31 research outputs found
Multiple tests of association with biological annotation metadata
We propose a general and formal statistical framework for multiple tests of
association between known fixed features of a genome and unknown parameters of
the distribution of variable features of this genome in a population of
interest. The known gene-annotation profiles, corresponding to the fixed
features of the genome, may concern Gene Ontology (GO) annotation, pathway
membership, regulation by particular transcription factors, nucleotide
sequences, or protein sequences. The unknown gene-parameter profiles,
corresponding to the variable features of the genome, may be, for example,
regression coefficients relating possibly censored biological and clinical
outcomes to genome-wide transcript levels, DNA copy numbers, and other
covariates. A generic question of great interest in current genomic research
regards the detection of associations between biological annotation metadata
and genome-wide expression measures. This biological question may be translated
as the test of multiple hypotheses concerning association measures between
gene-annotation profiles and gene-parameter profiles. A general and rigorous
formulation of the statistical inference question allows us to apply the
multiple hypothesis testing methodology developed in [Multiple Testing
Procedures with Applications to Genomics (2008) Springer, New York] and related
articles, to control a broad class of Type I error rates, defined as
generalized tail probabilities and expected values for arbitrary functions of
the numbers of Type I errors and rejected hypotheses. The resampling-based
single-step and stepwise multiple testing procedures of [Multiple Testing
Procedures with Applications to Genomics (2008) Springer, New York] take into
account the joint distribution of the test statistics and provide Type I error
control in testing problems involving general data generating distributions
(with arbitrary dependence structures among variables), null hypotheses, and
test statistics.Comment: Published in at http://dx.doi.org/10.1214/193940307000000446 the IMS
Collections (http://www.imstat.org/publications/imscollections.htm) by the
Institute of Mathematical Statistics (http://www.imstat.org
A Genetic Signature of Spina Bifida Risk from Pathway-Informed Comprehensive Gene-Variant Analysis
Despite compelling epidemiological evidence that folic acid supplements reduce the frequency of neural tube defects (NTDs) in newborns, common variant association studies with folate metabolism genes have failed to explain the majority of NTD risk. The contribution of rare alleles as well as genetic interactions within the folate pathway have not been extensively studied in the context of NTDs. Thus, we sequenced the exons in 31 folate-related genes in a 480-member NTD case-control population to identify the full spectrum of allelic variation and determine whether rare alleles or obvious genetic interactions within this pathway affect NTD risk. We constructed a pathway model, predetermined independent of the data, which grouped genes into coherent sets reflecting the distinct metabolic compartments in the folate/one-carbon pathway (purine synthesis, pyrimidine synthesis, and homocysteine recycling to methionine). By integrating multiple variants based on these groupings, we uncovered two provocative, complex genetic risk signatures. Interestingly, these signatures differed by race/ethnicity: a Hispanic risk profile pointed to alterations in purine biosynthesis, whereas that in non-Hispanic whites implicated homocysteine metabolism. In contrast, parallel analyses that focused on individual alleles, or individual genes, as the units by which to assign risk revealed no compelling associations. These results suggest that the ability to layer pathway relationships onto clinical variant data can be uniquely informative for identifying genetic risk as well as for generating mechanistic hypotheses. Furthermore, the identification of ethnic-specific risk signatures for spina bifida resonated with epidemiological data suggesting that the underlying pathogenesis may differ between Hispanic and non-Hispanic groups