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Given a time series or pseudo-times series of gene expression data, we might wish to know: Do the changes in gene expression in these data exhibit directionality? Are there turning points in this directionality. Do different subsets of the data move in different directions? This package uses spherical geometry to probe these sorts of questions. In particular, if we are looking at (say) the first n dimensions of the PCA of gene expression, directionality can be detected as the clustering of points on the (n-1)-dimensional sphere.

transite is a computational method that allows comprehensive analysis of the regulatory role of RNA-binding proteins in various cellular processes by leveraging preexisting gene expression data and current knowledge of binding preferences of RNA-binding proteins.

MetaNeighbor allows users to quantify cell type replicability across datasets using neighbor voting.

This package provides users with the ability to query the Human Cell Atlas data repository for single-cell experiment data. The `projects()`, `files()`, `samples()` and `bundles()` functions retrieve summary information on each of these indexes; corresponding `*_details()` are available for individual entries of each index. File-based resources can be downloaded using `files_download()`. Advanced use of the package allows the user to page through large result sets, and to flexibly query the 'list-of-lists' structure representing query responses.

This package implements an interactive, scientific analysis pipeline for high-dimensional cytometry data built using tidy data principles. It is specifically designed to play well with both the tidyverse and Bioconductor software ecosystems, with functionality for reading/writing data files, data cleaning, preprocessing, clustering, visualization, modeling, and other quality-of-life functions. tidytof implements a "grammar" of high-dimensional cytometry data analysis.

Phantasus is a web-application for visual and interactive gene expression analysis. Phantasus is based on Morpheus – a web-based software for heatmap visualisation and analysis, which was integrated with an R environment via OpenCPU API. Aside from basic visualization and filtering methods, R-based methods such as k-means clustering, principal component analysis or differential expression analysis with limma package are supported.

Membrane Protein-Lipid Interaction Database. A large-scale experimentally validated dataset of 80685 residue-level lipid contact annotations across 4712 membrane proteins derived from PDB crystal and cryo-EM structures. Provides pre-computed binary contact labels, continuous distance values, sequence-identity-based cluster assignments, and ready-made train-validation-test splits for machine learning.

Python package for biodatafuse project.

AmsterdamUMCdb is a database of de-identified health data related to tens of thousands of intensive care unit admissions, including demographics, vital signs, laboratory tests and medications.

austraits is an R package for accessing the AusTraits Plant database and working with traits.build databases

A bioinformatics tool for viewing and calculating base modification frequencies from BAM files

Simple test framework for Nextflow pipelines

Reactr is an modularized, Snakemake workflow for automated, species-agnostic characterization of gene families from sequence to experimental design. Given a query protein sequence and NCBI taxonomy IDs (or RefSeq assembly accessions), reactr retrieves genomic data and runs comprehensive analysis across 4 integrated tiers: (1) evolutionary analysis, including homolog detection, domain-based clustering, multiple sequence alignment, and phylogenetic inference; (2) synteny and selection analysis, detecting collinear blocks and calculating Ka/Ks ratios; (3) structural and regulatory characterization, including motif discovery, chromosomal mapping, biochemical property prediction, subcellular localization prediction, and promoter analysis; and (4) experimental design tools, generating PCR primers and scored CRISPR gRNAs for lab validation. Reactr bridges computational prediction and experimental validation, thus enabling rapid transition from genomic discovery to functional studies.