Abstract
High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2).
Highlights
In vitro functional studies using RNA interference (RNAi) screening libraries have recently dramatically improved in throughput speed, quality and genomic coverage with the advent of powerful biochemical methods for perturbing genes transcriptional mechanisms
We present a new method called high-throughput screenings (HTS)-Net, a substantial adaptation and improvement of the Interactome-Transcriptome Integration (ITI) algorithm [7], that is tailored for RNAi screenings network analyses
We are proposing the HTS-Net pipeline for the network analysis of large-scale RNAi screenings adapted to various experimental settings
Summary
In vitro functional studies using RNA interference (RNAi) screening libraries have recently dramatically improved in throughput speed, quality and genomic coverage with the advent of powerful biochemical methods for perturbing genes transcriptional mechanisms. RNAi screenings and the construction of associated genome-wide small interfering RNA (siRNA) libraries allowed a refined understanding of gene function at the genomic scale. The improvement of analytical microscopy and the development of high-content screening tools (HCS) have allowed scientists to access multi-parametric analyses at a single-cell level. Together, these technologies charted the way to high-throughput screenings (HTS) with sophisticated cellular read-outs at the genomic scale. The hits detected by such assays can quickly link single proteins to a studied phenotype/function [1][2].
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