freeCount - Coding Free Framework for Guided Count Data Analysis

DA

Differential Expression Analysis - Clustering, exact tests, GLM analysis with edgeR

FA

Functional Analysis - Over-representation and enrichment analysis with topGO

SO

Set Operations - Venn diagrams and subset extraction with ggVennDiagram

About freeCount

The freeCount analysis framework provides a modular set of tools and tutorials for a structured approach to biological count data analysis. Users are guided through data assessment, processing and analysis.

DA: Differential Expression Analysis with clustering, exact tests, and GLMs
FA: Functional Analysis using Fisher's exact and Kolmogorov-Smirnov tests
SO: Set Operations for comparing gene sets with Venn diagrams

Citation: Elizabeth Mae Brooks, Sheri A Sanders, and Michael E Pfrender. 2024. FreeCount: A Coding Free Framework for Guided Count Data Visualization and Analysis. In Practice and Experience in Advanced Research Computing 2024: Human Powered Computing (PEARC '24). Association for Computing Machinery, New York, NY, USA, Article 37, 1–4. https://doi.org/10.1145/3626203.3670605