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.

Grassroots DICOM (GDCM) is an implementation of the DICOM standard designed to be open source so that researchers may access clinical data directly. GDCM includes a file format definition and a network communications protocol, both of which should be extended to provide a full set of tools for a researcher or small medical imaging vendor to interface with an existing medical database.

Splicekit is a modular platform for splicing analysis from short-read RNA-seq datasets. The platform also integrates pybio for genomic operations and scanRBP for RNA-protein binding studies. The whole analysis is self-contained (one single directory) and the platform is written in Python, in a modular way.

This package implements the custom CRAM codecs used for "EXTERNAL" block types. These consist of two variants of the rANS codec (8-bit and 16-bit renormalisation, with run-length encoding and bit-packing also supported in the latter), a dynamic arithmetic coder, and custom codecs for name/ID compression and quality score compression derived from fqzcomp.

This package provides a new batch effect correction method based on Projection to Latent Structures Discriminant Analysis named “PLSDA-batch” to correct data prior to any downstream analysis. PLSDA-batch estimates latent components related to treatment and batch effects to remove batch variation. The method is multivariate, non-parametric and performs dimension reduction. Combined with centered log ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far.

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 is a Python-based command line interface for processing .bam files with mitochondrial reads and generating high-quality heteroplasmy estimation from sequencing data. The mgatk package places a special emphasis on mitochondrial genotypes generated from single-cell genomics data, primarily mtscATAC-seq, but is generally applicable across other assays.

This is an R package that integrates the installation of doublet-detection methods. In addition, this tool is used for execution and benchmark of those eight mentioned methods.

Jellyfish is a tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence. Jellyfish is a command-line program that reads FASTA and multi-FASTA files containing DNA sequences. It outputs its k-mer counts in a binary format, which can be translated into a human-readable text format using the jellyfish dump command, or queried for specific k-mers with jellyfish query.

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 phylo module provides a biojava interface layer to the forester phylogenomics library for constructing phylogenetic trees.

Pybiomart provides a simple pythonic interface to biomart.

MAGIC is an interactive tool to impute missing values in single-cell sequencing data and to restore the structure of the data. It also provides data pre-processing functionality such as dimensionality reduction and gene expression visualization.

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.

PhyML is a software package that uses modern statistical approaches to analyse alignments of nucleotide or amino acid sequences in a phylogenetic framework. The main tool in this package builds phylogenies under the maximum likelihood criterion. It implements a large number of substitution models coupled with efficient options to search the space of phylogenetic tree topologies. codePhyREX fits the spatial-Lambda-Fleming-Viot model to geo-referenced genetic data. This model is similar to the structured coalescent but assumes that individuals are distributed along a spatial continuum rather than discrete demes. PhyREX can be used to estimate population densities and rates of dispersal. Its output can be processed by treeannotator (from the BEAST package) as well as SPREAD.

This package provides a Python module creating/accessing GTF-based interval trees with associated meta-data. It is primarily used by the deeptools package.

This package is a rasterization preprocessing framework that aggregates cellular information into spatial pixels to reduce resource requirements for spatial omics data analysis. SEraster reduces the number of points in spatial omics datasets for downstream analysis through a process of rasterization where single cells gene expression or cell-type labels are aggregated into equally sized pixels based on a user-defined resolution. SEraster can be incorporated with other packages to conduct downstream analyses for spatial omics datasets, such as detecting spatially variable genes.

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 package provides basic routines for estimation of gene-specific transcriptional derivatives and visualization of the resulting velocity patterns.

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).

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 provides data structures, algorithms and educational resources for bioinformatics.

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

This package provides a library and collection of scripts to work with Illumina paired-end data (for CASAVA 1.8+).