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NEW: Only meta-analysis results with P-values <0.00001 are displayed in this table. Please contact us to request a list of other at least nominally significant meta-analysis results.
Per gene/locus only one (i.e. the best associated) marker is listed, ranking is based on P-value. All results are assessed for their epidemiological credibility using two methods:
1. The HuGENet interim criteria for the cumulative assessment of genetic associations: These criteria (Ioannidis et al, 2008a; Khoury et al, 2009) take into account amount of evidence (i.e. sample size, measured as "N minor"), consistency of replication (i.e. heterogeneity across studies, measured as "I2" [NB: this criterion does not apply [n.a.] to genome-wide significant findings [P < 5.0E-8]), and protection from bias ("Bias reason"). Overall epidemiological credibility is graded as "A" (=strong) if associations received three A grades, "B" (=moderate) if they received at least one B grade but no C grades, and "C" (=weak) if they received a C grade in any of the three assessment criteria.
2. Bayesian analyses: For this assessment we calculate Bayes factors (expressed here as log10-values) assuming an average non-null odds ratio of 1.15 using a spike and smear prior distribution of effects (as described in Ioannidis, 2008b) Generally, a logBF ≥5, which suggests that the data increase over 100,000-fold the odds of a given finding being true vs. not true, is considered as strong support in the context of genetic association studies (Stephens and Balding, 2009).
For more details see "Top Results Methods" and reference below.
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References:
Ioannidis JP, Boffetta P, Little J, O'Brien TR, Uitterlinden AG, Vineis P, Balding DJ, Chokkalingam A, Dolan SM, Flanders WD, Higgins JP, McCarthy MI, McDermott DH, Page GP, Rebbeck TR, Seminara D, Khoury MJ (2008a) "Assessment of cumulative evidence on genetic associations: interim guidelines." Int J Epidemiol 37(1):120-32. Abstract
Ioannidis JP (2008b) "Effect of Formal Statistical Significance on the Credibility of Observational Associations." Am J Epidemiol 168:374-383. Abstract
Khoury MJ, Bertram L, Boffetta P, Butterworth AS, Chanock SJ, Dolan SM, Fortier I, Garcia-Closas M, Gwinn M, Higgins JP, Janssens AC, Ostell J, Owen RP, Pagon RA, Rebbeck TR, Rothman N, Bernstein JL, Burton PR, Campbell H, Chockalingam A, Furberg H, Little J, O'Brien TR, Seminara D, Vineis P, Winn DM, Yu W, Ioannidis JP (2009) "Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases." Am J Epidemiol 170(3):269-79. Abstract
Stephens M, Balding DJ (2009) "Bayesian statistical methods for genetic association studies" Nat Rev Genet 10(10):681-90. Abstract
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