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CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing - 1 Jan 2000

He Bryan, Thomson Matthew, Subramaniam Meena, Perez Richard, Ye Chun Jimmie, Zou James

Abstract excerpt

Single-cell RNA sequencing (scRNA-seq) has the potential to provide powerful, high-resolution signatures to inform disease prognosis and precision medicine. This paper takes an important first step towards this goal by developing an interpretable machine learning algorithm, CloudPred, to predict individuals' disease phenotypes from their scRNA-seq data. Predicting phenotype from scRNA-seq is challenging for...

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PMID: 34890161

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