This package wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. Conos focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes.

This package provides the headers and static library of Protocol buffers for other R packages to compile and link against.

This package implements some simple capabilities for representing and manipulating hypergraphs.

R-scape discovers RNA secondary structure consensus elements. These elements include riboswitches and ribozymes. It utilizes probabilistic modeling of sequence alignments, explicitly considering folding dependencies. The tool enables the de novo search for new structural elements and facilitates comparative analysis of known RNA families.

PyLiftover is a library for quick and easy conversion of genomic (point) coordinates between different assemblies.

This package is a Python wrapper for Aaron Quinlan's BEDtools programs, which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python.

The porechop package is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity. Porechop also supports demultiplexing of Nanopore reads that were barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid Barcoding Kit.

This package is tools for analysing intercellular and intracellular signaling from single cell RNA-seq (scRNA-seq) data.

MAFFT offers a range of multiple alignment methods for nucleotide and protein sequences. For instance, it offers L-INS-i (accurate; for alignment of <~200 sequences) and FFT-NS-2 (fast; for alignment of <~30,000 sequences).

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:

1. Simple, easy to use pipeline to screen genes in Genome-wide CRISPR-Cas9 Knockout experiments;

2. High sensitivity and low false discovery rate;

3. Fully utilize the screening data by performing both positive and negative screening in one dataset;

4. Provide statistical evaluation in genes, sgRNAs and pathways;

5. Require as few as 2 samples;

6. Identify cell-type specific targets;

7. A set of visualization features that generate publication standard figures.

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

CD-HIT is a program for clustering and comparing protein or nucleotide sequences. CD-HIT is designed to be fast and handle extremely large databases.

Megadepth is an efficient tool for extracting coverage related information from RNA and DNA-seq BAM and BigWig files. It supports reading whole-genome coverage from BAM files and writing either indexed TSV or BigWig files, as well as efficient region coverage summary over intervals from both types of files.

An interval tree can be used to efficiently find a set of numeric intervals overlapping or containing another interval. This library provides a basic implementation of an interval tree using C++ templates, allowing the insertion of arbitrary types into the tree.

SAIGE is a package for efficiently controlling for case-control imbalance and sample relatedness in single-variant assoc tests (SAIGE) and controlling for sample relatedness in region-based assoc tests in large cohorts and biobanks (SAIGE-GENE+).

BWA-PSSM is a probabilistic short genomic sequence read aligner based on the use of position specific scoring matrices (PSSM). Like many of the existing aligners it is fast and sensitive. Unlike most other aligners, however, it is also adaptible in the sense that one can direct the alignment based on known biases within the data set. It is coded as a modification of the original BWA alignment program and shares the genome index structure as well as many of the command line options.

This package generates a Miami plot with centered chromosome labels. The output is a ggplot2 object. Users can specify which data they want plotted on top vs. bottom, whether to display significance line(s), what colors to give chromosomes, and what points to label.

This package provides a simple web interface for the RNA-centric annotation system (RCAS).

This package implements bindings for h5 files that are compatible with Bioconductor S4 data structures, namely the DataFrame and DelayedArray. This allows HDF5-backed data to be easily used as data frames with arbitrary sets of columns.

ChIPKernels is an R package for building different string kernels used for DNA Sequence analysis. A dictionary of the desired kernel must be built and this dictionary can be used for determining kernels for DNA Sequences.

MuSiC is a deconvolution method that utilizes cross-subject scRNA-seq to estimate cell type proportions in bulk RNA-seq data.

The preseq package is aimed at predicting and estimating the complexity of a genomic sequencing library, equivalent to predicting and estimating the number of redundant reads from a given sequencing depth and how many will be expected from additional sequencing using an initial sequencing experiment. The estimates can then be used to examine the utility of further sequencing, optimize the sequencing depth, or to screen multiple libraries to avoid low complexity samples.

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.

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.