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- W4287146918 abstract "Abstract 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." @default.
- W4287146918 created "2022-07-25" @default.
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- W4287146918 date "2022-07-25" @default.
- W4287146918 modified "2023-10-14" @default.
- W4287146918 title "ZetaSuite: computational analysis of two-dimensional high-throughput data from multi-target screens and single-cell transcriptomics" @default.
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- W4287146918 doi "https://doi.org/10.1186/s13059-022-02729-4" @default.
- W4287146918 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35879727" @default.
- W4287146918 hasPublicationYear "2022" @default.
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