Publication-quality network visualisations in python
Generate high quality, publication ready visualizations for single cell transcriptomics data.
Enables cellxgene to generate violin, stacked violin, stacked bar, heatmap, volcano, embedding, dot, track, density, 2D density, sankey and dual-gene plot in high-resolution SVG/PNG format. It also performs differential gene expression analysis and provides a Command Line Interface (CLI) for advanced users to perform analysis using python and R.
Fast, modular and reproducible generation of publication quality scientific figures and movies with only a few lines of code.
Visualize and print volumetric brain data
The proplot examples translated to Julia using PyCall.jl and PyPlot.jl.
A Python package with a plotting class and routines for publication-ready graphics
RNAlytics: A Shiny-based web application for RNA-Seq analysis, offering differential expression, KEGG/GO enrichment, and interactive visualizations (PCA, Volcano, Heatmap, Gene Count). Built with R 4.4.3, it provides a user-friendly platform for researchers to explore genomic data. Deployable on Shiny Server for full control and scalability.
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