Celia M. T. Greenwood

发表

PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

Michael S. Kobor, Michael J. Meaney, Lawrence Ming Chen, 2017 .

Simultaneous SNP selection and adjustment for population structure in high dimensional prediction models

Sahir Bhatnagar, Yi Yang, Celia M. T. Greenwood, 2019 .

Using the ratio of means as the effect size measure in combining results of microarray experiments

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2009, BMC Systems Biology.

Statistical Methods for Meta-Analysis of Microarray Data: A Comparative Study

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2006, Inf. Syst. Frontiers.

Integrating Affymetrix microarray data sets using probe-level test statistic for predicting prostate cancer

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

Functional normalization of 450k methylation array data improves replication in large cancer studies

Mathieu Lemire, Aurélie Labbe, Thomas J. Hudson, 2014 .

Bayesian Hyper-LASSO Classification for Feature Selection with Application to Endometrial Cancer RNA-seq Data

Celia M. T. Greenwood, Lai Jiang, Weixin Yao, 2020, Scientific Reports.

Significance Thresholds for Rare Variant Signals

Celia M. T. Greenwood, Antonio Ciampi, ChangJiang Xu, 2015 .

Weighted kernel Fisher discriminant analysis for integrating heterogeneous data

Jemila S. Hamid, Joseph Beyene, Celia M. T. Greenwood, 2012, Comput. Stat. Data Anal..

Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework

Alan C. Evans, Samir Das, Pierre Rioux, 2018, Front. Neuroinform..

Understanding the impact of preprocessing pipelines on neuroimaging cortical surface analyses

David N. Kennedy, Bratislav Misic, Shawn T. Brown, 2020, bioRxiv.

Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2005, BMC Bioinformatics.

Sparse Additive Interaction Learning

Yi Yang, Celia M. T. Greenwood, Sahir Bhatnagar, 2018, bioRxiv.

A General Framework for Variable Selection in Linear Mixed Models with Applications to Genetic Studies with Structured Populations

Yi Yang, Marie Forest, Celia M. T. Greenwood, 2018, bioRxiv.

funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types

Antonio Ciampi, Jean-Philippe Fortin, Aurélie Labbe, 2015, Bioinform..

Principal component of explained variance: an efficient and optimal data dimension reduction framework for association studies

Pedro Rosa-Neto, Aurélie Labbe, Maxime Turgeon, 2016 .

MDiNE: a model to estimate differential co-occurrence networks in microbiome studies

Aurélie Labbe, Celia M. T. Greenwood, Kevin McGregor, 2019, bioRxiv.

PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

Michael S. Kobor, Eva Unternaehrer, Shantala A. Hari Dass, 2017, BMC Bioinformatics.

A modified score function estimator for multinomial logistic regression in small samples

Celia M. T. Greenwood, Shelley B. Bull, Carment Mak, 2002 .

Efficiency of reduced logistic regression models

Allan Donner, Celia M. T. Greenwood, Shelley B. Bull, 1994 .