A rapid method for computationally inferring transcriptome coverage and microarray sensitivity
A rapid method for computationally inferring transcriptome coverage and microarray sensitivity
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DOI：
10.1093/bioinformatics/bth472
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发表时间：
2005-01-01
期刊：
影响因子：
5.8
通讯作者：
Dalrymple, BP
中科院分区：
文献类型：
--
作者：
Reverter, A;McWilliam, SM;Dalrymple, BP
动机：有许多不同的基因表达技术，包括cDNA和基于寡核苷酸的微阵列，SAGE和MPSS。对于每个感兴趣的生物体，转录组和基因组的覆盖范围将是不同的。我们解决的问题是什么水平的覆盖率需要利用不同的技术的灵敏度，什么是不同的方法在实验study.Results的灵敏度：我们估计的转录组覆盖率从一个预先定义的标签基因映射函数随机抽样成绩单。对于一个给定的微阵列实验，我们将阈值定位在定义转录本丰度分布的强度中。将这些值与通过将相同阈值应用于来自差异表达基因的强度而获得的分布进行比较。这两个分布的比率满足平衡定义灵敏度。我们的结论是，收集类似的340 000序列是足够的微阵列，但不够大，最大限度地利用标签为基础的技术。在没有大规模测序的情况下，通过后一种方法检测到的大多数标签将保持未被识别，直到基因组序列可用。
Motivation: There are many different gene expression technologies, including cDNA and oligo-based microarrays, SAGE and MPSS. For each organism of interest, coverage of the transcriptome and the genome will be different. We address the question of what level of coverage is required to exploit the sensitivity of the different technologies, and what is the sensitivity of the different approaches in the experimental study.Results: We estimate the transcriptome coverage by randomly sampling transcripts from a pre-defined tag-to-gene mapping function. For a given microarray experiment, we locate the thresholds in intensities that define the distribution of transcript abundance. These values are compared against the distribution obtained by applying the same thresholds to the intensities from differentially expressed genes. The ratio of these two distributions meets at the equilibrium defining sensitivity. We conclude that a collection of similar to340 000 sequences is adequate for microarrays, but not large enough for maximum utilization of tag-based technologies. In the absence of large-scale sequencing, the majority of the tags detected by the latter approaches will remain unidentified until the genome sequence is available.