Population structure at different minor allele frequency levels.

Inferring population genetic structure from large-scale genotyping of single-nucleotide polymorphisms or variants is an important technique for studying the history and distribution of extant human populations, but it is also a very important tool for adjusting tests of association. However, the structures inferred depend on the minor allele frequency of the variants; this is very important when considering the phenotypic association of rare variants. Using the Genetic Analysis Workshop 18 data set for 142 unrelated individuals, which includes genotypes for many rare variants, we study the following hypothesis: the difference in detected structure is the result of a "scale" effect; that is, rare variants are likely to be shared only locally (smaller scale), while common variants can be spread over longer distances.

THE DUALITY DIAGRAM IN DATA ANALYSIS: EXAMPLES OF MODERN APPLICATIONS.

Today's data-heavy research environment requires the integration of different sources of information into structured datasets that can not be analyzed as simple matrices. We introduce an old technique, known in the European data analyses circles as the Duality Diagram Approach, put to new uses through the use of a variety of metrics and ways of combining different diagrams together. This issue of the Annals of Applied Statistics contains contemporary examples of how this approach provides solutions to hard problems in data integration.

Gene, region and pathway level analyses in whole-genome studies.

In the setting of genome-wide association studies, we propose a method for assigning a measure of significance to pre-defined sets of markers in the genome. The sets can be genes, conserved regions, or groups of genes such as pathways. Using the proposed methods and algorithms, evidence for association between a particular functional unit and a disease status can be obtained not just by the presence of a strong signal from a SNP within it, but also by the combination of several simultaneous weaker signals that are not strongly correlated.

A signature of evolutionary constraint on a subset of ectopically expressed olfactory receptor genes.

Olfactory receptor (OR) genes constitute the basis for the sense of smell. It has long been observed that a subset of mammalian OR genes are expressed in nonolfactory tissues, in addition to their expression in the olfactory epithelium. However, it is unknown whether OR genes have alternative functions in the nonolfactory tissues.

Characterizing the expression of the human olfactory receptor gene family using a novel DNA microarray.

Background: Olfactory receptor (OR) genes were discovered more than a decade ago, when Buck and Axel observed that, in rats, certain G-protein coupled receptors are expressed exclusively in the olfactory epithelium. Subsequently, protein sequence similarity was used to identify entire OR gene repertoires of a number of mammalian species, but only in mouse were these predictions followed up by expression studies in olfactory epithelium. To rectify this, we have developed a DNA microarray that contains probes for most predicted human OR loci and used that array to examine OR gene expression profiles in olfactory epithelium tissues from three individuals.

Complex life cycles and density dependence: assessing the contribution of egg mortality to amphibian declines.

In the last decade there has been increasing evidence of amphibian declines from relatively pristine areas. Some declines are hypothesized to be the result of egg mortality caused by factors such as elevated solar UV-B irradiation, chemical pollutants, pathogenic fungi, and climate change. However, the population-level consequences of egg mortality have not been examined explicitly, and may be complicated by density dependence in intervening life-history stages.