Univ Lille Nord de France, F-59000 Lille, France.
Nucleic Acids Res. 2010 Apr;38(7):e94. doi: 10.1093/nar/gkp1215. Epub 2010 Jan 13.
Array-based comparative genomic hybridization (aCGH) is a powerful tool to detect genomic imbalances in the human genome. The analysis of aCGH data sets has revealed the existence of a widespread technical artifact termed as 'waves', characterized by an undulating data profile along the chromosome. Here, we describe the development of a novel noise-reduction algorithm, waves aCGH correction algorithm (WACA), based on GC content and fragment size correction. WACA efficiently removes the wave artifact, thereby greatly improving the accuracy of aCGH data analysis. We describe the application of WACA to both real and simulated aCGH data sets, and demonstrate that our algorithm, by systematically correcting for all known sources of bias, is a significant improvement on existing aCGH noise reduction algorithms. WACA and associated files are freely available as Supplementary Data.
基于阵列的比较基因组杂交（aCGH）是一种强大的工具，可用于检测人类基因组中的基因组失衡。对 aCGH 数据集的分析揭示了一种广泛存在的技术伪影，称为“波浪”，其特征是沿着染色体呈现出波浪状的数据分布。在这里，我们描述了一种基于 GC 含量和片段大小校正的新型降噪算法——波浪 aCGH 校正算法（WACA）的开发。WACA 有效地去除了波浪伪影，从而极大地提高了 aCGH 数据分析的准确性。我们描述了 WACA 在真实和模拟 aCGH 数据集上的应用，并证明我们的算法通过系统地纠正所有已知的偏差源，是对现有 aCGH 降噪算法的重大改进。WACA 及其相关文件可作为补充数据免费获取。
