Related Experiment Video
Updated: Jun 4, 2026
A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
Published on: October 28, 2025
aCGH.Spline--an R package for aCGH dye bias normalization
Tomas W Fitzgerald1, Lee D Larcombe, Solena Le Scouarnec
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk
Motivation:
The careful normalization of array-based comparative genomic hybridization (aCGH) data is of critical importance for the accurate detection of copy number changes. The difference in labelling affinity between the two fluorophores used in aCGH-usually Cy5 and Cy3-can be observed as a bias within the intensity distributions. If left unchecked, this bias is likely to skew data interpretation during downstream analysis and lead to an increased number of false discoveries.
Results:
In this study, we have developed aCGH.Spline, a natural cubic spline interpolation method followed by linear interpolation of outlier values, which is able to remove a large portion of the dye bias from large aCGH datasets in a quick and efficient manner.
Conclusions:
We have shown that removing this bias and reducing the experimental noise has a strong positive impact on the ability to detect accurately both copy number variation (CNV) and copy number alterations (CNA).
