DoubletFinder identifies doublets by generating artificial doublets from existing scRNA-seq data and defining which real cells preferentially co-localize with artificial doublets in gene expression space. Other DoubletFinder package functions are used for fitting DoubletFinder to different scRNA-seq datasets. For example, ideal DoubletFinder performance in real-world contexts requires optimal pK selection and homotypic doublet proportion estimation. pK selection is achieved using pN-pK parameter sweeps and maxima identification in mean-variance-normalized bimodality coefficient distributions. Homotypic doublet proportion estimation is achieved by finding the sum of squared cell annotation frequencies.

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.

Trinity assembles transcript sequences from Illumina RNA-Seq data. Trinity represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes.

This package provides Python bindings to the bwa mem aligner.

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.

This library contains the genomics components of the Bio++ phylogenetics library. It is part of the Bio++ project.

Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes preprocessing, visualization, clustering, pseudotime and trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.

Biosoup is a C++ collection of header-only data structures used for storage and logging in bioinformatics tools.

EMBOSS is the "European Molecular Biology Open Software Suite". EMBOSS is an analysis package specially developed for the needs of the molecular biology (e.g. EMBnet) user community. The software automatically copes with data in a variety of formats and even allows transparent retrieval of sequence data from the web. It also provides a number of libraries for the development of software in the field of molecular biology. EMBOSS also integrates a range of currently available packages and tools for sequence analysis into a seamless whole.

SortMeRNA is a biological sequence analysis tool for filtering, mapping and OTU picking of NGS reads. The core algorithm is based on approximate seeds and allows for fast and sensitive analyses of nucleotide sequences. The main application of SortMeRNA is filtering rRNA from metatranscriptomic data.

This package offers Cython bindings and a Python interface for Prodigal. Prodigal is an ORF finder designed for both genomes and metagenomes.

This R tool infers, visualizes, and analyzes cell-cell communication networks. It supports scRNA-seq and spatially resolved transcriptomics data.

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

t-Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization of high dimensional datasets. A popular implementation of t-SNE uses the Barnes-Hut algorithm to approximate the gradient at each iteration of gradient descent. This implementation differs in these ways:

• Instead of approximating the N-body simulation using Barnes-Hut, we interpolate onto an equispaced grid and use FFT to perform the convolution.

• Instead of computing nearest neighbors using vantage-point trees, we approximate nearest neighbors using the Annoy library. The neighbor lookups are multithreaded to take advantage of machines with multiple cores.

Straw is library which allows rapid streaming of contact data from .hic files. This package provides Python bindings.

This package is designed to streamline scATAC analyses in R.

This is a Python module for analyzing cell-hashing/nucleus-hashing data. It is the demultiplexing module of Pegasus, which is used by Cumulus in the demultiplexing step.

This package is designed to improve and simplify the analysis of scRNA-seq data. It uses the Seurat object for this purpose. It provides an array of enhanced visualization tools, an integrated functional and pathway analysis pipeline, seamless integration with popular Python tools, and a suite of utility functions to aid in data manipulation and presentation.

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

BioJava is a project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats, reference implementations of popular algorithms, and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

This package provides the core libraries.

Express Beta Diversity (EBD) calculates ecological beta diversity (dissimilarity) measures between biological communities. EBD implements a variety of diversity measures including those that make use of phylogenetic similarity of community members.

Bio-vcf provides a DSL for processing the VCF format. Record named fields can be queried with regular expressions. Bio-vcf is a new generation VCF parser, filter and converter. Bio-vcf is not only very fast for genome-wide (WGS) data, it also comes with a filtering, evaluation and rewrite language and can output any type of textual data, including VCF header and contents in RDF and JSON.

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.

PiGX ChIPseq is an analysis pipeline for preprocessing, peak calling and reporting for ChIP sequencing experiments. It is easy to use and produces high quality reports. The inputs are reads files from the sequencing experiment, and a configuration file which describes the experiment. In addition to quality control of the experiment, the pipeline enables to set up multiple peak calling analysis and allows the generation of a UCSC track hub in an easily configurable manner.