graphsim — Peer-reviewed • Rank 14.3 • Science 98%

graphsim: An R package for simulating gene expression data from graph structures of biological pathways - Published in JOSS (2020)

BASiCS • Rank 17.6 • Science 59%

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data. This is an unstable experimental version. Please see http://bioconductor.org/packages/BASiCS/ for the official release version

GeneTonic • Rank 16.5 • Science 59%

Enjoy your transcriptomic data and analysis responsibly - like sipping a cocktail

psichomics • Rank 15.8 • Science 59%

Interactive R package to quantify, analyse and visualise alternative splicing

myTAI • Rank 12.0 • Science 59%

Evolutionary Transcriptomics with R

https://github.com/broadinstitute/tangram • Rank 16.0 • Science 54%

Spatial alignment of single cell transcriptomic data.

comparative_ml_analysis_bioinformatics • Rank 0.7 • Science 67%

A comprehensive analysis of gene expression data using machine learning techniques in Python and R, focusing on predictive modeling and data visualization

cTRAP • Rank 13.2 • Science 49%

Identification of candidate causal perturbations from differential gene expression data

iSEE • Rank 19.0 • Science 36%

R/shiny interface for interactive visualization of data in SummarizedExperiment objects

fishpond • Rank 16.4 • Science 33%

Differential expression and allelic analysis, nonparametric statistics

volcano3d • Rank 15.7 • Science 23%

An R package to plot interactive three-way differential expression analysis

pymrmr • Rank 13.7 • Science 23%

Python3 binding to mRMR Feature Selection algorithm (currently not maintained)

NBAMSeq • Rank 11.5 • Science 23%

Negative Binomial Additive Model for RNASeq Data

stanmf • Rank 6.8 • Science 23%

A python implementation of Stability NMF

rnaagecalc • Rank 3.5 • Science 23%

A multi-tissue transcriptional age calculator

vidger • Rank 14.9 • Science 10%

Make rapid visualizations of RNA-seq data in R

scinsight • Rank 9.6 • Science 10%

Matrix factorization model for interpreting single cell gene expression in biologically heterogeneous data

pathcore-t • Rank 3.8 • Science 13%

Methods to build a network of pathway co-occurrence relationships out of expression signatures extracted from transcriptomic compendia.

BioGA • Science 49%

Optimize high-throughput genomic data analysis using genetic algorithms for efficient pattern discovery and feature selection.

helical • Science 57%

A framework for state-of-the-art pre-trained bio foundation models on genomics and transcriptomics modalities.

eqtl-mapping • Science 26%

diane • Science 57%

Dashboard for the Inference and Analysis of Networks from Expression data

https://github.com/ahmedmoustafa/gene-expression-datasets • Science 10%

Collection of gene expression datasets

ccbcge • Science 44%

Python package to access Breast Cancer Gene Expression data

https://github.com/bvieth/powsimr • Science 13%

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

https://github.com/bgeedb/bgee_web • Science 49%

React code of the Bgee frontend

refinebio-examples • Science 44%

Example workflows for refine.bio data

https://github.com/bgeedb/bgee_apps • Science 49%

Source code of the Java Bgee applications

ClusterGVis • Science 26%

One-step to Cluster and Visualize Gene Expression Matrix

https://github.com/bgeedb/bgee_pipeline • Science 49%

Source code of the Bgee pipeline used to build the Bgee database