How to understand the cell by breaking it: network analysis of gene perturbation screens

TL;DR

This paper reviews network analysis methods for interpreting high-throughput gene perturbation screens, focusing on inferring cellular wiring diagrams from phenotypic data at various dimensionalities.

Contribution

It provides a comprehensive overview of current approaches to analyze perturbation screens using network inference from phenotypic data, integrating multiple data sources.

Findings

Methods for analyzing low-dimensional phenotypes like viability or reporter activity.

Approaches for high-dimensional phenotypes such as transcriptome or proteome changes.

Strategies for integrating phenotypic data with other data sources for network inference.

Abstract

Modern high-throughput gene perturbation screens are key technologies at the forefront of genetic research. Combined with rich phenotypic descriptors they enable researchers to observe detailed cellular reactions to experimental perturbations on a genome-wide scale. This review surveys the current state-of-the-art in analyzing perturbation screens from a network point of view. We describe approaches to make the step from the parts list to the wiring diagram by using phenotypes for network inference and integrating them with complementary data sources. The first part of the review describes methods to analyze one- or low-dimensional phenotypes like viability or reporter activity; the second part concentrates on high-dimensional phenotypes showing global changes in cell morphology, transcriptome or proteome.