many options), bedgraph, links (represented as arcs), and Hi-C matrices. pyGenomeTracks can make plots with or without Hi-C data.
Millefy is a tool for visualizing read coverage of scRNA-seq(single-cell RNA sequencing) datasets in genomic contexts. By dynamically and automatically reorder single cells based on locus-specific pseudo time, Millefy highlights cell-to-cell heterogeneity in read coverage of scRNA-seq data.
SeuratWrappers is a collection of community-provided methods and extensions for Seurat, curated by the Satija Lab at NYGC. These methods comprise functionality not presently found in Seurat, and are able to be updated much more frequently.
CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts.
Mudata is a Python package for multi-omics data analysis. It is designed to provide functionality to load, process, and store multimodal omics data.
The gdc-client provides several convenience functions over the GDC API which provides general download/upload via HTTPS.
MACS is an implementation of a ChIP-Seq analysis algorithm for identifying transcript factor binding sites named Model-based Analysis of ChIP-Seq (MACS). MACS captures the influence of genome complexity to evaluate the significance of enriched ChIP regions and it improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation.
Ngs-bits (Next-Generation Sequencing) is collection of short-read and long-read sequencing tools for diagnostics.