Python scripts to find enrichment of GO terms. In addition, this package is used for processing the obo-formatted file from Gene Ontology website. The data structure is a directed acyclic graph that allows easy traversal from leaf to root.

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.

PAML (for Phylogentic Analysis by Maximum Likelihood) contains a few programs for model fitting and phylogenetic tree reconstruction using nucleotide or amino-acid sequence data.

This package implements methods to project single-cell RNA-seq data onto a reference atlas, enabling interpretation of unknown cell transcriptomic states in the the context of known, reference states.

HOMER (Hypergeometric Optimization of Motif EnRichment) is a suite of tools for Motif Discovery and next-gen sequencing analysis. It is a collection of command line programs written in Perl and C++. HOMER was primarily written as a de novo motif discovery algorithm and is well suited for finding 8-20 bp motifs in large scale genomics data. HOMER contains many useful tools for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets.

This is a package for the discovery of communities in Pore-C concatemers.

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.

CLIPper is a tool to define peaks in CLIP-seq datasets.

BSeq-sc is a bioinformatics analysis pipeline that leverages single-cell sequencing data to estimate cell type proportion and cell type-specific gene expression differences from RNA-seq data from bulk tissue samples. This is a companion package to the publication "A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure." Baron et al. Cell Systems (2016) https://www.ncbi.nlm.nih.gov/pubmed/27667365.

Psupertime is supervised pseudotime for single cell RNAseq data. It uses single cell RNAseq data, where the cells have a known ordering. This ordering helps to identify a small number of genes which place cells in that known order. It can be used for discovery of relevant genes, for identification of subpopulations, and characterization of further unknown or differently labelled data.

This package provides a package that makes it easy to implement sankey, alluvial and sankey bump plots in ggplot2.

SCENIC (Single-cell regulatory network inference and clustering) is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

ReadWriter is a set of R functions to read and write files conveniently.

A tiny C library for managing SOM (Self-Organizing Maps) neural networks.

modbedtools is a python command line tool to generate modbed files for visualization on the WashU Epigenome Browser.

GEMMA provides a standard linear mixed model resolver with application in GWAS.

This package implements scalable gene regulatory network inference using tree-based ensemble regressors.

This is a C++ wrapper around the Tabix project which abstracts some of the details of opening and jumping in tabix-indexed files.

Zarr backend for DelayedArray objects.

This package provides TagGD barcode demultiplexing utilities for Spatial Transcriptomics data.

Bloom-filter-based error correction solution for high-throughput sequencing reads (BLESS) uses a single minimum-sized bloom filter is a correction tool for genomic reads produced by Next-generation sequencing (NGS). BLESS produces accurate correction results with much less memory compared with previous solutions and is also able to tolerate a higher false-positive rate. BLESS can extend reads like DNA assemblers to correct errors at the end of reads.

Pando leverages multi-modal single-cell measurements to infer gene regulatory networks using a flexible linear model-based framework. By modeling the relationship between TF-binding site pairs with the expression of target genes, Pando simultaneously infers gene modules and sets of regulatory regions for each transcription factor.

StringTie is a fast and efficient assembler of RNA-Seq sequence alignments into potential transcripts. It uses a novel network flow algorithm as well as an optional de novo assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Its input can include not only the alignments of raw reads used by other transcript assemblers, but also alignments of longer sequences that have been assembled from those reads. To identify differentially expressed genes between experiments, StringTie's output can be processed either by the Cuffdiff or Ballgown programs.

This tool provides a Python framework to streamline genomics operations. It offers a direct interface to Ensembl genome assemblies and annotations, while also accommodating custom genomes via FASTA/GTF inputs. The primary objective of pybio is to simplify genome management. It achieves this by providing automatic download of Ensembl genome assemblies and annotation, provides Python genomic feature search and sequence retrieval from the managed genomes, STAR indexing and mapping and more.