FlexStat: Combinatory differentially expressed protein extraction

Abstract

Mass spectrometry-based system proteomics allows identification of dysregulated protein hubs and associated disease-related features. Obtaining differentially expressed proteins (DEPs) is the most important step of downstream bioinformatics analysis. However, the extraction of statistically significant DEPs from datasets with multiple experimental conditions or disease types through currently available tools remains a laborious task. More often such an analysis requires considerable bioinformatics expertise, making it inaccessible to researchers with limited computational analytics experience. To uncover the differences among the many conditions within the data in a user-friendly manner, here we introduce FlexStat, a web-based interface that extracts DEPs through combinatory analysis. This tool accepts a protein expression matrix as input and systematically generates DEP results for every conceivable combination of various experimental conditions or disease types. FlexStat includes a suite of robust statistical tools for data preprocessing, in addition to DEP extraction, and publication-ready visualization, which are built on established R scientific libraries in an automated manner. This analytics suite was validated in diverse public proteomic datasets to showcase its high performance of rapid and simultaneous pairwise comparisons of comprehensive data sets. FlexStat is implemented in R and is freely available at https://jglab.shinyapps.io/flexstatv1-pipeline-only/. The source code is accessible at https://github.com/kts-desilva/FlexStat/tree/main. Supplementary data are available at Bioinformatics Advances online.