Abstract
BackgroundRegulatory hotspots are genetic variations that may regulate the expression levels of many genes. It has been of great interest to find those hotspots utilizing expression quantitative trait locus (eQTL) analysis. However, it has been reported that many of the findings are spurious hotspots induced by various unknown confounding factors. Recently, methods utilizing complicated statistical models have been developed that successfully identify genuine hotspots. Next-generation Intersample Correlation Emended (NICE) is one of the methods that show high sensitivity and low false-discovery rate in finding regulatory hotspots. Even though the methods successfully find genuine hotspots, they have not been widely used due to their non-user-friendly interfaces and complex running processes. Furthermore, most of the methods are impractical due to their prohibitively high computational complexity.ResultsTo overcome the limitations of existing methods, we developed a fully automated web-based tool, referred to as NICER (NICE Renew), which is based on NICE program. First, we dramatically reduced running and installing burden of NICE. Second, we significantly reduced running time by incorporating multi-processing. Third, besides our web-based NICER, users can use NICER on Google Compute Engine and can readily install and run the NICER web service on their local computers. Finally, we provide different input formats and visualizations tools to show results. Utilizing a yeast dataset, we show that NICER can be successfully used in an eQTL analysis to identify many genuine regulatory hotspots, for which more than half of the hotspots were previously reported elsewhere.ConclusionsEven though many hotspot analysis tools have been proposed, they have not been widely used for many practical reasons. NICER is a fully-automated web-based solution for eQTL mapping and regulatory hotspots analysis. NICER provides a user-friendly interface and has made hotspot analysis more viable by reducing the running time significantly. We believe that NICER will become the method of choice for increasing power of eQTL hotspot analysis.
Highlights
Regulatory hotspots are genetic variations that may regulate the expression levels of many genes
It is impractical to run Next-generation Intersample Correlation Emended (NICE) on real datasets, as most of the expression quantitative trait locus (eQTL) datasets contain hundreds of thousands of Single-nucleotide polymorphisms (SNP) (Single Nucleotide Polymorphisms), and hotspot analysis tools such as NICE use very complicated statistical models
We show that NICER can be successfully used in an eQTL analysis to identify 29 genuine regulatory hotspots, of which 17 were previously reported elsewhere
Summary
To overcome the limitations of existing methods, we developed a fully automated web-based tool, referred to as NICER (NICE Renew), which is based on NICE program. We dramatically reduced running and installing burden of NICE. We significantly reduced running time by incorporating multi-processing. Besides our web-based NICER, users can use NICER on Google Compute Engine and can readily install and run the NICER web service on their local computers. We provide different input formats and visualizations tools to show results. We show that NICER can be successfully used in an eQTL analysis to identify many genuine regulatory hotspots, for which more than half of the hotspots were previously reported elsewhere
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