@article {54, title = {Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel.}, journal = {Genet Med}, volume = {21}, year = {2019}, month = {2019 Sep}, pages = {2135-2144}, abstract = {

PURPOSE: To provide a validated method to confidently identify exon-containing copy-number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs.

METHODS: DNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a batch of samples, when the target log ratio of the sample to the batch median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap).

RESULTS: Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation, and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multiexon and 29 single-exon CNVs with high C-scores were assessed by~Multiplex Ligation-dependent Probe Amplification (MLPA).

CONCLUSION: Atlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We propose guidelines and criteria to identify high confidence single-exon CNVs.

}, issn = {1530-0366}, doi = {10.1038/s41436-019-0475-4}, author = {Chiang, Theodore and Liu, Xiuping and Wu, Tsung-Jung and Hu, Jianhong and Sedlazeck, Fritz J and White, Simon and Schaid, Daniel and Andrade, Mariza de and Jarvik, Gail P and Crosslin, David and Stanaway, Ian and Carrell, David S and Connolly, John J and Hakonarson, Hakon and Groopman, Emily E and Gharavi, Ali G and Fedotov, Alexander and Bi, Weimin and Leduc, Magalie S and Murdock, David R and Jiang, Yunyun and Meng, Linyan and Eng, Christine M and Wen, Shu and Yang, Yaping and Muzny, Donna M and Boerwinkle, Eric and Salerno, William and Venner, Eric and Gibbs, Richard A} } @article {9, title = {Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.}, journal = {N Engl J Med}, volume = {376}, year = {2017}, month = {2017 Jan 05}, pages = {21-31}, abstract = {

BACKGROUND: Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes.

METHODS: We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology.

RESULTS: A molecular diagnosis was rendered for 2076 of 7374 patients (28.2\%); among these patients, 101 (4.9\%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8\% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7\% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7\% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9\%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77{\texttimes}10).

CONCLUSIONS: In our study, we found multiple molecular diagnoses in 4.9\% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).

}, keywords = {Exome, Genetic Diseases, Inborn, Genetic Variation, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Phenotype, Retrospective Studies, Sequence Analysis, DNA}, issn = {1533-4406}, doi = {10.1056/NEJMoa1516767}, author = {Posey, Jennifer E and Harel, Tamar and Liu, Pengfei and Rosenfeld, Jill A and James, Regis A and Coban Akdemir, Zeynep H and Walkiewicz, Magdalena and Bi, Weimin and Xiao, Rui and Ding, Yan and Xia, Fan and Beaudet, Arthur L and Muzny, Donna M and Gibbs, Richard A and Boerwinkle, Eric and Eng, Christine M and Sutton, V Reid and Shaw, Chad A and Plon, Sharon E and Yang, Yaping and Lupski, James R} }