A Comprehensive Map of Mobile Element Insertion Polymorphisms in Humans
Figure 3
Non-reference MEI validation and detection sensitivity.
a) Example of PCR gel chromatograph validation results. At this site, three of the 25 low coverage samples show two bands characteristic of heterozygous insertions. Two additional test samples (Pop80 and HeLa) also show the insertion allele. b) False detection rate estimates based on PCR experiments at random sites, broken down by element type (Alu, L1, SVA), algorithm (RP & SR), and dataset (LCP: low coverage pilot, TP: trio pilot). The false detection rate for Alu elements is uniformly <3% while the false detection rates for L1s and SVA element insertions approach 30%, with large error bars (95% confidence intervals) arising from relatively low statistics. c) Non-reference MEI detection overlap from trio samples NA12878 and NA19240. This level of overlap between two independent methods using independent sequence data corresponds to a detection sensitivity of roughly 70% for each algorithm and a combined detection sensitivity of 90% in these samples. d) Non-reference MEI detection sensitivity as a function of allele frequency in the low coverage dataset. PCR results for loci randomly selected from one method were used as a gold standard for the complementary method, and vice versa. PCR also provides an estimate of the allele frequency based on the 25 low coverage samples used for validation experiments. RP (blue) and SR (red) and the combined (black) detection sensitivities rise with frequency. One standard deviation confidence intervals are shown as shaded bars for the RP and SR algorithm, with black error bars for the combined RP+SR detection efficiency.