Motivation: De novo variant (DNV) calling typically relies on heuristic filters intrinsic to specific platforms and variant calling algorithms. FreeBayes and neural network approaches have overcome this limitation for variant calling, and we implemented a similar approach for DNV identification. Results: We developed a DNV calling framework that uses Genome Analysis Toolkit (GATK), FreeBayes and a neural network trained on Integrative Genomics Viewer pile-up plots (IGVbot). We identified DNVs in 2,390 WGS trios and benchmarked results against heuristics based on GATK parameters. Results were validated in silico and with Sanger sequencing, with the latter showing true positive rates of 98.4% and 97.3% for SNVs and indels, respectively. Taken together we describe a scalable framework for DNV identification based on both FreeBayes and neural network methods. Availability: Source code and documentation are available at https://github.com/ShenLab/igvclassifier and https://github.com/frichter/dnv_pipeline under the MIT license. Contact:

53Background 54The contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital 55 heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and 56 cardiovascular tissue has not been determined. 58Results 59We developed a computational method, Expectation-Maximization-based detection of Mosaicism (EM-60 mosaic), to analyze mosaicism in exome sequences of 2530 CHD proband-parent trios. EM-mosaic 61 detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 62 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac 63 tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 64 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic 65 variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were 66 confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, 67 suggesting a role in CHD. The frequency of mosaic variants above 10% mosaicism was 0.13/person in 68 blood and 0.14/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available 69 revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele 70 fraction. 72 Conclusions 73We estimate that ~1% of CHD probands have a mosaic variant detectable in blood that could contribute 74 to cardiac malformations, particularly those damaging variants expressed at higher allele fraction 75 compared to benign variants. Although blood is a readily-available DNA source, cardiac tissues analyzed 76 contributed ~5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses. 77 78 Keywords 79 Mosaic, Somatic, Congenital Heart Disease, Exome Sequencing 80 2 Background 81 Mosaicism results from somatic mutations that arise post-zygotically in an early embryonic cell, 82 resulting in two or more cell populations with distinct genotypes in the developing embryo {Biesecker 83 2013}. The developmental status of the early embryonic cell at the time of mutagenesis determines the 84 proportion of variant-carrying cells and the tissue distribution of these cells in the post-natal child {Acuna-85 Hidalgo 2015}. While germline variants have a variant allele frequency (VAF) of 0.5, somatic mosaic 86 variants have a significantly lower VAF. 87 Post-zygotic mosaic mutations have been implicated in several diseases including non-malignant 88 developmental disorders such as overgrowth syndromes {Poduri 2013; Lindhurst 2012; Kurek 2016}, 89 structural brain malformations {Poduri 2012; Jamuar 2014; Riviere 2012; Lee 2012}, epilepsy {Stosser 90 2018}, and autism spectrum disorder {Lim 2017; Krupp 2017; Freed 2016; Dou 2017}. Recent analyses 91 also identified mosaic variants in a cohort of patients with congenital heart disease (CHD) {Manheimer 92 2018}, but the prev...