In the analysis of DNA sequences on related individuals, most methods strive to incorporate as much information as possible, with little or no attention paid to the issue of statistical significance. For example, a modern workstation can easily handle the computations needed to perform a large-scale genome-wide inheritance-by-descent (IBD) scan, but accurate assessment of the significance of that scan is often hindered by inaccurate approximations and computationally intensive simulation. To address these issues, we developed gLOD-a test of co-segregation that, for large samples, models chromosome-specific IBD statistics as a collection of stationary Gaussian processes. With this simple model, the parametric bootstrap yields an accurate and rapid assessment of significance-the genome-wide corrected P-value. Furthermore, we show that (i) under the null hypothesis, the limiting distribution of the gLOD is the standard Gumbel distribution; (ii) our parametric bootstrap simulator is approximately 40 000 times faster than gene-dropping methods, and it is more powerful than methods that approximate the adjusted P-value; and, (iii) the gLOD has the same statistical power as the widely used maximum Kong and Cox LOD. Thus, our approach gives researchers the ability to determine quickly and accurately the significance of most large-scale IBD scans, which may contain multiple traits, thousands of families and tens of thousands of DNA sequences.

T1D pedigreeThis is a simple text file containing the biological relationships of individuals across 422 affected families. Each affected family was ascertained through a single proband with type 1 diabetes (T1D). This file is in the standard MERLIN pedigree format, with the first 6 columns specifying relationships, and the remaining columns specifying genotypes.wg.scan.pedT1D mapFor each marker, this simple text file gives the name, the chromosome, and the chromosome-specific location. The order of the markers in this file, corresponds to the order of the columns in 'T1D pedigree'. In particular, there are 3697 markers in 'T1D map', which means that there are (6 + 2 * 3697) = 7400 columns in 'T1D pedigree'.wg.scan.map