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A probabilistic method for the identification of de novo CNVs from maternal blood plasma sequencing. fCNV combines three types of data: allelic ratios, reflecting the changes in the expected observations of various alleles at SNP positions in the presence of the CNV; phasing information, allowing for the combining of allelic ratios across multiple SNP positions, thus improving the signal-to-noise ratio; and depth of coverage information reflecting the change in expected sequencing depth in the presence of the CNV. We apply the resulting method to simulated sequencing data, demonstrating promising results for CNVs >400 kb in length, and especially for CNVs of paternal origin.
FSDA / Fragment-Size Distribution Analysis
An alternative framework for identifying sub-chromosomal copy number variants in a fetal genome. This framework relies on the size-distribution of fragments in a sample, as fetal-origin fragments tend to be smaller than maternal-origin. By analyzing the local distribution of the cell-free DNA fragment sizes in each region our method allows for the identification of sub-megabase CNVs, even in the absence of SNP positions. To evaluate the accuracy of our method, we used a plasma sample with the fetal fraction of 13%, down-sampled it to samples with coverage of 10X to 40X and simulated samples with CNVs based on it. Our method had a perfect accuracy (both specificity and sensitivity) for detecting 5 Mbp CNVs, and after reducing the fetal fraction (to 11%, 9% and 7%), it could correctly identify 98.82% to 100% of the 5 megabase CNVs and had a true negative rate of 95.29% to 99.76%.
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