Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.
Bioinformatics
; 40(2)2024 02 01.
Article
en En
| MEDLINE
| ID: mdl-38244574
ABSTRACT
MOTIVATION 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. RESULTS:
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% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts. AVAILABILITY AND IMPLEMENTATION Conumee 2.0 is available under open-source license at https//github.com/hovestadtlab/conumee2.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Metilación de ADN
/
Neoplasias
Tipo de estudio:
Prognostic_studies
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos