期刊
GENOME BIOLOGY
卷 22, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s13059-021-02313-2
关键词
-
资金
- NIH [R01 GM081871]
- U.S. Department of Defense (DOD) through the National Defense Science and Engineering Graduate Fellowship (NDSEG)
Schema is a tool that synthesizes multiple biological information modalities using a metric learning strategy, which can be used for inferring cell types, data visualization, performing differential gene expression analysis, and estimating evolutionary pressure on peptide sequences.
A complete understanding of biological processes requires synthesizing information across heterogeneous modalities, such as age, disease status, or gene expression. Technological advances in single-cell profiling have enabled researchers to assay multiple modalities simultaneously. We present Schema, which uses a principled metric learning strategy that identifies informative features in a modality to synthesize disparate modalities into a single coherent interpretation. We use Schema to infer cell types by integrating gene expression and chromatin accessibility data; demonstrate informative data visualizations that synthesize multiple modalities; perform differential gene expression analysis in the context of spatial variability; and estimate evolutionary pressure on peptide sequences.
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