@article {114,
	title = {A structural variation reference for medical and population genetics.},
	journal = {Nature},
	volume = {581},
	year = {2020},
	month = {2020 05},
	pages = {444-451},
	abstract = {<p>Structural variants (SVs) rearrange large segments of DNA and can have profound consequences in evolution and human disease. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral in the interpretation of single-nucleotide variants (SNVs). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54\% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29\% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9\% of samples, and estimate that 0.13\% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings. This SV resource is freely distributed via the gnomAD browser and will have broad utility in population genetics, disease-association studies, and diagnostic screening.</p>},
	keywords = {Continental Population Groups, Disease, Female, Genetic Testing, Genetic Variation, Genetics, Medical, Genetics, Population, Genome, Human, Genotyping Techniques, Humans, Male, Middle Aged, Mutation, Polymorphism, Single Nucleotide, Reference Standards, Selection, Genetic, Whole Genome Sequencing},
	issn = {1476-4687},
	doi = {10.1038/s41586-020-2287-8},
	author = {Collins, Ryan L and Brand, Harrison and Karczewski, Konrad J and Zhao, Xuefang and Alf{\"o}ldi, Jessica and Francioli, Laurent C and Khera, Amit V and Lowther, Chelsea and Gauthier, Laura D and Wang, Harold and Watts, Nicholas A and Solomonson, Matthew and O{\textquoteright}Donnell-Luria, Anne and Baumann, Alexander and Munshi, Ruchi and Walker, Mark and Whelan, Christopher W and Huang, Yongqing and Brookings, Ted and Sharpe, Ted and Stone, Matthew R and Valkanas, Elise and Fu, Jack and Tiao, Grace and Laricchia, Kristen M and Ruano-Rubio, Valentin and Stevens, Christine and Gupta, Namrata and Cusick, Caroline and Margolin, Lauren and Taylor, Kent D and Lin, Henry J and Rich, Stephen S and Post, Wendy S and Chen, Yii-Der Ida and Rotter, Jerome I and Nusbaum, Chad and Philippakis, Anthony and Lander, Eric and Gabriel, Stacey and Neale, Benjamin M and Kathiresan, Sekar and Daly, Mark J and Banks, Eric and MacArthur, Daniel G and Talkowski, Michael E}
}
@article {45,
	title = {Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects.},
	journal = {Nat Commun},
	volume = {9},
	year = {2018},
	month = {2018 10 02},
	pages = {4038},
	abstract = {<p>Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.</p>},
	keywords = {Genome, Human, Human Genetics, Humans, Whole Genome Sequencing},
	issn = {2041-1723},
	doi = {10.1038/s41467-018-06159-4},
	author = {Regier, Allison A and Farjoun, Yossi and Larson, David E and Krasheninina, Olga and Kang, Hyun Min and Howrigan, Daniel P and Chen, Bo-Juen and Kher, Manisha and Banks, Eric and Ames, Darren C and English, Adam C and Li, Heng and Xing, Jinchuan and Zhang, Yeting and Matise, Tara and Abecasis, Goncalo R and Salerno, Will and Zody, Michael C and Neale, Benjamin M and Hall, Ira M}
}
