A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001003335	A resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect.	Illumina HiSeq 2500	96

Publications	Citations
The ICR96 exon CNV validation series: a resource for orthogonal assessment of exon CNV calling in NGS data. Mahamdallie S, Ruark E, Yost S, Ramsay E, Uddin I, Wylie H, Elliott A, Strydom A, Renwick A, Seal S, Rahman N. Wellcome Open Res 2: 2017 35	9
Evaluation of CNV detection tools for NGS panel data in genetic diagnostics. Moreno-Cabrera JM, Del Valle J, Castellanos E, Feliubadaló L, Pineda M, Brunet J, Serra E, Capellà G, Lázaro C, Gel B. Eur J Hum Genet 28: 2020 1645-1655	63
isoCNV: in silico optimization of copy number variant detection from targeted or exome sequencing data. Barcelona-Cabeza R, Sanseverino W, Aiese Cigliano R. BMC Bioinformatics 22: 2021 530	3
SavvyCNV: Genome-wide CNV calling from off-target reads. Laver TW, De Franco E, Johnson MB, Patel KA, Ellard S, Weedon MN, Flanagan SE, Wakeling MN. PLoS Comput Biol 18: 2022 e1009940	22
ifCNV: A novel isolation-forest-based package to detect copy-number variations from various targeted NGS datasets. Cabello-Aguilar S, Vendrell JA, Van Goethem C, Brousse M, Gozé C, Frantz L, Solassol J. Mol Ther Nucleic Acids 30: 2022 174-183	8
Detection of germline CNVs from gene panel data: benchmarking the state of the art. Munté E, Roca C, Del Valle J, Feliubadaló L, Pineda M, Gel B, Castellanos E, Rivera B, Cordero D, Moreno V, Lázaro C, Moreno-Cabrera JM. Brief Bioinform 26: 2024 bbae645	0