A principal-components-based clustering method to identify multiple variants associated with rheumatoid arthritis and arthritis-related autoantibodies.
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ABSTRACT:
SUBMITTER: Black MH
PROVIDER: S-EPMC2795902 | biostudies-literature | 2009 Dec
REPOSITORIES: biostudies-literature
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A principal-components-based clustering method to identify multiple variants associated with rheumatoid arthritis and arthritis-related autoantibodies.
Black Mary Helen MH Watanabe Richard M RM
BMC proceedings 20091215
Multivariate techniques are an important area of investigation for studying contributions of multiple genetic variants to disease onset and pathology. We analyzed the Genetic Analysis Workshop 16 North American Rheumatoid Arthritis Consortium (NARAC) data using a principal-components analysis (PCA) with an orthoblique rotation to identify specific subsets of single-nucleotide polymorphisms (SNP) in the major histocompatibility complex (MHC) region associated with rheumatoid arthritis (RA) and rh ...[more]
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