CPASSOC statistics

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CPASSOC specifications

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Unique identifier OMICS_20330
Name CPASSOC
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability No
Maintained No

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Publication for CPASSOC

CPASSOC in publications

 (5)
PMCID: 5832233
PMID: 29494641
DOI: 10.1371/journal.pone.0193256

[…] more than a half of study traits. as the number of traits with null effects increases, asset performed the best along with competitive specificity and sensitivity. with opposite directional effects, cpassoc featured the first-rate power. however, caution is advised when using cpassoc for studying genetically correlated traits with overlapping samples. we conclude with a discussion of unresolved […]

PMCID: 5717338
PMID: 29093210
DOI: 10.1098/rsob.170125

[…] two meta-analysis test statistics to detect cross-phenotype associations assuming homogeneous and heterogeneous effects across studies, respectively []. the tests are implemented in the r package cpassoc, and work with both univariate (i.e. one trait per cohort) and multivariate summary statistics (i.e. several traits measured in each cohort). cpassoc requires the specification […]

PMCID: 5886098
PMID: 28934396
DOI: 10.1093/hmg/ddx285

[…] to search for potential novel associations not identified by single-trait gwas, we performed a cross-phenotype meta-analysis between each pairwise combination of oa and bmd datasets. using the cpassoc method (), we computed two statistics, shom and shet, which assume homogeneous and heterogeneous effects across studies, respectively. the quantile–quantile and manhattan plots […]

PMCID: 5446189
PMID: 28498854
DOI: 10.1371/journal.pgen.1006728

[…] snps; and hypertension (htn): one locus, one snp), with the evx1/hoxa locus identified for sbp, dbp and htn (). when combining summary statistics for sbp, dbp, and htn using the multi-trait approach cpassoc,[] we identified one locus by the multi-trait statistic shom (evx1/hoxa) and six loci by shet (ulk4, tcf21, evx1/hoxa, igfbp3, cdh17, znf746) at p < 5×10−8 (). note some loci overlap […]

PMCID: 5049793
PMID: 27701450
DOI: 10.1371/journal.pone.0163912

[…] association studies (gwass). although hundreds of variants have been identified by gwas, these variants only explain a small fraction of phenotypic variation. cross-phenotype association analysis (cpassoc) can further improve statistical power by searching for variants that contribute to multiple traits, which is often relevant to pleiotropy. in this study, we performed cpassoc analysis […]


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CPASSOC institution(s)
Department of Epidemiology & Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA; College of Mathematical Science, Heilongjiang University, Harbin, China; Department of Public Health Science, Loyola University Chicago Stritch School of Medicine, Maywood, IL, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Center for Human Genetics Research, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN, USA; Tulane Center for Cardiovascular Health, Tulane University, New Orleans, LA, USA; Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD, USA; Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA; University of Virginia Center for Public Health Genomics, Charlottesville, VA, USA; The Charles Bronfman Institute for Personalized Medicine, Mount Sinai School of Medicine, New York, NY, USA; Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD, USA; Department of Epidemiology & Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL,USA; Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA; Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Departments of Medicine, Brigham and Women’s Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
CPASSOC funding source(s)
Supported by the NIH grants HG003054 from the National Human Genome Research Institute and HL086718, HL053353, HL113338, and HL123677 from the National Heart, Lung, and Blood Institute.

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