NB_Ranking
Description
The Neuroblastoma Research Consortium dataset was analyzed to explore the relationship between copy number variations, gene expression, and clinical risk classification. CNV data, originally mapped to hg18, was lifted to hg38 using the UCSC Genome Browser liftOver tool, with gene annotations retrieved from Ensembl. CNVs were classified as gain, loss, or normal based on established thresholds. Expression and metadata were integrated, standardizing sample identifiers and normalizing expression values. A linear model assessed the impact of CNVs on gene expression while accounting for clinical classification. To identify significant chromosomal alterations, CNV frequencies were analyzed in a high-risk neuroblastoma cohort. A ranking system prioritized genes based on CNV frequency, dosage sensitivity, and risk association, identifying key candidates in neuroblastoma. This framework integrates genomic data and statistical modeling to highlight chromosomal alterations relevant to disease progression, offering insights into potential biomarkers and therapeutic targets. All code can be found on GitHub: https://github.com/PPOLLabGhent/NB_Ranking