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A Multi-Marker Test for Analyzing Paired Genetic Data in Transplantation
Victoria L. Arthur
, Zhengbang Li
, Rui Cao
, William S. Oetting
,
Ajay K. Israni
, Pamala A. Jacobson
, Marylyn D. Ritchie
, Weihua Guan
, Jinbo Chen
Research output
:
Contribution to journal
›
Article
›
peer-review
6
Scopus citations
Overview
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Dive into the research topics of 'A Multi-Marker Test for Analyzing Paired Genetic Data in Transplantation'. Together they form a unique fingerprint.
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Keyphrases
Genetic Data
100%
Transplantation
100%
Score Test
100%
Joint Score
100%
Multi-marker Test
100%
Matching Score
100%
Single nucleotide Polymorphism
66%
Gene-rich Regions
66%
Transplant Outcomes
66%
Donor-recipient Matching
66%
Common SNP
66%
Multimarker
66%
Matching Effect
66%
Genetic Studies
33%
Genotype
33%
Coding Region
33%
Statistical Power
33%
Gene Coding
33%
Non-associated
33%
Transplant Experiment
33%
SNP
33%
Acute Rejection
33%
Degrees of Freedom
33%
Multiple Genes
33%
Biological Mechanisms
33%
Human Leukocyte Antigen
33%
Kidney Transplant
33%
Linkage Disequilibrium
33%
Simulation Study
33%
Gene-based
33%
Dimensionality Reduction
33%
Non-HLA
33%
Marker-based
33%
Single nucleotide Polymorphism Effect
33%
Sequence Kernel Association Test
33%
Genotype Effect
33%
Eigendecomposition
33%
Transplant Genetics
33%
Biochemistry, Genetics and Molecular Biology
Genetics
100%
Single-Nucleotide Polymorphism
100%
Single Nucleotide Polymorphism
100%
Genotyping
66%
Coding Region
33%
Human Leukocyte Antigen
33%
Gene Linkage Disequilibrium
33%
Mathematics
Score Test
100%
Statistical Power
33%
Simulation Study
33%
Biological Mechanism
33%
Degree of Freedom
33%
Coding Region
33%
Medicine and Dentistry
Single Nucleotide Polymorphism
100%
Kidney Graft
16%
Human Leukocyte Antigen
16%
Acute Graft Rejection
16%
Gene Linkage Disequilibrium
16%