Evaluating coverage of genome-wide association studies
ABSTRACT Genome-wide association studies involving hundreds of thousands of SNPs in thousands of cases and controls are now underway. The first of many analytical challenges in these studies involves the choice of SNPs to genotype. It is not practical to construct a different panel of tag SNPs for each study, so the first generation of genome-wide scans will use predefined, commercially available marker panels, which will in part dictate their success or failure. We compare different approaches in use today, and show that although many of them provide substantial coverage of common variation in non-African populations, the precise extent is strongly dependent on the frequencies of alleles of interest and on specific considerations of study design. Overall, despite substantial differences in genotyping technologies, marker selection strategies and number of markers assayed, the first-generation high-throughput platforms all offer similar levels of genome coverage.
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ABSTRACT: Two recent studies [Newton-Cheh et al., Nature Genetics 41, 399-406 (2009); Pfeufer et al., Nature Genetics 41, 407-414 (2009)] identified an association, with genome-wide significance, between a single nucleotide polymorphism within the gene encoding RING finger protein 207 (RNF207) and the QT interval. We sought to determine the role of RNF207 in cardiac electrophysiology. Morpholino knockdown of RNF207 in zebrafish embryos resulted in APD prolongation, occasionally a 2:1 atrioventricular block and slowing of conduction velocity. Conversely, neonatal rabbit cardiomyocytes infected with RNF207-expressing adenovirus exhibited shortened APD. Using transfections of U-2 OS and HEK293 cells, western blot and immunocytochemistry data demonstrate that RNF207 and the HERG (human ether-a-go-go-related gene) potassium channel interact and co-localize. Furthermore, RNF207 overexpression significantly elevated total and membrane HERG protein and HERG-encoded current density by approximately 30-50%, which was dependent on the intact N-terminal RING domain of RNF207. Finally, co-expression of RNF207 and HSP70 increased HERG expression as compared to HSP70 alone. This effect was dependent on the C-terminus of RNF207. Taken together, the evidence is strong that RNF207 is an important regulator of action potential duration likely via effects on HERG trafficking and localization in a heat shock protein-dependent manner.Journal of Biological Chemistry 10/2014; 289(49). DOI:10.1074/jbc.M114.592295 · 4.60 Impact Factor
Conference Paper: Ensemble-based classifiers for prostate cancer diagnosis[Show abstract] [Hide abstract]
ABSTRACT: In this paper, we address microarray data sets dimensionality problem to achieve early and accurate diagnosis of prostate cancer without need to biopsy operation based rotation multiple classifier forest system. To evaluate the performance of presented approach, we present tests on different prostate data sets. The experimental results obtained, show that the overall accuracy offered by the employed technique is high compared with other machine learning techniques including random forest classifier, single decision trees and rough sets as well as features were reduced from 12600 features to 89 features using correlation filter method.2013 9th International Computer Engineering Conference (ICENCO); 12/2013
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ABSTRACT: Publisher’s description: This book presents the statistical aspects of designing, analyzing and interpreting the results of genome-wide association scans (GWAS studies) for genetic causes of disease using unrelated subjects. Particular detail is given to the practical aspects of employing the bioinformatics and data handling methods necessary to prepare data for statistical analysis. The goal in writing this book is to give statisticians, epidemiologists, and students in these fields the tools to design a powerful genome-wide study based on current technology. The other part of this is showing readers how to conduct analysis of the created study. This book provides a compendium of well-established statistical methods based upon single SNP associations. It also provides an introduction to more advanced statistical methods and issues. Knowing that technology, for instance large scale SNP arrays, is quickly changing, this text has significant lessons for future use with sequencing data. Emphasis on statistical concepts that apply to the problem of finding disease associations irrespective of the technology ensures its future applications. The author includes current bioinformatics tools while outlining the tools that will be required for use with extensive databases from future large scale sequencing projects. The author includes current bioinformatics tools while outlining additional issues and needs arising from the extensive databases from future large scale sequencing projects.