A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation-Reference-Cited by-同舟云学术

A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation

Published:2020-06-05 Issue:2 Volume:77 Page:424-438
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Zhao Kaiqiong¹²^ORCID,Oualkacha Karim³,Lakhal‐Chaieb Lajmi⁴,Labbe Aurélie⁵,Klein Kathleen²,Ciampi Antonio¹²,Hudson Marie²⁶,Colmegna Inés⁶⁷,Pastinen Tomi⁸,Zhang Tieyuan⁹,Daley Denise¹⁰,Greenwood Celia M.T.¹²¹¹^ORCID

Affiliation:

1. Department of Epidemiology, Biostatistics and Occupational Health McGill University Montreal QC Canada

2. Lady Davis Institute for Medical Research Montreal QC Canada

3. Département de Mathématiques Université du Québec à Montrèal Montreal QC Canada

4. Département de Mathématiques et de Statistique Université Laval Quebec City QC Canada

5. Département des Sciences de la Décision HEC Montrèal Montreal QC Canada

6. Department of Medicine McGill University Montreal QC Canada

7. The Research Institute of the McGill University Health Centre Montreal QC Canada

8. Center for Pediatric Genomic Medicine Children's Mercy Kansas City Kansas City MO USA

9. Department of Psychiatry Douglas Mental Health University Institute McGill University Montreal QC Canada

10. The Centre for Heart Lung Innovation, and Department of Medicine University of British Columbia Vancouver BC Canada

11. Department of Human Genetics and Gerald Bronfman Department of Oncology McGill University Montreal QC Canada

Funder

Compute Canada

Canadian Institutes of Health Research

Natural Sciences and Engineering Research Council of Canada

Genome Canada

Fonds de Recherche du Québec - Santé

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13307

Reference43 articles.

1. Characterization of functional methylomes by next‐generation capture sequencing identifies novel disease‐associated variants;Allum F.;Nature Communications,2015

2. A classification approach for DNA methylation profiling with bisulfite next-generation sequencing data

3. Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci

4. Maximum Likelihood from Incomplete Data Via theEMAlgorithm

5. Phenotypic plasticity and the epigenetics of human disease

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