10 citations · 16 across the 10 of their papers we have counts for
10 papers
DMseg: a Python algorithm for de novo detection of differentially or variably methylated regions
Xiaoyu Wang, Ming Yu, William Grady +3
Detecting and assessing statistical significance of differentially methylated regions (DMRs) is a fundamental task in methylome association studies. While the average differential…
Incorporating increased variability in testing for cancer DNA methylation
James Y. Dai, Heng Chen, Xiaoyu Wang +4
Cancer development is associated with aberrant DNA methylation, including increased stochastic variability. Statistical tests for discovering cancer methylation biomarkers have foc…
Heterogeneity-aware integrative regression for ancestry-specific association studies
Aaron J. Molstad, Yanwei Cai, Alexander P. Reiner +3
Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral group…
Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics
Zhen Miao, Weihao Kong, Ramya Korlakai Vinayak +2
This paper investigates the theoretical and empirical performance of Fisher-Pitman-type permutation tests for assessing the equality of unknown Poisson mixture distributions. Build…
A covariance-enhanced approach to multi-tissue joint eQTL mapping with application to transcriptome-wide association studies
Aaron J. Molstad, Wei Sun, Li Hsu
Transcriptome-wide association studies based on genetically predicted gene expression have the potential to identify novel regions associated with various complex traits. It has be…
Gaussian process regression for survival time prediction with genome-wide gene expression
Aaron J. Molstad, Li Hsu, Wei Sun
Predicting the survival time of a cancer patient based on his/her genome-wide gene expression remains a challenging problem. For certain types of cancer, the effects of gene expres…