CLAMP - Curated Latent-variable Analysis with Molecular Priors
CLAMP performs prior-informed latent variable decomposition of high-dimensional transcriptomic data. It integrates curated gene sets to learn biologically interpretable latent variables, supports file-backed matrices for large datasets, and provides tools for preprocessing, normalization, projection, and evaluation of latent structures. CLAMP is designed to scale to tens of thousands of samples, making it suitable for large public resources such as recount3 and ARCHS4. It enables researchers to uncover biologically meaningful patterns that connect genes, pathways, and complex traits in transcriptomics studies.
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softwaregeneexpressionrnaseqtranscriptomicsdimensionreductionvisualizationnormalizationpathwayspreprocessinggenepredictiongenetargetopenblascpp
6.91 score 5 stars 17 scripts 598 downloadsCLAMPData - Experiment data for CLAMP package
Curated CLAMP resources (latent variables, loadings, priors, and example matrices) for use with the CLAMP package, distributed via ExperimentHub.
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experimenthubexperimentdatarnaseqdataexpressiondatadatapkg
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