Group of Bioinformatics, CEIT and TECNUN, University of Navarra, San Sebastian, Spain.
Bioinformatics. 2010 Aug 1;26(15):1827-33. doi: 10.1093/bioinformatics/btq300. Epub 2010 Jun 6.
Current algorithms for estimating DNA copy numbers (CNs) borrow concepts from gene expression analysis methods. However, single nucleotide polymorphism (SNP) arrays have special characteristics that, if taken into account, can improve the overall performance. For example, cross hybridization between alleles occurs in SNP probe pairs. In addition, most of the current CN methods are focused on total CNs, while it has been shown that allele-specific CNs are of paramount importance for some studies. Therefore, we have developed a summarization method that estimates high-quality allele-specific CNs.
The proposed method estimates the allele-specific DNA CNs for all Affymetrix SNP arrays dealing directly with the cross hybridization between probes within SNP probesets. This algorithm outperforms (or at least it performs as well as) other state-of-the-art algorithms for computing DNA CNs. It better discerns an aberration from a normal state and it also gives more precise allele-specific CNs.
The method is available in the open-source R package ACNE, which also includes an add on to the aroma.affymetrix framework (http://www.aroma-project.org/).
当前用于估计 DNA 拷贝数 (CN) 的算法借鉴了基因表达分析方法的概念。然而，单核苷酸多态性 (SNP) 阵列具有特殊的特征，如果考虑到这些特征，可以提高整体性能。例如，在 SNP 探针对之间会发生等位基因间的交叉杂交。此外，大多数当前的 CN 方法都集中在总 CN 上，而已经表明，对于某些研究，等位基因特异性 CN 至关重要。因此，我们开发了一种估计高质量等位基因特异性 CN 的汇总方法。
所提出的方法直接处理 SNP 探针集中探针之间的交叉杂交，估计所有 Affymetrix SNP 阵列的等位基因特异性 DNA CN。该算法在计算 DNA CN 方面优于（或至少与）其他最先进的算法。它更好地区分了异常和正常状态，并且还提供了更精确的等位基因特异性 CN。
该方法可在开源 R 包 ACNE 中使用，该包还包括对 aroma.affymetrix 框架（http://www.aroma-project.org/）的附加功能。
