The Application of Spearman Partial Correlation for Screening Predictors of Weight Loss in a Multiomics Dataset.

ABSTRACT: Obesity has reached epidemic proportions in the United States, but little is known about the mechanisms of weight gain and weight loss. Integration of omics data is becoming a popular tool to increase understanding in such complex phenotypes. Biomarkers come in abundance, but small sample size remains a serious limitation in clinical trials. In the present study, we developed a strategy to screen predictors from a multiomics, high-dimensional, and longitudinal dataset from a small cohort of 10 women with obesity who were provided an identical very-low calorie diet. Our proposal explores the combinatorial space of potential predictors from transcriptomics, microbiome, metabolome, fecal bile acids, and clinical data with the application of the first-order Spearman partial correlation coeffic

SUBMITTER: Rosa JCD 

PROVIDER: S-EPMC9805879 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature