Variant calling procedure in the Exon Pilot Project. (a) The SNP calling procedure. Read alignment and SNP calling were carried out by Boston College (BC) and the Broad Institute (BI) independently using complementary pipelines. The call sets were intersected for the final release. (b) The INDEL calling procedure. INDELs were called on the Illumina and Roche 454 platforms. The sequence was processed on three independent pipelines, Illumina at the Baylor College of Medicine Human Genome Sequencing Center (BCM-HGSC), Illumina at BI, and Roche 454 at BCM-HGSC. The union of the three call sets formed the final call set. The Venn diagram provided is not to scale. AB: allele balance; MSA: multiple sequence alignment; QDP: discovery confidence of the variant divided by the depth of coverage; SW: software.

Sensitivity measurement of Exon Pilot SNP calls. Sensitivity was estimated by comparison to variants in HapMap, version 3.2, in regions overlapping the Exon Pilot exon targets. Circles connected with solid lines show the number of SNPs in such regions in HapMap, the Exon Pilot, and the Low Coverage Pilot project, as a function of alternative allele count. Dashed lines indicate the calculated sensitivity against the HapMap 3.2 variants. Sensitivity is shown for three sets of calls: the intersection between filtered call sets from BC and BI (most stringent); the union between the BC and BI filtered call sets; and the union between the BC and BI raw, unfiltered call sets (most permissive).

The distribution of functionally characterized Exon Pilot SNPs according to minor allele frequency within all samples. (a) Annotation according to amino acid change. The distribution of the Exon Pilot coding SNPs classified according to amino acid change introduced by the alternative allele (silent, missense, and nonsense) is shown, as a function of AF. Both missense and nonsense variants are enriched in the rare allele frequency bin compared to silent variants, with highly significant P << 10^-16. The differences remain significant after correcting for the differential error rates in different bins (P << 10^-16 for missense, and P << 10^-5 for nonsense). (b) Computational prediction of functional impact. The distribution of SNPs classified according to functional impact (benign, possibly damaging, and damaging) based on computational predictions by the SIFT and PolyPhen-2 programs, as a function of allele frequency. In case of disagreement, the more severe classification was used. Silent SNPs are also shown, as neutral internal control for each bin. The damaging variants are highly enriched in the rare bin compared to the silent variants with highly significant P << 10^-16. This remains significant after correcting for the differential error rates in different bins (P << 10^-16). (a-b) Allele frequency was binned as follows: low frequency, <0.01; intermediate frequency, 0.01 to 0.1; and common, >0.1. The fraction of SNPs also called in the 1000 Genomes Low Coverage Pilot is indicated by blue shading, in each category. (c) Functional impact among variants shared with HGMD. Functional predictions using SIFT and PolyPhen-2 for the variants shared between the Exon Pilot and HGMD-DM, as a function of the disease allele frequency bin (<0.01, 0.01 to 0.1, and >0.1). Color represents predicted damage (green, benign; orange, possibly damaging; red, damaging); open sections represent variants shared between the Exon Pilot and Low Coverage Pilot, while solid sections represent variants observed only in the Exon Pilot.

Coverage distribution. (a) Coverage across exon targets. Per-sample read depth of the 8,000 targets in all CEU and TSI samples. Targets were ordered by median per-sample read coverage (black). For each target, the upper and lower decile coverage value is also shown. Upper panel: samples sequenced with Illumina. Lower panel: samples sequenced with 454. (b) Cumulative distribution of base coverage at every target position in every sample. Depth of coverage is shown for all Exon Pilot capture targets, ordered according to decreasing coverage. Blue, samples sequenced by Illumina only; red, 454 only; green, all samples regardless of sequencing platform.

Allele frequency properties of the Exon Pilot SNP variants. (a) The allele frequency spectra (AFS) for each of the seven population panels sequenced in this study, projected to 100 chromosomes, using chimpanzee as a polarizing out-group. The expected AFS for a constant population undergoing neutral evolution, θ/x, corresponds to a straight line of slope -1 on this graph (shown here for the average value of the Watterson's θ nucleotide diversity parameter over the seven populations). Individuals with low coverage or high HapMap discordance (section 9, 'Allele sharing among populations', in Additional file 1) have not been used in this analysis. (b) Comparison of the site frequency spectra obtained from silent and missense sites in the Exon Pilot, as well as intergenic regions from the HapMap resequencing of ENCODE regions, within CEU population samples. The frequency spectra are normalized to 1, and S indicates the total number of segregating sites in each AFS. Individuals with low coverage or high HapMap discordance (section 9 in Additional file 1) have not been used in this analysis. (c) Allele frequency spectrum considering all 697 Exon Pilot samples. The inset shows the AFS at low alternative allele counts, and the fraction of known variant sites (defined as the fraction of SNPs from our study that were also present in dbSNP version 129).

Allele sharing among populations in the Exon Pilot versus ENCODE intergenic SNPs. The probability that two minor alleles, sampled at random without replacement among all minor alleles, come from the same population, different populations on the same continent, or different continents, displayed according to minor allele frequency bin (<0.01, 0.01 to 0.1, and 0.1 to 0.5). For comparison, we also show the expected level of sharing in a panmictic population, which is independent of AF. The ENCODE and the Exon Pilot data have different sample sizes for each population panel, which could impact sharing probabilities. We therefore calculated the expected sharing based on subsets of equal size, corresponding to 90% of the smallest sample size for each population (section 9, 'Allele sharing among populations', in Additional file 1). To reduce possible biases due to reduced sensitivity in rare variants, only high-coverage sites were used, and individuals with overall low coverage or poor agreement with ENCODE genotypes were discarded. Error bars indicate the 95% confidence interval based on bootstrapping at individual variant sites.