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首页> 外文期刊>Genome research >Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome.
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Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome.

机译:评估用于绘制人类基因组转录区的不同高密度平铺微阵列策略的性能。

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摘要

Genomic tiling microarrays have become a popular tool for interrogating the transcriptional activity of large regions of the genome in an unbiased fashion. There are several key parameters associated with each tiling experiment (e.g., experimental protocols and genomic tiling density). Here, we assess the role of these parameters as they are manifest in different tiling-array platforms used for transcription mapping. First, we analyze how a number of published tiling-array experiments agree with established gene annotation on human chromosome 22. We observe that the transcription detected from high-density arrays correlates substantially better with annotation than that from other array types. Next, we analyze the transcription-mapping performance of the two main high-density oligonucleotide array platforms in the ENCODE regions of the human genome. We hybridize identical biological samples and develop several ways of scoring the arrays and segmenting the genome into transcribed and nontranscribed regions, with the aim of making the platforms most comparable to each other. Finally, we develop a platform comparison approach based on agreement with known annotation. Overall, we find that the performance improves with more data points per locus, coupled with statistical scoring approaches that properly take advantage of this, where this larger number of data points arises from higher genomic tiling density and the use of replicate arrays and mismatches. While we do find significant differences in the performance of the two high-density platforms, we also find that they complement each other to some extent. Finally, our experiments reveal a significant amount of novel transcription outside of known genes, and an appreciable sample of this was validated by independent experiments.
机译:基因组切片微阵列已成为一种以无偏见方式询问基因组大区域转录活性的流行工具。每个切片实验都有几个关键参数(例如,实验方案和基因组切片密度)。在这里,我们评估这些参数的作用,因为它们在用于转录映射的不同平铺阵列平台中表现出来。首先,我们分析了许多已公开的平铺阵列实验如何与人类22号染色体上已建立的基因注释相符。我们观察到,从高密度阵列中检测到的转录与注释的相关性要比其他阵列类型中的显着更好。接下来,我们分析了人类基因组ENCODE区域中两个主要的高密度寡核苷酸阵列平台的转录映射性能。我们杂交相同的生物样品,并开发了几种对阵列进行评分和将基因组划分为转录和非转录区域的方法,目的是使平台之间的可比性最高。最后,我们开发了一种基于与已知注释一致的平台比较方法。总的来说,我们发现,通过每个基因座上更多的数据点以及结合适当地利用这一点的统计评分方法,性能会提高,其中大量的数据点来自更高的基因组平铺密度以及使用重复阵列和错配。尽管我们确实发现两个高密度平台的性能存在显着差异,但我们也发现它们在某种程度上可以互补。最后,我们的实验揭示了在已知基因之外的大量新转录,并且相当数量的样本已通过独立实验验证。

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