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首页> 外文期刊>DNA research: an international journal for rapid publication of reports on genes and genomes >Genome-wide Copy Number Profiling on High-density Bacterial Artificial Chromosomes, Single-nucleotide Polymorphisms, and Oligonucleotide Microarrays: A Platform Comparison based on Statistical Power Analysis
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Genome-wide Copy Number Profiling on High-density Bacterial Artificial Chromosomes, Single-nucleotide Polymorphisms, and Oligonucleotide Microarrays: A Platform Comparison based on Statistical Power Analysis

机译:全基因组拷贝数谱分析高密度细菌人工染色体,单核苷酸多态性和寡核苷酸微阵列:基于统计功效分析的平台比较。

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摘要

Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a higher resolution have resulted in the generation of additional microarray platforms encompassing larger numbers of shorter DNA targets (oligonucleotides). Here, we present a novel method to estimate the ability of a microarray to detect genomic copy-number variations of different sizes and types (i.e. deletions or duplications). We applied our method, which is based on statistical power analysis, to four widely used high-density genomic microarray platforms. By doing so, we found that the high-density oligonucleotide platforms are superior to the BAC platform for the genome-wide detection of copy-number variations smaller than 1 Mb. The capacity to reliably detect single copy-number variations below 100 kb, however, appeared to be limited for all platforms tested. In addition, our analysis revealed an unexpected platform-dependent difference in sensitivity to detect a single copy-number loss and a single copy-number gain. These analyses provide a first objective insight into the true capacities and limitations of different genomic microarrays to detect and define DNA copy-number variations.
机译:最近,已证明在细菌人工染色体(BAC)阵列上进行比较基因组杂交(基于阵列的比较基因组杂交)已成功检测出健康和疾病中的亚显微DNA拷贝数变异。为了获得更高的分辨率而进行的技术改进导致产生了包含更多数量的较短DNA靶标(寡核苷酸)的附加微阵列平台。在这里,我们提出了一种新颖的方法来评估微阵列检测不同大小和类型(即缺失或重复)的基因组拷贝数变异的能力。我们将基于统计功效分析的方法应用于四个广泛使用的高密度基因组微阵列平台。通过这样做,我们发现在全基因组范围内检测小于1 Mb的拷贝数变异时,高密度寡核苷酸平台优于BAC平台。但是,对于所有测试的平台,可靠地检测100 kb以下的单个拷贝数变异的能力似乎受到限制。此外,我们的分析显示,在检测单个拷贝数丢失和单个拷贝数增加的灵敏度方面,出乎意料的依赖于平台的差异。这些分析提供了对不同基因组微阵列检测和定义DNA拷贝数变异的真实能力和局限性的初步客观见解。

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