ZetaSuite: computational analysis of two-dimensional high-throughput data from multi-target screens and single-cell...

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• High-throughput two-dimensional data are prevalent in functional genomics.
• Analyzing this complex data presents significant challenges.
• Existing methods may not fully capture the nuances of such datasets.

Purpose of the Study:

• Introduce Zeta, a novel statistic for identifying global splicing regulators.
• Present ZetaSuite, a software package for applying Zeta statistics.
• Demonstrate the utility of ZetaSuite in diverse high-throughput datasets.

Main Methods:

• Developed the Zeta statistic for analyzing two-dimensional RNAi screens.
• Created the ZetaSuite software package for general application.
• Compared Zeta with existing methods on benchmarked datasets.

Main Results:

• Zeta effectively identifies global splicing regulators.
• ZetaSuite demonstrates broad utility in processing large-scale cancer dependency screens.
• ZetaSuite is effective for analyzing single-cell transcriptomics data.

Conclusions:

• Zeta and ZetaSuite offer a powerful approach for high-throughput functional genomics data analysis.
• The software facilitates the elucidation of novel biological insights from complex datasets.
• This work addresses key challenges in modern genomics data analysis.