This package builds on Seurat's Doheatmap function code to produce a heatmap from a Seurat object with multiple annotation bars.

This package provides different statistical methods to extract biological activities from omics data within a unified framework.

This package implements scalable gene regulatory network inference using tree-based ensemble regressors.

Mudskipper is a tool for projecting genomic alignments to transcriptomic coordinates.

An interval map structure that is optimized for low memory (each interval is represented by about 3 words + whatever the cargo is) and has semantics that are appropriate for genomic intervals (namely, intervals can overlap and queries will return all matches together). It also designed to be used in two phases: a construction phase + query phase).

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

This package offers a quick and straight-forward way to explore and perform basic analysis of single cell sequencing data coming from droplet sequencing. It has been particularly tailored for Drop-seq.

BBKNN is a batch effect removal tool that can be directly used in the Scanpy workflow. It serves as an alternative to scanpy.api.pp.neighbors(), with both functions creating a neighbour graph for subsequent use in clustering, pseudotime and UMAP visualisation. If technical artifacts are present in the data, they will make it challenging to link corresponding cell types across different batches. BBKNN actively combats this effect by splitting your data into batches and finding a smaller number of neighbours for each cell within each of the groups. This helps create connections between analogous cells in different batches without altering the counts or PCA space.

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 contains the Battenberg R package for subclonal copy number estimation, as described by Nik-Zainal et al.

This package detects naive associations between omics features and metadata in cross-sectional data-sets using non-parametric tests. In a second step, confounding effects between metadata associated to the same omics feature are detected and labeled using nested post-hoc model comparison tests. The generated output can be graphically summarized using the built-in plotting function.

Pybiomart provides a simple pythonic interface to biomart.

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

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

This is an R package for pre-processing of flow and mass cytometry data. This package includes panel editing or renaming for FCS files, bead-based normalization and debarcoding.

This is a set of functions for processing raw scDam&T-seq data. scDam&T-seq is a method to simultaneously measure protein-DNA interactions and transcription from single cells (Rooijers et al., 2019). It combines a DamID-based method to measure protein-DNA interactions and an adaptation of CEL-Seq to measure transcription. The starting point of the workflow is raw sequencing data and the end result are tables of UMI-unique DamID and CEL-Seq counts.

This package infers, visualizes and analyzes the cell-cell communication networks from scRNA-seq data.

randfold computes the probability that, for a given sequence, the Minimum Free Energy (MFE) of the secondary structure is different from MFE computed with random sequences.

Ngless is a domain-specific language for next-generation sequencing (NGS) data processing.

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

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.

This package provides a collection of useful functions for working with DNA methylation micro-array data.

This package implements a bioinformatics algorithm for demultiplexing multiplexed single cell datasets. It is built on a statistical model of tag read counts derived from the physical mechanism of tag cross-contamination.

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.