Secondary Phenotype

The SecondaryPhenotype R package uses proportional odds logistic regression to test for the association between a SNP (i.e. x) and secondary phenotype (i.e. y) while accounting for the ascertainment bias due to case-control sampling (i.e. d).


install.packages("devtools") # devtools must be installed first



For the given dataset dataSP, one can test if the SNP (i.e. x) is associated with the normally distributed secondary phenotype (i.e. y) given the case-control sampling (i.e. d) and adjusting for a confounder (i.e. z). The code below runs this analysis.

library(SecondaryPhenotype) #load the library SecondaryPhenotype
?SecondaryPhenotype # For details on how to use the function

x <- dataSP[,"x"]
y <- dataSP[,"y"]
d <- dataSP[,"d"]
z <- dataSP[,"z"]


For this example, the SNP is associated with the secondary phenotype given the case-control sampling (p-value=0.0001).

[1] "The SNP is associated with the secondary phenotype Y given case-control status (p-value=0.00016172135463588)."
Likelihood ratio tests of ordinal regression models

Response: as.factor(x)
      Model Resid. df Resid. Dev   Test    Df LR stat.      Pr(Chi)
1     d + z       996    1885.27                                   
2 y + d + z       995    1871.04 1 vs 2     1 14.23058 0.0001617214


Lutz SM, Hokanson JE, Lange C. (2014) An Alternative Hypothesis Testing Strategy for Secondary Phenotype Data in Case-Control Genetic Association Studies. Frontiers in Genetics. 5 (188).

SharonLutz/SecondaryPhenotype documentation built on May 31, 2019, 3:53 a.m.