ArticleJournal of the American Medical Informatics Association : JAMIA2012
The role of complementary bipartite visual analytical representations in the analysis of SNPs: a case study in ancestral informative markers.
Article in Journal of the American Medical Informatics Association : JAMIA, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Subtyping Social Determinants of Health in the "All of Us" Program: Network Analysis and Visualization Study.Journal of medical Internet research · 2025Article
- The Pre-Adaptation of a Stroke-Specific Self-Management Program Among Older Adults.Journal of aging and health · 2023Article
- Subtyping Social Determinants of Health inmedRxiv : the preprint server for health sciences · 2023Article
- A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach.JMIR medical informatics · 2022Article
- Methylation differences reveal heterogeneity in preterm pathophysiology: results from bipartite network analyses.Journal of perinatal medicine · 2018Review
- Review
- How Comorbidities Co-Occur in Readmitted Hip Fracture Patients: From Bipartite Networks to Insights for Post-Discharge Planning.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Heterogeneity within and across Pediatric Pulmonary Infections: From Bipartite Networks to At-Risk Subphenotypes.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2014Article
- How Cytokines Co-occur across Rickettsioses Patients: From Bipartite Visual Analytics to Mechanistic Inferences of a Cytokine Storm.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2013Article
- Network analysis of unstructured EHR data for clinical research.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2013Article
- The coming age of data-driven medicine: translational bioinformatics' next frontier.Journal of the American Medical Informatics Association : JAMIA · 2012Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveSeveral studies have shown how sets of single-nucleotide polymorphisms (SNPs) can help to classify subjects on the basis of their continental origins, with applications to case-control studies and population genetics. However, most of these studies use dimensionality-reduction methods, such as principal component analysis, or clustering methods that result in unipartite (either subjects or SNPs) representations of the data. Such analyses conceal important bipartite relationships, such as how subject and SNP clusters relate to each other, and the genotypes that determine their cluster memberships.
methodsTo overcome the limitations of current methods of analyzing SNP data, the authors used three bipartite analytical representations (bipartite network, heat map with dendrograms, and Circos ideogram) that enable the simultaneous visualization and analysis of subjects, SNPs, and subject attributes.
resultsThe results demonstrate (1) novel insights into SNP data that are difficult to derive from purely unipartite views of the data, (2) the strengths and limitations of each method, revealing the role that each play in revealing novel insights, and (3) implications for how the methods can be used for the analysis of SNPs in genomic studies associated with disease.
conclusionThe results suggest that bipartite representations can reveal new patterns in SNP data compared with existing unipartite representations. However, the novel insights require multiple representations to discover, verify, and comprehend the complex relationships. The results therefore motivate the need for a complementary visual analytical framework that guides the use of multiple bipartite representations to analyze complex relationships in SNP data.
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