So many correlated tests, so little time! Rapid adjustment of P values for multiple correlated tests.

By Karen N. Conneely, Michael Boehnke. American Journal of Human Genetics, 2007

477 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Plant Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7a31408b1b25c4eb8cc6ae7c281b77dc66ef0b7a

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In Management Science and Operations Research

In Plant Science

In Statistics and Probability

Citations in the corpus

Integrating Functional Data to Prioritize Causal Variants in Statistical Fine-Mapping Studies (2014, background): “and relate the causal set of SNPs to the observed association Zscores under a standard multivariate normal assumption [35,36,37] as:”
... and the Cross-Section of Expected Returns (2013, unknown): “Examples include Lin (2005), Conneely and Boehnke (2007), and Han, Kang, and Eskin (2009).”
Dissecting the genetics of complex traits using summary association statistics (2016, methodology): “The key insight of these approaches is that LD induces correlations between z-scores, which can be modeled using a multi-variate normal (MVN) distribution with variance equal to the LD correlation matrix 19 .”
Avoiding the high Bonferroni penalty in genome-wide association studies (2009, methodology): “…a large number of SNPs, e.g. 1M or 500K, are involved in the genetic association study, permutation tests become impractical for GWASs because it can take years to finish on a single modern PC if a substantial number of random shuffles are carried out [Conneely and Boehnke 2007; Gao, et al. 2008].”
Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches. (2012, methodology): “In fact, permutation tests have even been referred to as the “gold standard” of hypothesis testing (e.g., Conneely & Boehnke, 2007, p. 1158; Hesterberg, Monaghan, Moore, Clipson, & Epstein, 2003, p. 61).”
Simultaneous Statistical Inference (2014, background): “Applications of the projectionmethods under (asymptotic) normality discussed in this section to the field of genetics have been exemplified by Conneely and Boehnke (2007).”
Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics (2016, methodology): “In this work, we presented a new tool called Pascal (Pathway scoring algorithm) that specifically addresses both gene scoring and pathway enrichment, making significant advancement with respect to the state-of-the-art: First, our gene score calculation combines analytical and numerical solutions to ”