Abstract

Functional enrichment analysis is an analytical method to extract biological insights from gene expression data, popularized by the ever-growing application of high-throughput techniques. Typically, expression profiles are generated for hundreds to thousands of genes/proteins from samples belonging to two experimental groups, and after ad-hoc statistical tests, researchers are left with lists of statistically significant entities, possibly lacking any unifying biological theme. Functional enrichment tackles the problem of putting overall gene expression changes into a broader biological context, based on pre-existing knowledge bases of reference: database collections of known expression regulation, relationships and molecular interactions. STRING is among the most popular tools, providing both protein–protein interaction networks and functional enrichment analysis for any given set of identifiers. For complex experimental designs, manually retrieving, interpreting, analyzing and abridging functional enrichment results is a daunting task, usually performed by hand by the average wet-biology researcher. We have developed reString, a cross-platform software that seamlessly retrieves from STRING functional enrichments from multiple user-supplied gene sets, with just a few clicks, without any need for specific bioinformatics skills. Further, it aggregates all findings into human-readable table summaries, with built-in features to easily produce user-customizable publication-grade clustermaps and bubble plots. Herein, we outline a complete reString protocol, showcasing its features on a real use-case.

Highlights

  • Functional enrichment analysis is an analytical method to extract biological insights from gene expression data, popularized by the ever-growing application of high-throughput techniques

  • In a typical experimental workflow, the abundance of mRNA transcripts or proteins are obtained for hundreds to thousands of analytes at the same time, and their increased or decreased abundance with respect to a reference experimental group is evaluated with ad-hoc statistical tools

  • Data visualization was performed with matplotlib[23] and seaborn[24] libraries for the Python programming language. reString can be automatically installed via pip, the Python package installer, downloaded from GitHub or from the Python package Index, PyPI

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Summary

Introduction

Functional enrichment analysis is an analytical method to extract biological insights from gene expression data, popularized by the ever-growing application of high-throughput techniques. We have developed reString, a software that leverages STRING APIs to automatically perform functional enrichment analysis on multiple user-provided gene/protein lists, rendering the handling of even the most complicate experimental layout a lightweight task.

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