A computational framework for complex disease stratification from multiple large-scale datasets

Autor: De Meulder, B., Lefaudeux, D., Bansal, A. T., Mazein, A., Chaiboonchoe, A., Ahmed, H., Balaur, I., Saqi, M., Pellet, J., Ballereau, S., Lemonnier, N., Sun, K., Pandis, I., Yang, X., Batuwitage, M., Kretsos, K., van Eyll, J., Bedding, A., Davison, T., Dodson, P., Larminie, C., Postle, A., Corfield, J., Djukanovic, R., Chung, K. F., Adcock, I. M., Guo, Y. -K., Sterk, P. J., Manta, A., Rowe, A., Baribaud, F., Auffray, C., Gibeon, D., Hoda, U., Kuo, S., Meah, S., Meiser, A., Fleming, L. J., Hu, S., Pavlidis, S., Rossios, C., Russel, K., Wiegman, C., Nezhad, A. T., Oehmichen, A., O'Malley, D., Guitton, F., Emam, I., Agapow, P., Rice, P., Miles, S., Elyasigomari, V., Bel, E., Brinkman, P., Dekker, T., Dijkhuis, A., Hashimoto, S., Hekking, P. -P., Lone-Latif, S., Lutter, R., Ravanetti, L., Smids, B., van Aalderen, W., van de Pol, M., van Drunen, K., van Drunen, M., Wagener, A., Zwinderman, K., Adriaens, N., Carusi, A. M., Richard, F., Nogueira, M. M., Taibi, N., Brasier, O., Aliprantis, A., Alving, K., Faulenbach, C., Braun, A., Hohlfeld, J., Krug, N., Badorrek, P., Bakke, P., Berglind, A., Chaleckis, R., Dahlen, B., Delin, I., Gallart, H., Gomez, C., Hedlin, G., Henriksson, E., James, A. J., Kolmert, J., Konradsen, J., Kupczyk, M., Lantz, A. -S., Lazarinis, L., Mathon, C., Middelveld, R., Naz, S., Nordlund, B., Petren, A., Reinke, S., Sjodin, M., Soderman, P., Strandberg, K., Wheelock, C. E., Zetterquist, W., Balgoma, D., Brandsma, J., Burg, D., Dennison, P., Nicholas, B., Schofield, J. P. R., Skipp, P. J., Staykova, D., Tariq, K., Ward, J., Wilson, S. J., Barber, C., Loza, M. J., Bautmans, A., Sandstrom, T., Behndig, A. F., De Alba, J., Beleta, J., Berton, A., de Verdier, M. G., Nihlen, U., Ostling, J., Dalentoft, T., Lindgren, E., Boedigheimer, M. J., Hu, R., Hu, X., Yu, W., Bigler, J., Bonnelykke, K., Thorsen, J., Vising, N., Bisgaard, H., Bochenek, G., Caruso, M., Emma, R., Campagna, D., Thornton, B., Carayannopoulos, L., Gent, J., Manzies-Gow, A., Sogbesan, A., da Purificacao Rocha, P. C., Pedro, J., Chanez, P., Edwards, J., Flood, B., Hudson, V., Kennington, E. J., Metcalf, L., Rahman-Amin, M., Reynolds, L., Roberts, A., Smith, J., Supple, D., Versnel, J., Walker, S., Coleman, C., Hasan, S., Compton, C., Myles, D., Riley, J., Sousa, A. R., Yeyasingham, E., Pennazza, G., Santoninco, M., D'Amico, A., Dahlen, S. -E., de Boer, P., Robberechts, M., De Lepeleire, I., Fitch, N., Garret, T., Wagers, S., Draper, A., Thorngren, J. -O., Ericsson, M., Erpenbeck, V., Kluglich, M., Nething, K., Riemann, K., Schoelch, C., Seibold, W., Sigmund, R., Wald, F., Wetzel, K., Fichtner, K., Erzen, D., Galffy, G., Horvath, I., Szentkereszty, M., Tamasi, L., Fowler, S. J., Krueger, L., Singer, F., Frey, U., Gahlemann, M., Geiser, T., Hewitt, L., Howarth, P., Marouzet, L., Martin, J., Pink, S., Ray, E., Roberts, G., Smith, C., Gove, K., Gozzard, N., Williams, S., Haughney, J., Higgenbottam, T., Matthews, J. G., Holweg, C., Rutgers, M., Kamphuis, J., Kerry, D., Vink, A., Knobel, H., Knowles, R., Shaw, D. E., Smith, K. M., Know, A., Kots, M., Lambrecht, B., Masefield, S., Nilsson, P., Mikus, M., Miralpeix, M., Monk, P., Mores, N., Valente, S., Montuschi, P., Murray, C. S., Musial, J., Pacino, A., Pahus, L., Palkonen, S., Powel, P., Rao, N., Santini, G., Vestbo, J., von Garnier, C., Weiszhart, Z., Woodcock, A., Biryukov, M., Schneider, R., Herzinger, S., Satagopam, V., Gu, W., da Silva, A. B., Tielmann, A., Bergeron, J., Gaudette, A., Silberberg, A., Henderson, D., Hayat, S., Elefsinioti, A., Moltzen, E. K., Harbo, I. S., Birgitte, J., Bratfalean, D., Houston, P., Kisler, B., Capdevila, F. B., Verbeeck, D., Marchetti, G., Rahal, G., Schuermann, H. D., Mazuranok, L., Hendlich, M., Painell'S, L., Marren, D., Martasek, J., Rimell, J., Romacker, M., Braxenthaler, M., Sansone, S. -A., Rocca-Serra, P.
Přispěvatelé: Commission of the European Communities, Pulmonology, Graduate School, Experimental Immunology, Paediatric Pulmonology, Ear, Nose and Throat, Epidemiology and Data Science, APH - Methodology, ARD - Amsterdam Reproduction and Development, Consortium, U-Biopred Study Group And The Etriks, Rocca-Serra, P, Sansone, S, De Meulder, Bertrand [0000-0002-2108-7657], Apollo - University of Cambridge Repository
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: BMC Systems Biology, Vol 12, Iss 1, Pp 1-23 (2018)
BMC systems biology, 12(1):60. BioMed Central
U-BIOPRED Study Group, eTRIKS Consortium, Fowler, S J, Murray, C S, Vestbo, J & Woodcock, A 2018, ' A computational framework for complex disease stratification from multiple large-scale datasets ', BMC Systems Biology, vol. 12, no. 1, 60 . https://doi.org/10.1186/s12918-018-0556-z
BMC Systems Biology
ISSN: 1752-0509
DOI: 10.1186/s12918-018-0556-z
Popis: Background Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-‘omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-‘omics signatures of disease states. Methods The framework is divided into four major steps: dataset subsetting, feature filtering, ‘omics-based clustering and biomarker identification. Results We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-‘omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. Conclusions This framework will help health researchers plan and perform multi-‘omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine. Electronic supplementary material The online version of this article (10.1186/s12918-018-0556-z) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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