Biomedical subjects

Ben W Tripp

Publications and source records attributed to Ben W Tripp.

4 recordsLinked to original sources

PubMed2006

MACGT: multi-dimensional automated clustering genotyping tool for analysis of microarray-based mini-sequencing data.

SUMMARY: Multi-dimensional Automated Clustering Genotyping Tool (MACGT) is a Java application that clusters complex multi-dimensional vector data derived from single nucleotide polymorphism (SNP) genotyping experiments using mini-sequencing based microarray chemistries such as arrayed primer extension (APEX). Spot intensity output files from microarray experiments across multiple samples are imported into MACGT. The datasets can include four channels of intensity data for each spot, replica spots for each SNP probe and multiple probe types (APEX and allele-specific APEX probes) on both DNA strands for each SNP. MACGT automatically clusters these multi-dimensionality datasets for each SNP across multiple samples. Incorporation of additional array datasets from known samples that have previously validated SNP genotype calls allows unknown samples to be automatically assigned a genotype based on the clustering, along with numerical measures of confidence for each genotype call. Calling accuracy by MACGT exceeds 98% when applied to genotyping data from APEX microarrays, and can be increased to >99.5% by applying thresholds to the confidence measures.

Algorithms↗

PubMed2006

Deoxynucleotides can replace dideoxynucleotides in minisequencing by arrayed primer extension.

Scientific literature describing arrayed primer extension and other array-based minisequencing technologies consistently cite the requirement for four fluorescent dideoxynucleotides (with concomitant absence/inactivation of deoxynucleotides) to ensure single-base extension and thus sequence-specific intensity data that can be interpreted as a base call or genotype. We present compelling evidence that fluorescent deoxynucleotides can reliably be used in microarray minisequencing experiments, generating fluorescent sequence extension intensity profiles that are homologous to the single-base extensions obtained with terminator dideoxynucleotides. Due to the almost 10-fold higher costs (and limited fluorophore choice) of many commercially available fluorescent dideoxynucleotides, compared to fluorescent deoxynucleotides, as well as other potentially constraining intellectual property and licensing issues, this hitherto dismissed microarray chemistry represents an important reevaluation in the field of array-based genotyping and related enzymology.

Chromosome Mapping↗

PubMed2004

SNP Chart: an integrated platform for visualization and interpretation of microarray genotyping data.

UNLABELLED: SNP Chart is a Java application for the visualization and interpretation of microarray genotyping data primarily derived from arrayed primer extension-based chemistries. Spot intensity output files from microarray analysis tools are imported into SNP Chart, together with a multi-channel TIFF image of the original array experiment and a list of the actual single nucleotide polymorphisms (SNPs) being tested. Data from different and/or replicate probes that interrogate the same SNP, but that are scattered across the array grid, can be reassembled into a single chart format, specific for the SNP. This allows a quick and very effective 'visualization'/'quality control' of the data from multiple probes for the same SNP that can be easily interpreted and manually scored as a genotype. AVAILABILITY: http://www.snpchart.ca.

Computer Graphics↗

PubMed2004

Microarray genotyping resource to determine population stratification in genetic association studies of complex disease.

We have developed a robust microarray genotyping chip that will help advance studies in genetic epidemiology. In population-based genetic association studies of complex disease, there could be hidden genetic substructure in the study populations, resulting in false-positive associations. Such population stratification may confound efforts to identify true associations between genotype/haplotype and phenotype. Methods relying on genotyping additional null single nucleotide polymorphism (SNP) markers have been proposed, such as genomic control (GC) and structured association (SA), to correct association tests for population stratification. If there is an association of a disease with null SNPs, this suggests that there is a population subset with different genetic background plus different disease susceptibility. Genotyping over 100 null SNPs in the large numbers of patient and control DNA samples that are required in genetic association studies can be prohibitively expensive. We have therefore developed and tested a resequencing chip based on arrayed primer extension (APEX) from over 2000 DNA probe features that facilitate multiple interrogations of each SNP, providing a powerful, accurate, and economical means to simultaneously determine the genotypes at 110 null SNP loci in any individual. Based on 1141 known genotypes from other research groups, our GC SNP chip has an accuracy of 98.5%, including non-calls.

Animals↗