Laframboise Thomas, Harrington David, Weir Barbara A
Department of Medical Oncology, Dana-Farber Cancer Institute, MA 02115, USA.
Biostatistics. 2007 Apr;8(2):323-36. doi: 10.1093/biostatistics/kxl012. Epub 2006 Jun 20.
Human cancer is largely driven by the acquisition of mutations. One class of such mutations is copy number polymorphisms, comprised of deviations from the normal diploid two copies of each autosomal chromosome per cell. We describe a probe-level allele-specific quantitation (PLASQ) procedure to determine copy number contributions from each of the parental chromosomes in cancer cells from single-nucleotide polymorphism (SNP) microarray data. Our approach is based upon a generalized linear model that takes advantage of a novel classification of probes on the array. As a result of this classification, we are able to fit the model to the data using an expectation-maximization algorithm designed for the purpose. We demonstrate a strong model fit to data from a variety of cell types. In normal diploid samples, PLASQ is able to genotype with very high accuracy. Moreover, we are able to provide a generalized genotype in cancer samples (e.g. CCCCT at an amplified SNP). Our approach is illustrated on a variety of lung cancer cell lines and tumors, and a number of events are validated by independent computational and experimental means. An R software package containing the methods is freely available.
人类癌症很大程度上是由突变的获得所驱动的。这类突变中的一类是拷贝数多态性，它由每个细胞中常染色体正常二倍体的两份拷贝发生偏差所组成。我们描述了一种探针水平等位基因特异性定量（PLASQ）程序，用于从单核苷酸多态性（SNP）微阵列数据确定癌细胞中每个亲本染色体的拷贝数贡献。我们的方法基于一个广义线性模型，该模型利用了阵列上探针的一种新分类。由于这种分类，我们能够使用为此目的设计的期望最大化算法将模型拟合到数据。我们证明该模型能很好地拟合来自多种细胞类型的数据。在正常二倍体样本中，PLASQ能够以非常高的准确性进行基因分型。此外，我们能够在癌症样本中提供广义基因型（例如在一个扩增的SNP处为CCCC T）。我们的方法在多种肺癌细胞系和肿瘤上进行了说明，并且一些结果通过独立的计算和实验方法得到了验证。包含这些方法的R软件包可免费获取。
