Biomedical subjects
Publications and source records attributed to Thomas B Ryder.
Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.
The analysis of single nucleotide polymorphisms (SNPs) is increasingly utilized to investigate the genetic causes of complex human diseases. Here we present a high-throughput genotyping platform that uses a one-primer assay to genotype over 10,000 SNPs per individual on a single oligonucleotide array. This approach uses restriction digestion to fractionate the genome, followed by amplification of a specific fractionated subset of the genome. The resulting reduction in genome complexity enables allele-specific hybridization to the array. The selection of SNPs was primarily determined by computer-predicted lengths of restriction fragments containing the SNPs, and was further driven by strict empirical measurements of accuracy, reproducibility, and average call rate, which we estimate to be >99.5%, >99.9%, and>95%, respectively [corrected]. With average heterozygosity of 0.38 and genome scan resolution of 0.31 cM, the SNP array is a viable alternative to panels of microsatellites (STRs). As a demonstration of the utility of the genotyping platform in whole-genome scans, we have replicated and refined a linkage region on chromosome 2p for chronic mucocutaneous candidiasis and thyroid disease, previously identified using a panel of microsatellite (STR) markers.
MOTIVATION: Analysis of many thousands of single nucleotide polymorphisms (SNPs) across whole genome is crucial to efficiently map disease genes and understanding susceptibility to diseases, drug efficacy and side effects for different populations and individuals. High density oligonucleotide microarrays provide the possibility for such analysis with reasonable cost. Such analysis requires accurate, reliable methods for feature extraction, classification, statistical modeling and filtering. RESULTS: We propose the modified partitioning around medoids as a classification method for relative allele signals. We use the average silhouette width, separation and other quantities as quality measures for genotyping classification. We form robust statistical models based on the classification results and use these models to make genotype calls and calculate quality measures of calls. We apply our algorithms to several different genotyping microarrays. We use reference types, informative Mendelian relationship in families, and leave-one-out cross validation to verify our results. The concordance rates with the single base extension reference types are 99.36% for the SNPs on autosomes and 99.64% for the SNPs on sex chromosomes. The concordance of the leave-one-out test is over 99.5% and is 99.9% higher for AA, AB and BB cells. We also provide a method to determine the gender of a sample based on the heterozygous call rate of SNPs on the X chromosome. See http://www.affymetrix.com for further information. The microarray data will also be available from the Affymetrix web site. AVAILABILITY: The algorithms will be available commercially in the Affymetrix software package.
BACKGROUND: There have been no published reports comparing the CYP450 GeneChip microarray assay with more standard methods of genetic testing. METHODS: We collected 20-mL blood samples from 236 volunteers for DNA isolation and testing before each individual ingested 60 mg of dextromethorphan, and collected their urine. CYP2D6 alleles *3 to *7, *9, *17, and *41, and multiple CYP2D6 gene copies were tested by allele-specific PCR (AS-PCR), whereas alleles *2 to *4 and *6 to *11 were tested by the Affymetrix CYP450 GeneChip assay. Five of the CYP2D6 alleles (*3, *4, *6, *7, and *9) were tested by both AS-PCR and the CYP450 GeneChip assay in an independent and blinded fashion in 232 of the 236 healthy volunteers. The combined CYP2D6 genotype from both methods was used to divide the population into four subgroups, poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs), and ultrarapid metabolizers (UMs), based on their relative function and ability to express the CYP2D6 gene. The urinary elimination of dextromethorphan was assessed in each of these CYP2D6 subgroups. RESULTS: The CYP2D6*3, *4, *6, *7, and *9 alleles showed a high degree of concordance between the CYP450 GeneChip and AS-PCR methods (>99% concordance). The mean (SD) of the log[dextromethorphan metabolic ratio (MR)] in the four CYP2D6 subgroups was PM = 0.49 (0.38); IM = -1.24 (0.53); EM = -2.35 (0.61); and UM = -2.43 (0.38). CONCLUSIONS: Oligonucleotide microarray technology is an efficient and reliable way to test for CYP2D6 gene variation based on five alleles compared by separate methods. The methodology is influenced by the quality and amount of DNA present. The log(dextromethorphan MR) is a highly variable index that appears to reflect the crude nature of the dextromethorphan MR as an indicator of CYP2D6 in vivo enzyme activity.