Ranking the importance of genetic factors by variable‐selection confidence sets

Chao Zheng, Davide Ferrari, Michael Zhang and Paul Baird

Journal of the Royal Statistical Society Series C, 2019, vol. 68, issue 3, 727-749

Abstract: The widespread use of generalized linear models in case–control genetic studies has helped to identify many disease‐associated risk factors typically defined as DNA variants, or single‐nucleotide polymorphisms (SNPs). Up to now, most literature has focused on selecting a unique best subset of SNPs based on some statistical perspective. When the noise is large compared with the signal, however, multiple biological paths are often found to be supported by a given data set. We address the ambiguity related to SNP selection by constructing a list of models—called a variable‐selection confidence set (VSCS)—which contains the collection of all well‐supported SNP combinations at a user‐specified confidence level. The VSCS extends the familiar notion of confidence intervals in the variable‐selection setting and provides the practitioner with new tools aiding the variable‐selection activity beyond trusting a single model. On the basis of the VSCS, we consider natural graphical and numerical statistics measuring the inclusion importance of an SNP based on its frequency in the most parsimonious VSCS models. This work is motivated by available case–control genetic data on age‐related macular degeneration, which is a widespread disease and leading cause of loss of vision.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://doi.org/10.1111/rssc.12337

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:bla:jorssc:v:68:y:2019:i:3:p:727-749

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().