Journal article
Interactive network-based clustering and investigation of multimorbidity association matrices with associationSubgraphs
Bioinformatics (Oxford, England), Vol.39(1), btac780
2023
PMID: 36472455
Abstract
Motivation: Making sense of networked multivariate association patterns is vitally important to many areas of high-dimensional analysis. Unfortunately, as the data-space dimensions grow, the number of association pairs increases in O(n(2)); this means that traditional visualizations such as heatmaps quickly become too complicated to parse effectively.
Results: Here, we present associationSubgraphs: a new interactive visualization method to quickly and intuitively explore high-dimensional association datasets using network percolation and clustering. The goal is to provide an efficient investigation of association subgraphs, each containing a subset of variables with stronger and more frequent associations among themselves than the remaining variables outside the subset, by showing the entire clustering dynamics and providing subgraphs under all possible cutoff values at once. Particularly, we apply association Subgraphs to a phenome-wide multimorbidity association matrix generated from an electronic health record and provide an online, interactive demonstration for exploring multimorbidity subgraphs.
Details
- Title
- Interactive network-based clustering and investigation of multimorbidity association matrices with associationSubgraphs
- Authors/Creators
- Nick Strayer - Vanderbilt UniversitySiwei Zhang - Vanderbilt UniversityLydia Yao - Vanderbilt UniversityTess Vessels - Vanderbilt University Medical CenterCosmin A. Bejan - Vanderbilt University Medical CenterRyan S. Hsi - Vanderbilt University Medical CenterJana K. Shirey-Rice - Vanderbilt University Medical CenterJustin M. Balko - Vanderbilt University Medical CenterDouglas B. Johnson - Vanderbilt University Medical CenterElizabeth J. Phillips - Vanderbilt University Medical CenterAlex Bick - Vanderbilt University Medical CenterTodd L. Edwards - Vanderbilt University Medical CenterDigna R. Velez Edwards - Vanderbilt University Medical CenterJill M. Pulley - Vanderbilt University Medical CenterQuinn S. Wells - Vanderbilt University Medical CenterMichael R. Savona - Vanderbilt University Medical CenterNancy J. Cox - Vanderbilt University Medical CenterDan M. Roden - Vanderbilt University Medical CenterDouglas M. Ruderfer - Vanderbilt University Medical CenterYaomin Xu - Vanderbilt University
- Publication Details
- Bioinformatics (Oxford, England), Vol.39(1), btac780
- Publisher
- Oxford University Press
- Number of pages
- 6
- Grant note
- UL1 TR002243; R21DK127075; R01HL140074; P50GM115305; R01CA227481; UL1 TR0002245 / Vanderbilt University Department of Biostatistics Development Award
- Identifiers
- 991005588669807891
- Copyright
- © 2022 The Author(s)
- Murdoch Affiliation
- Institute for Immunology and Infectious Diseases
- Language
- English
- Resource Type
- Journal article
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