Article

TiMEG: an integrative approach for partially missing multi-omics data with an application to tuberous sclerosis

2020-12-11

Abstract excerpt

1 Multi-omics data integration is widely used to understand the genetic architecture of disease. In multi-omics association analysis, data collected on multiple omics for the same set of individuals are immensely important for biomarker identification. But when the sample size of such data is limited, the presence of partially missing individual-level observations poses a major challenge in data integration. More...

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Literature Corpus work: 48ca57cd-761d-5263-9f4f-8cb229e16b03
DOI: 10.1101/2020.12.10.420638

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