@article{MTMT:33832882,
	title = {Twist exome capture allows for lower average sequence coverage in clinical exome sequencing.},
	url = {https://m2.mtmt.hu/api/publication/33832882},
	author = {Yaldiz, Burcu and Kucuk, Erdi and Hampstead, Juliet and Hofste, Tom and Pfundt, Rolph and Corominas Galbany, Jordi and Rinne, Tuula and Yntema, Helger G and Hoischen, Alexander and Nelen, Marcel and Gilissen, Christian},
	doi = {10.1186/s40246-023-00485-5},
	journal-iso = {HUM GENOMICS},
	journal = {HUMAN GENOMICS},
	volume = {17},
	unique-id = {33832882},
	issn = {1473-9542},
	abstract = {Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques.We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection.We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques.},
	keywords = {Exome sequencing; genome sequencing; Uniformity of coverage},
	year = {2023},
	eissn = {1479-7364},
	orcid-numbers = {Balicza, Péter/0000-0001-8555-5467; Molnár, Mária Judit/0000-0001-9350-1864}
}

@article{MTMT:32119912,
	title = {Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases},
	url = {https://m2.mtmt.hu/api/publication/32119912},
	author = {Zurek, Birte and Ellwanger, Kornelia and Vissers, Lisenka E. L. M. and Schuele, Rebecca and Synofzik, Matthis and Topf, Ana and de, Voer Richarda M. and Laurie, Steven and Matalonga, Leslie and Gilissen, Christian and Ossowski, Stephan and 't, Hoen Peter A. C. and Vitobello, Antonio and Schulze-Hentrich, Julia M. and Riess, Olaf and Brunner, Han G. and Brookes, Anthony J. and Rath, Ana and Bonne, Gisele and Gumus, Gulcin and Verloes, Alain and Hoogerbrugge, Nicoline and Evangelista, Teresinha and Harmuth, Tina and Swertz, Morris and Spalding, Dylan and Hoischen, Alexander and Beltran, Sergi and Graessner, Holm},
	doi = {10.1038/s41431-021-00859-0},
	journal-iso = {EUR J HUM GENET},
	journal = {EUROPEAN JOURNAL OF HUMAN GENETICS},
	volume = {29},
	unique-id = {32119912},
	issn = {1018-4813},
	abstract = {For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.},
	keywords = {Biochemistry & Molecular Biology},
	year = {2021},
	eissn = {1476-5438},
	pages = {1325-1331},
	orcid-numbers = {Ellwanger, Kornelia/0000-0003-4845-5795; Synofzik, Matthis/0000-0002-2280-7273; Laurie, Steven/0000-0003-3913-5829; Matalonga, Leslie/0000-0003-0807-2570; Gilissen, Christian/0000-0003-1693-9699; Vitobello, Antonio/0000-0003-3717-8374; Balicza, Péter/0000-0001-8555-5467; Molnár, Mária Judit/0000-0001-9350-1864}
}