@article {126,
	title = {Epilepsy subtype-specific copy number burden observed in a genome-wide study of 17 458 subjects.},
	journal = {Brain},
	volume = {143},
	year = {2020},
	month = {2020 07 01},
	pages = {2106-2118},
	abstract = {<p>Cytogenic testing is routinely applied in most neurological centres for severe paediatric epilepsies. However, which characteristics of copy number variants (CNVs) confer most epilepsy risk and which epilepsy subtypes carry the most CNV burden, have not been explored on a genome-wide scale. Here, we present the largest CNV investigation in epilepsy to date with 10 712 European epilepsy cases and 6746 ancestry-matched controls. Patients with genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, and developmental and epileptic encephalopathy were included. All samples were processed with the same technology and analysis pipeline. All investigated epilepsy types, including lesional focal epilepsy patients, showed an increase in CNV burden in at least one tested category compared to controls. However, we observed striking differences in CNV burden across epilepsy types and investigated CNV categories. Genetic generalized epilepsy patients have the highest CNV burden in all categories tested, followed by developmental and epileptic encephalopathy patients. Both epilepsy types also show association for deletions covering genes intolerant for truncating variants. Genome-wide CNV breakpoint association showed not only significant loci for genetic generalized and developmental and epileptic encephalopathy patients but also for lesional focal epilepsy patients. With a 34-fold risk for developing genetic generalized epilepsy, we show for the first time that the established epilepsy-associated 15q13.3 deletion represents the strongest risk CNV for genetic generalized epilepsy across the whole genome. Using the human interactome, we examined the largest connected component of the genes overlapped by CNVs in the four epilepsy types. We observed that genetic generalized epilepsy and non-acquired focal epilepsy formed disease modules. In summary, we show that in all common epilepsy types, 1.5-3\% of patients carry epilepsy-associated CNVs. The characteristics of risk CNVs vary tremendously across and within epilepsy types. Thus, we advocate genome-wide genomic testing to identify all disease-associated types of CNVs.</p>},
	keywords = {DNA Copy Number Variations, Epilepsy, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male},
	issn = {1460-2156},
	doi = {10.1093/brain/awaa171},
	author = {Niestroj, Lisa-Marie and Perez-Palma, Eduardo and Howrigan, Daniel P and Zhou, Yadi and Cheng, Feixiong and Saarentaus, Elmo and N{\"u}rnberg, Peter and Stevelink, Remi and Daly, Mark J and Palotie, Aarno and Lal, Dennis}
}
@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}
}
