TY  - JOUR
AU  - Daenekas, Bjarne
AU  - Pérez, Eilís
AU  - Boniolo, Fabio
AU  - Stefan, Sabina
AU  - Benfatto, Salvatore
AU  - Sill, Martin
AU  - Sturm, Dominik
AU  - Jones, David T W
AU  - Capper, David
AU  - Zapatka, Marc
AU  - Hovestadt, Volker
TI  - Conumee 2.0: Enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.
JO  - Bioinformatics
VL  - 40
IS  - 2
SN  - 0266-7061
CY  - Oxford
PB  - Oxford Univ. Press
M1  - DKFZ-2024-00176
SP  - btae029
PY  - 2024
N1  - 2024 Feb 1;40(2):btae029
AB  - Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings.We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9
LB  - PUB:(DE-HGF)16
C6  - pmid:38244574
DO  - DOI:10.1093/bioinformatics/btae029
UR  - https://inrepo02.dkfz.de/record/287227
ER  -