Integrative analysis with a system of semiparametric projection non-linear regression models

Yuan Ao (), Wu Tianmin (), Fang Hong-Bin () and Tan Ming T. ()
Additional contact information
Yuan Ao: Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, 20057Washington DC, USA
Wu Tianmin: Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, 20057Washington DC, USA
Fang Hong-Bin: Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, 20057Washington DC, USA
Tan Ming T.: Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, 20057Washington DC, USA

The International Journal of Biostatistics, 2021, vol. 17, issue 1, 55-74

Abstract: In integrative analysis parametric or nonparametric methods are often used. The former is easier for interpretation but not robust, while the latter is robust but not easy to interpret the relationships among the different types of variables. To combine the advantages of both methods and for flexibility, here a system of semiparametric projection non-linear regression models is proposed for the integrative analysis, to model the innate coordinate structure of these different types of data, and a diagnostic tool is constructed to classify new subjects to the case or control group. Simulation studies are conducted to evaluate the performance of the proposed method, and shows promising results. Then the method is applied to analyze a real omics data from The Cancer Genome Atlas study, compared the results with those from the similarity network fusion, another integrative analysis method, and results from our method are more reasonable.

Keywords: innate coordinate structure; integrative analysis; omics data; semiparametric projection non-linear regression model (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/ijb-2019-0124 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:ijbist:v:17:y:2021:i:1:p:55-74:n:3

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/ijb/html

DOI: 10.1515/ijb-2019-0124

Access Statistics for this article

The International Journal of Biostatistics is currently edited by Antoine Chambaz, Alan E. Hubbard and Mark J. van der Laan

More articles in The International Journal of Biostatistics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().