Methods for Collapsing Multiple Rare Variants in Whole-Genome Sequence Data-Reference-Cited by-同舟云学术

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Methods for Collapsing Multiple Rare Variants in Whole-Genome Sequence Data

Published:2014-08-11 Issue:S1 Volume:38 Page:S13-S20
ISSN:0741-0395
Container-title:Genetic Epidemiology
language:en
Short-container-title:Genet. Epidemiol.

Author:

Sung Yun Ju¹,Korthauer Keegan D.²,Swartz Michael D.³,Engelman Corinne D.⁴

Affiliation:

1. Division of Biostatistics; Washington University School of Medicine; St. Louis Missouri United States of America

2. Department of Statistics; University of Wisconsin; Madison Wisconsin United States of America

3. Division of Biostatistics; University of Texas School of Public Health; Houston Texas United States of America

4. Department of Population Health Sciences; University of Wisconsin; Madison Wisconsin United States of America

Funder

National Institutes of Health

NIH

Publisher

Wiley

Subject

Genetics (clinical),Epidemiology

Reference39 articles.

1. Considering interactive effects in the identification of influential regions in extremely rare variants via fixed bin approach;Agne;BMC Proc,2014

2. Data for Genetic Analysis Workshop 18: human whole-genome sequence, blood pressure, and simulated phenotypes in extended pedigrees;Almasy;BMC Proc,2014

3. Rare variant association analysis methods for complex traits;Asimit;Annu Rev Genet,2010

4. Statistical analysis strategies for association studies involving rare variants;Bansal;Nat Rev Genet,2010

5. Comparison of statistical tests for disease association with rare variants;Basu;Genet Epidemiol,2011

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3. A review of regression and classification techniques for analysis of common and rare variants and gene-environmental factors;Neurocomputing;2021-12

4. Genetic factors in treatment-related cardiovascular complications in survivors of childhood acute lymphoblastic leukemia;Pharmacogenomics;2021-09

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