2 citations · 3 across the 5 of their papers we have counts for
5 papers
An algorithm-based multiple detection influence measure for high dimensional regression using expectile
Amadou Barry, Nikhil Bhagwat, Bratislav Misic +2
The identification of influential observations is an important part of data analysis that can prevent erroneous conclusions drawn from biased estimators. However, in high dimension…
Detecting differentially methylated regions in bisulfite sequencing data using quasi-binomial mixed models with smooth covariate effect estimates
Kaiqiong Zhao, Karim Oualkacha, Lajmi Lakhal-Chaieb +6
Identifying disease-associated changes in DNA methylation can help to gain a better understanding of disease etiology. Bisulfite sequencing technology allows the generation of meth…
A Tracy-Widom Empirical Estimator For Valid P-values With High-Dimensional Datasets
Maxime Turgeon, Celia MT Greenwood, Aurelie Labbe
Recent technological advances in many domains including both genomics and brain imaging have led to an abundance of high-dimensional and correlated data being routinely collected.…
Distinguishing differential susceptibility, diathesis-stress and vantage sensitivity: beyond the single gene and environment model
Alexia Jolicoeur-Martineau, Jay Belsky, Eszter Szekely +4
Currently, two main approaches exist to distinguish differential susceptibility from diathesis-stress and vantage sensitivity in genotype x environment interaction (GxE) research:…
Alternating optimization for GxE modelling with weighted genetic and environmental scores: examples from the MAVAN study
Alexia Jolicoeur-Martineau, Ashley Wazana, Eszter Szekely +5
Motivated by the goal of expanding currently existing genotype x environment interaction (GxE) models to simultaneously include multiple genetic variants and environmental exposure…