Copy number variants (CNVs) play important roles in a number of human diseases and in pharmacogenetics. Powerful methods exist for CNV detection in whole genome sequencing (WGS) data, but such data are costly to obtain. Many disease causal CNVs span or are found in genome coding regions (exons), which makes CNV detection using whole exome sequencing (WES) data attractive. If reliably validated against WGS-based CNVs, exome-derived CNVs have potential applications in a clinical setting. Several algorithms have been developed to exploit exome data for CNV detection and comparisons made to find the most suitable methods for particular data samples. The results are not consistent across studies. Here, we review some of the exome CNV detection methods based on depth of coverage profiles and examine their performance to identify problems contributing to discrepancies in published results. We also present a streamlined strategy that uses a single metric, the likelihood ratio, to compare exome methods, and we demonstrated its utility using the VarScan 2 and eXome Hidden Markov Model (XHMM) programs using paired normal and tumour exome data from chronic lymphocytic leukaemia patients. We use array-based somatic CNV (SCNV) calls as a reference standard to compute prevalence-independent statistics, such as sensitivity, specificity and likelihood ratio, for validation of the exome-derived SCNVs. We also account for factors known to influence the performance of exome read depth methods, such as CNV size and frequency, while comparing our findings with published results.

UNLABELLED: Linkage disequilibrium (LD) maps increase power and precision in association mapping, define optimal marker spacing and identify recombination hot-spots and regions influenced by natural selection. Phase II of HapMap provides approximately 2.8-fold more single nucleotide polymorphisms (SNPs) than phase I for constructing higher resolution maps. LDMAP-cluster, is a parallel program for rapid map construction in a Linux environment used here to construct genome-wide LD maps with >8.2 million SNPs from the phase II data. AVAILABILITY: The LD maps, LDMAP-cluster and documentation are available from: http://www.som.soton.ac.uk/research/geneticsdiv/epidemiology/LDMAP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Integrated maps are useful for gene mapping and establishing the relationship between recombination and sequence. In this paper we describe algorithms and their implementation for constructing sequence-based integrated maps of the human chromosomes, which are presented in LDB2000, a web based resource. Gene mapping efforts are now focussing on linkage disequilibrium mapping and extension of the integrated map to represent the extent of linkage disequilibrium in different genomic regions would further increase the utility of these maps. RESULTS: Sequence-based integrated maps have been completed for chromosomes 21 and 22. These maps provide locations for genes and polymorphic markers in sequence and on genetic linkage, radiation hybrid and cytogenetic scales. Single nucleotide polymorphisms associated with genes in the maps are also included and their sequence locations indicated. Related locus information, such as aliases and expression information, can be searched on the WWW site.