ShinyBioHEAT

The goal of ShinyBioHEAT is to provide a shiny interface to allow users to predict phenotype driver gene in lab evolved E. coli and B. subtilis using Evolutionary Action. It currently supports 3 reference genomes including: E. coli MG1655, E.coli REL606 and B. subtilis 168. A live version of the application is hosted at http://bioheat.lichtargelab.org. The application contains 3 modules:

1. Driver Gene Analysis: Two orthogonal approaches, EA integration and Frequency based method, are used to identify phenotype driven genes.
2. Quick EA search: EA (Evolutionary Action) scores predicts the functional impact of protein coding mutations (ref). This module allows user to quickly search the EA score of any given mutations in the selected reference genome.
3. Structure Viewer: Mapping mutation data and EA/ET scores to AlphaFold structures.

Installation

You can install the development version of ShinyBioHEAT like so:

devtools::install_github("LichtargeLab/ShinyBioHEAT")

To load the shiny app

library(ShinyBioHEAT)
run_app()

Related References

Wang C, Govindarajan H, Katsonis P, Lichtarge O. ShinyBioHEAT: an interactive shiny app to identify phenotype driver genes in E.coli and B.subtilis. Bioinformatics. 2023 Aug 1;39(8):btad467.

Marciano DC, Wang C, Hsu TK, Bourquard T, Atri B, Nehring RB, Abel NS, Bowling EA, Chen TJ, Lurie PD, Katsonis P, Rosenberg SM, Herman C, Lichtarge O. Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli. Nat Commun. 2022 Jun 9;13(1):3189.

Katsonis P, Lichtarge O. A formal perturbation equation between genotype and phenotype determines the Evolutionary Action of protein-coding variations on fitness. Genome Res. 2014 Dec;24(12):2050-8.