A unified approach for quantifying, testing and correcting population stratification in case-control association studies

The HapMap project has given case-control association studies a unique opportunity to uncover the genetic basis of complex diseases. However, persistent issues in such studies remain the proper quantification of, testing for, and correction for population stratification (PS). In this paper, we present the first unified paradigm that addresses all three fundamental issues within one statistical framework. Our unified approach makes use of an omnibus quantity (delta), which can be estimated in a case-control study from suitable null loci. We show how this estimated value can be used to quantify PS, to statistically test for PS, and to correct for PS, all in the context of case-control studies. Moreover, we provide guidelines for interpreting values of delta in association studies (e.g., at alpha = 0.05, a delta of size 0.416 is small, a delta of size 0.653 is medium, and a delta of size 1.115 is large). A novel feature of our testing procedure is its ability to test for either strictly any PS or only 'practically important' PS. We also performed simulations to compare our correction procedure with Genomic Control (GC). Our results show that, unlike GC, it maintains good Type I error rates and power across all levels of PS.     

Fire,landscape change and models of small mammal habitat suitability at multiple spatial scales

Fire is an important process in many ecosystems, but inappropriate fire regimes can adversely affect biodiversity. We identified a naturally flammable heathy woodland ecosystem where the use of planned fire had increased the extent of older vegetation, and quantified the abundance of two small native mammals in this landscape (silky mouse Pseudomys apodemoides and heath rat P. shortridgei). We defined four time‐since‐fire (TSF) categories representing a 2‐ to 55‐year post‐fire sequence and, on the basis of a habitat accommodation model, predicted that both species would select younger age‐classes over older ones. We also predicted that (i) much of the variance in vegetation structure would remain unexplained by TSF and (ii) statistical models of mammal abundance and occupancy including structural variables as predictors would be better than models including TSF. Pseudomys apodemoides selected 17‐ to 23‐year‐old sites, while there was no evidence that P. shortridgei selected a particular TSF category, findings that were inconsistent with our predictions. In line with our predictions, relatively large portions of the variance in vegetation structure remained unexplained by TSF (adjustedr² for four structural variables: 0.24, 0.29, 0.35 and 0.57), and in three of four cases there was strong evidence that statistical models of mammal abundance and occupancy including structural variables were better than those including TSF. At the site scale (hectares), P. shortridgei abundance was positively related to the cover of dead material at the base of Xanthorrhoea plants and at the trap scale (metres), the trapability of both species was significantly related to vegetation volume at 0–20 cm. Our findings suggest that TSF may not be a good proxy for either vegetation structure or species abundance/occupancy.