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ANIMA: Association Network Integration for Multiscale Analysis

View ORCID ProfileArmin Deffur, View ORCID ProfileRobert J Wilkinson, View ORCID ProfileBongani M Mayosi, View ORCID ProfileNicola Mulder
doi: https://doi.org/10.1101/257642
Armin Deffur
1Department of Medicine, University of Cape Town, South Africa
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  • For correspondence: A.Deffur@uct.ac.za
Robert J Wilkinson
1Department of Medicine, University of Cape Town, South Africa
2Wellcome Centre for Infectious Diseases Research in Africa, University of Cape Town, South Africa
3Francis Crick Institute, London, NW1 2AT, United Kingdom
4Imperial College London, W2 1PG, United Kingdom
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Bongani M Mayosi
1Department of Medicine, University of Cape Town, South Africa
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Nicola Mulder
5Computational Biology Division, Department Integrative Biomedical Sciences, IDM, University of Cape Town, South Africa
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Abstract

Contextual functional interpretation of -omics data derived from clinical samples is a classical and difficult problem in computational systems biology. The measurement of thousands of datapoints on single samples has become routine but relating ‘big data’ datasets to the complexities of human pathobiology is an area of ongoing research. Complicating this is the fact that many publically available datasets use bulk transcriptomics data from complex tissues like blood. The most prevalent analytic approaches derive molecular ‘signatures’ of disease states or apply modular analysis frameworks to the data. Here we show, using a network-based data integration method using clinical phenotype and microarray data as inputs, that we can reconstruct multiple features (or endophenotypes) of disease states at various scales of organization, from transcript abundance patterns of individual genes through co-expression patterns of groups of genes to patterns of cellular behavior in whole blood samples, both in single experiments as well as in a meta-analysis of multiple datasets.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted February 10, 2018.
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ANIMA: Association Network Integration for Multiscale Analysis
Armin Deffur, Robert J Wilkinson, Bongani M Mayosi, Nicola Mulder
bioRxiv 257642; doi: https://doi.org/10.1101/257642
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ANIMA: Association Network Integration for Multiscale Analysis
Armin Deffur, Robert J Wilkinson, Bongani M Mayosi, Nicola Mulder
bioRxiv 257642; doi: https://doi.org/10.1101/257642

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