Implementation of the Smith-Waterman algorithm.

The data within this package is a panel of four samples, each with 3000 cells. There are two samples which are bone marrow (BM), and two samples which are cord blood (CB).

BioRuby comes with a comprehensive set of Ruby development tools and libraries for bioinformatics and molecular biology. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO.

This is a drop-in replacement for the IlluminaHumanMethylationEPIC package. It utilizes a Manifest based on 1.0B5 annotation. As of version 0.3.0, the IlluminaHumanMethylationEPIC package still employs the 1.0B2 annotation manifest. A corresponding annotation package, IlluminaHumanMethylationEPICanno.ilm10b5.hg38, is available to ensure proper annotation. The decision to maintain the same name is due to complications in downstream processing caused by array name lookup in certain preprocessing options.

This package contains functions for the SCENT algorithm. SCENT uses single-cell multimodal data and links ATAC-seq peaks to their target genes by modeling association between chromatin accessibility and gene expression across individual single cells.

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.

This package provides a set of functions to parse and open (search query) links to genomics related and other websites for R. Useful when you want to explore e.g.: the function of a set of differentially expressed genes.

Pegasusio is a Python package for reading or writing single-cell genomics data.

MUSIC is an algorithm for identification of enriched regions at multiple scales in the read depth signals from ChIP-Seq experiments.

The Shaman package implements functions for resampling Hi-C matrices in order to generate expected contact distributions given constraints on marginal coverage and contact-distance probability distributions. The package also provides support for visualizing normalized matrices and statistical analysis of contact distributions around selected landmarks.

Mosaicatcher counts Strand-seq reads and classifies strand states of each chromosome in each cell using a Hidden Markov Model.

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.

SEEK is a computational gene co-expression search engine. SEEK provides biologists with a way to navigate the massive human expression compendium that now contains thousands of expression datasets. SEEK returns a robust ranking of co-expressed genes in the biological area of interest defined by the user's query genes. It also prioritizes thousands of expression datasets according to the user's query of interest.

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).

TADbit is a complete Python library to deal with all steps to analyze, model, and explore 3C-based data. With TADbit the user can map FASTQ files to obtain raw interaction binned matrices (Hi-C like matrices), normalize and correct interaction matrices, identify and compare the so-called Topologically Associating Domains (TADs), build 3D models from the interaction matrices, and finally, extract structural properties from the models. TADbit is complemented by TADkit for visualizing 3D models.

This package facilitates the analysis of single-cell RNA-seq UMI matrices. It does this by computing partitions of a cell similarity graph into small homogeneous groups of cells, which are defined as metacells (MCs). The derived MCs are then used for building different representations of the data, allowing matrix or 2D graph visualization forming a basis for analysis of cell types, subtypes, transcriptional gradients,cell-cycle variation, gene modules and their regulatory models and more.

This is a set of R functions that allows you to generate precise figures. This tool will create clean markdown reports about what you just discovered.

LAMMPS is a classical molecular dynamics simulator designed to run efficiently on parallel computers. LAMMPS has potentials for solid-state materials (metals, semiconductors), soft matter (biomolecules, polymers), and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale.

Aragorn identifies transfer RNA, mitochondrial RNA and transfer-messenger RNA from nucleotide sequences, based on homology to known tRNA consensus sequences and RNA structure. It also outputs the secondary structure of the predicted RNA.

Samblaster is a fast and flexible program for marking duplicates in read-id grouped paired-end SAM files. It can also optionally output discordant read pairs and/or split read mappings to separate SAM files, and/or unmapped/clipped reads to a separate FASTQ file. When marking duplicates, samblaster will require approximately 20MB of memory per 1M read pairs.

HISAT is a fast and sensitive spliced alignment program for mapping RNA-seq reads. In addition to one global FM index that represents a whole genome, HISAT uses a large set of small FM indexes that collectively cover the whole genome. These small indexes (called local indexes) combined with several alignment strategies enable effective alignment of RNA-seq reads, in particular, reads spanning multiple exons.

This package provides bioinformatic tools to align, deduplicate, reformat, filter and normalize DNA and RNA-seq data. It includes the following tools: BBMap, a short read aligner for DNA and RNA-seq data; BBNorm, a kmer-based error-correction and normalization tool; Dedupe, a tool to simplify assemblies by removing duplicate or contained subsequences that share a target percent identity; Reformat, to convert reads between fasta/fastq/scarf/fasta+qual/sam, interleaved/paired, and ASCII-33/64, at over 500 MB/s; and BBDuk, a tool to filter, trim, or mask reads with kmer matches to an artifact/contaminant file.

ParDRe is a parallel tool to remove duplicate genetic sequence reads. Duplicate reads can be seen as identical or nearly identical sequences with some mismatches. This tool lets users avoid the analysis of unnecessary reads, reducing the time of subsequent procedures with the dataset (e.g. assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters.

dRep is a Python program for rapidly comparing large numbers of genomes. dRep can also "de-replicate" a genome set by identifying groups of highly similar genomes and choosing the best representative genome for each genome set.