Bilke Sven, Chen Qing-Rong, Whiteford Craig C, Khan Javed
Oncogenomics Section, Pediatric Oncology Branch, Advanced Technology Center, National Cancer Institute 8717 Grovemont Circle, Gaithersburg, MD 20877, USA.
Bioinformatics. 2005 Apr 1;21(7):1138-45. doi: 10.1093/bioinformatics/bti133. Epub 2004 Nov 11.
The accumulation of genomic alterations is an important process in tumor formation and progression. Comparative genomic hybridization performed on cDNA arrays (cDNA aCGH) is a common method to investigate the genomic alterations on a genome-wide scale. However, when detecting low-level DNA copy number changes this technology requires the use of noise reduction strategies due to a low signal to noise ratio.
Currently a running average smoothing filter is the most frequently used noise reduction strategy. We analyzed this strategy theoretically and experimentally and found that it is not sensitive to very low level genomic alterations. The presence of systematic errors in the data is one of the main reasons for this failure. We developed a novel algorithm which efficiently reduces systematic noise and allows for the detection of low-level genomic alterations. The algorithm is based on comparison of the biological relevant data to data from so-called self-self hybridizations, additional experiments which contain no biological information but contain systematic errors. We find that with our algorithm the effective resolution for +/-1 DNA copy number changes is about 2 Mb. For copy number changes larger than three the effective resolution is on the level of single genes.
基因组改变的积累是肿瘤形成和进展中的一个重要过程。在cDNA阵列上进行的比较基因组杂交（cDNA aCGH）是在全基因组范围内研究基因组改变的常用方法。然而，在检测低水平DNA拷贝数变化时，由于信噪比低，该技术需要使用降噪策略。
目前，移动平均平滑滤波器是最常用的降噪策略。我们对该策略进行了理论和实验分析，发现它对极低水平的基因组改变不敏感。数据中存在系统误差是导致这种失败的主要原因之一。我们开发了一种新算法，该算法能有效降低系统噪声，并允许检测低水平的基因组改变。该算法基于将生物学相关数据与来自所谓的自我自我杂交的数据进行比较，自我自我杂交是额外的实验，不包含生物学信息，但包含系统误差。我们发现，使用我们的算法，对于+/-1 DNA拷贝数变化的有效分辨率约为2 Mb。对于大于三个的拷贝数变化，有效分辨率处于单个基因水平。
