342 research outputs found

    A robust clustering algorithm for identifying problematic samples in genome-wide association studies

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    Summary: High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individual's inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide variation. Its use as a semi-automated quality control tool is demonstrated using several summary statistics, selected to identify different potential problems, and it is applied to two different genotyping platforms and sample collections

    The complex genetics of multiple sclerosis: pitfalls and prospects

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    The genetics of complex disease is entering a new and exciting era. The exponentially growing knowledge and technological capabilities emerging from the human genome project have finally reached the point where relevant genes can be readily and affordably identified. As a result, the last 12 months has seen a virtual explosion in new knowledge with reports of unequivocal association to relevant genes appearing almost weekly. The impact of these new discoveries in Neuroscience is incalculable at this stage but potentially revolutionary. In this review, an attempt is made to illuminate some of the mysteries surrounding complex genetics. Although focused almost exclusively on multiple sclerosis all the points made are essentially generic and apply equally well, with relatively minor addendums, to any other complex trait, neurological or otherwise

    A second major histocompatibility complex susceptibility locus for multiple sclerosis

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    Objective: Variation in the major histocompatibility complex (MHC) on chromosome 6p21 is known to influence susceptibility to multiple sclerosis with the strongest effect originating from the HLA-DRB1 gene in the class II region. The possibility that other genes in the MHC independently influence susceptibility to multiple sclerosis has been suggested but remains unconfirmed. Methods: Using a combination of microsatellite, single nucleotide polymorphism, and human leukocyte antigen (HLA) typing, we screened the MHC in trio families looking for evidence of residual association above and beyond that attributable to the established DRB1*1501 risk haplotype. We then refined this analysis by extending the genotyping of classical HLA loci into independent cases and control subjects. Results: Screening confirmed the presence of residual association and suggested that this was maximal in the region of the HLA-C gene. Extending analysis of the classical loci confirmed that this residual association is partly due to allelic heterogeneity at the HLA-DRB1 locus, but also reflects an independent effect from the HLA-C gene. Specifically, the HLA-C*05 allele, or a variant in tight linkage disequilibrium with it, appears to exert a protective effect (p = 3.3 × 10−5). Interpretation: Variation in the HLA-C gene influences susceptibility to multiple sclerosis independently of any effect attributable to the nearby HLA-DRB1 gene
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