Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies.
Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work.
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America.
Nicholas B
NB
Larson
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America.
Shannon
S
McDonnell
Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.
Lisa Cannon
LC
Albright
Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.
Craig
C
Teerlink
Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
Janet
J
Stanford
National Human Genome Research Institute, Bethesda, Maryland, United States of America.
Elaine A
EA
Ostrander
Department of Urology, Johns Hopkins Hospital, Baltimore, Maryland, United States of America.
William B
WB
Isaacs
NorthShore University HealthSystem Research Institute, Chicago, Illinois, United States of America.
Jianfeng
J
Xu
Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Urology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.
Kathleen A
KA
Cooney
Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Ethan
E
Lange
Department of Medical Biochemistry and Genetics, Institute of Biomedicine, University of Turku, Finland.
Johanna
J
Schleutker
Integrated Cancer Genomics Division, The Translational Genomics Research Institute, Phoenix, Arizona, United States of America.
John D
JD
Carpten
Wayne State University, Detroit, Michigan, United States of America.
Isaac
I
Powell
Statistical Genetics Section, National Human Genome Research Institute, Bethesda, Maryland, United States of America.
Joan
J
Bailey-Wilson
CeRePP, Hopital Tenon, Paris, France.
Olivier
O
Cussenot
CeRePP, Hopital Tenon, Paris, France.
Geraldine
G
Cancel-Tassin
Cancer Epidemiology Centre, Cancer Council Victoria, University of Melbourne, Melbourne, Australia.|Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Graham
G
Giles
Cancer Epidemiology Centre, Cancer Council Victoria, University of Melbourne, Melbourne, Australia.|Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Robert
R
MacInnis
Department of Urology, University of Ulm, Ulm, Germany.
Christiane
C
Maier
Department of Health Research and Policy, Stanford University, Stanford, California, United States of America.
Alice S
AS
Whittemore
Department of Urology, University of Southern California, Los Angeles, California, United States of America.
Chih-Lin
CL
Hsieh
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Fredrik
F
Wiklund
Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.
William J
WJ
Catalona
Department of Oncology and Human Genetics, Montreal General Hospital, Montreal, QC, Canada.|Department of Human Genetics, Montreal General Hospital, Montreal, QC, Canada.
William
W
Foulkes
Department of Genetics, LSU Health Sciences Center, New Orleans, Louisiana, United States of America.
Diptasri
D
Mandal
Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, United Kingdom.
Rosalind
R
Eeles
Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, United Kingdom.
Zsofia
Z
Kote-Jarai
Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Michael J
MJ
Ackerman
Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Timothy M
TM
Olson
Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America.
Christopher J
CJ
Klein
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, United States of America.
Stephen N
SN
Thibodeau
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America.
Daniel J
DJ
Schaid
D001499:Bayes Theorem; D016022:Case-Control Studies; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008957:Models, Genetic; D017422:Sequence Analysis, DNA
MCMC; Next-generation sequencing; burden testing; prostate cancer