Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats, including optionally gzip'ed BED, GFF, SAM, VCF, FASTA/Q and TAB-delimited formats with column names. It also adds a few built-in functions and a command line option to use TAB as the input/output delimiter. When the new functionality is not used, bioawk is intended to behave exactly the same as the original BWK awk.

Tombo is a suite of tools primarily for the identification of modified nucleotides from nanopore sequencing data. Tombo also provides tools for the analysis and visualization of raw nanopore signal.

PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph representing phenotypic similarities between cells and then identifying communities in this graph.

This package contains a multicore Barnes-Hut implementation of the t-SNE algorithm. The implementation is described here: http://lvdmaaten.github.io/publications/papers/JMLR_2014.pdf.

The IDR (Irreproducible Discovery Rate) framework is a unified approach to measure the reproducibility of findings identified from replicate experiments and provide highly stable thresholds based on reproducibility.

Salmon is a program to produce highly-accurate, transcript-level quantification estimates from RNA-seq data. Salmon achieves its accuracy and speed via a number of different innovations, including the use of lightweight alignments (accurate but fast-to-compute proxies for traditional read alignments) and massively-parallel stochastic collapsed variational inference.

The BIOM file format is designed to be a general-use format for representing counts of observations e.g. operational taxonomic units, KEGG orthology groups or lipid types, in one or more biological samples e.g. microbiome samples, genomes, metagenomes.

This package provides an R API and htmlwidget facilitating interactive visualization of spatial single-cell data with Vitessce. The R API contains classes and functions for loading single-cell data stored in compatible on-disk formats. The htmlwidget is a wrapper around the Vitessce JavaScript library and can be used in the Viewer tab of RStudio or Shiny apps.

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.

This package conducts batch effects removal from a taxa read count table by a conditional quantile regression method. The distributional attributes of microbiome data - zero-inflation and over-dispersion, are simultaneously considered.

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

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.

The Maxprobes package collects cross-reactive probes of Illumina methylation array 450K and EPIC/850K.

dnaio is a Python library for fast parsing of FASTQ and also FASTA files. The code was previously part of the cutadapt tool.

iVar is a computational package that contains functions broadly useful for viral amplicon-based sequencing.

SNAP is a fast and accurate aligner for short DNA reads. It is optimized for modern read lengths of 100 bases or higher, and takes advantage of these reads to align data quickly through a hash-based indexing scheme.

Phylogenetic Analysis with Space/Time models (PHAST) is a collection of command-line programs and supporting libraries for comparative and evolutionary genomics. Best known as the search engine behind the Conservation tracks in the University of California, Santa Cruz (UCSC) Genome Browser, PHAST also includes several tools for phylogenetic modeling, functional element identification, as well as utilities for manipulating alignments, trees and genomic annotations.

This package provides a method to detect and enable removal of doublets from single-cell RNA-sequencing.

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.

Prodigal runs smoothly on finished genomes, draft genomes, and metagenomes, providing gene predictions in GFF3, Genbank, or Sequin table format. It runs quickly, in an unsupervised fashion, handles gaps, handles partial genes, and identifies translation initiation sites.

This package computes informative enrichment and quality measures for ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq data. It can also be used to obtain robust estimates of the predominant fragment length or characteristic tag shift values in these assays.

python-scanrbp is a Python package that provides the scanRBP tool that loads RNA-protein binding motif PWM and computes the log-odds scores for all the loaded RBPs across a given genomic sequence and draws a heatmap of the scores.

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.

PLINK is a whole genome association analysis toolset, designed to perform a range of basic, large-scale analyses in a computationally efficient manner. The focus of PLINK is purely on analysis of genotype/phenotype data, so there is no support for steps prior to this (e.g. study design and planning, generating genotype or CNV calls from raw data). Through integration with gPLINK and Haploview, there is some support for the subsequent visualization, annotation and storage of results.