Inference for set‐based effects in genetic association studies with interval‐censored outcomes

Ryan Sun, Liang Zhu, Yimei Li, Yutaka Yasui and Leslie Robison

Biometrics, 2023, vol. 79, issue 2, 1573-1585

Abstract: The rapid acceleration of genetic data collection in biomedical settings has recently resulted in the rise of genetic compendiums filled with rich longitudinal disease data. One common feature of these data sets is their plethora of interval‐censored outcomes. However, very few tools are available for the analysis of genetic data sets with interval‐censored outcomes, and in particular, there is a lack of methodology available for set‐based inference. Set‐based inference is used to associate a gene, biological pathway, or other genetic construct with outcomes and is one of the most popular strategies in genetics research. This work develops three such tests for interval‐censored settings beginning with a variance components test for interval‐censored outcomes, the interval‐censored sequence kernel association test (ICSKAT). We also provide the interval‐censored version of the Burden test, and then we integrate ICSKAT and Burden to construct the interval censored sequence kernel association test—optimal (ICSKATO) combination. These tests unlock set‐based analysis of interval‐censored data sets with analogs of three highly popular set‐based tools commonly applied to continuous and binary outcomes. Simulation studies illustrate the advantages of the developed methods over ad hoc alternatives, including protection of the type I error rate at very low levels and increased power. The proposed approaches are applied to the investigation that motivated this study, an examination of the genes associated with bone mineral density deficiency and fracture risk.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/biom.13636

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:biomet:v:79:y:2023:i:2:p:1573-1585

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0006-341X

Access Statistics for this article

More articles in Biometrics from The International Biometric Society
Bibliographic data for series maintained by Wiley Content Delivery ().