Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
, 29 Rosedale Ave, MA 01545, Shrewsbury, USA.
Genome Biol. 2022 Jul 25;23(1):162. doi: 10.1186/s13059-022-02729-4.
Two-dimensional high-throughput data have become increasingly common in functional genomics studies, which raises new challenges in data analysis. Here, we introduce a new statistic called Zeta, initially developed to identify global splicing regulators from a two-dimensional RNAi screen, a high-throughput screen coupled with high-throughput functional readouts, and ZetaSuite, a software package to facilitate general application of the Zeta statistics. We compare our approach with existing methods using multiple benchmarked datasets and then demonstrate the broad utility of ZetaSuite in processing public data from large-scale cancer dependency screens and single-cell transcriptomics studies to elucidate novel biological insights.
二维高通量数据在功能基因组学研究中变得越来越普遍，这给数据分析带来了新的挑战。在这里，我们介绍了一种新的统计量，称为 Zeta，最初是为了从二维 RNAi 筛选中识别全局剪接调节剂而开发的，这是一种与高通量功能读出相结合的高通量筛选方法，以及 ZetaSuite，这是一个软件包，用于方便一般应用 Zeta 统计。我们使用多个基准数据集比较了我们的方法与现有方法，然后展示了 ZetaSuite 在处理来自大规模癌症依赖性筛选和单细胞转录组学研究的公共数据以阐明新的生物学见解方面的广泛用途。
