Assessments of the genotyping performance of exome capture and resequencing over the CCDS target. Exome capture sequence data were analyzed using our capture analysis pipeline (see Materials and methods; Figure 8), and genotype calls with consensus quality of at least 50 were used to determine the utility of solution exome capture for proper genotyping. These tests were performed with genotype gold standards prepared from the HapMap 3 panel and the trio pilot of 1000 Genomes Project (1000GP) for the two CEU and YRI trios used for this study (Table 3). In all panels, the color of the symbols designates the platform used, with green representing the NimbleGen platform (NM) and red representing the Agilent platform (AG). The label associated with the symbol identifies the sample using a two-letter code: the first letter identifies the trio (y for YRI and c for CEU) and the second letter identifies the family member (m for mother, f for father, and d for daughter). The shape of the symbols specifies the number of lanes of data used (rectangle for one lane, circle for two lanes, diamond for three lanes, and triangle for four lanes). (a, b) The y-axes show the percentage of the HapMap (a) and 1000 Genomes Project (b) gold standard positions that were successfully genotyped with a minimum consensus of 50; the x-axes show the percent of the called genotypes that disagree with the given gold standard genotypes. (c, d) Plots of sensitivity versus false discovery rates for the task of identifying variants: HapMap (c); 1000 Genomes Project (d). Sensitivity is defined as the percentage of positions with a variant genotype in the gold standard that have been called as variants from the exome capture data. The false discovery rate is defined as the percentage of variant calls from the exome capture data over the gold standard positions that do not have a variant genotype in the gold standard. (e, f) Plots of sensitivity versus false discovery rates for the task of identifying heterozygous variants: HapMap (e); 1000 Genomes Project (f).
Parla et al. Genome Biology 2011 12:R97 doi:10.1186/gb-2011-12-9-r97