SurprisalAnalysis: an open-source software for information-theoretic analysis of gene expression
Year: 2024
Type: article
Abstract: Summary: SurprisalAnalysis is an open-source R package with an accompanying web-based application that utilizes Surprisal analysis to extract patterns of genes that tend to get up or down regulated as a result of a biological process. Surprisal analysis frames gene expression values in thermodynamic terms and identifies entropy-driven constraints and relevant gene weights that allow the decomposition of each gene's expression into a baseline (maximal entropy) component and one or more constraint-driven components. These components correspond to distinct biological modules or processes whose coordinated up or down regulation underlies the observed system dynamics. Availability and implementation: SurprisalAnalysis is written in R and is freely available on GitHub (https://github.com/AnniceNajafi/SurprisalAnalysis). The package is distributed under a permissive license to promote scientific collaboration and reproducibility. A web-based application with a Graphical User Interface (GUI) is hosted on https://najafiannice.shinyapps.io/surprisal_analysis_app/.
Source: Bioinformatics Advances
Author: Annice Najafi
Institution: California State Polytechnic University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,917
OpenAlex ID: W4416413468