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Statistical Simulator Supports Benchmarking Tool to Mimic Omics Data

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The UCLA researchers say they believe scDesign3 “offers the first probabilistic model that unifies the generation and inference for single-cell and spatial omics data."

Credit: UCLA Health

University of California, Los Angeles (UCLA) researchers have developed a next-generation in-silico statistical simulator that can support a benchmarking tool for medical and biological researchers to assess and validate computational methods.

UCLA's Jingyi Jessica Li said the researchers created the scDesign3 simulator to mimic actual information in order to produce realistic single-cell RNA sequencing data from continuous cell trajectories.

The team described scDesign3 as "a multifunctional suite for benchmarking computational methods and interpreting single-cell and spatial omics data."

The researchers explained scDesign3's interpretable parameters and model likelihood can generate tailored in silico data "as negative and positive controls for computational analysis, and for assessing the goodness-of-fit of inferred cell clusters, trajectories, and spatial locations in an unsupervised way."

From UCLA Health
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