首页> 外文期刊>Bioinformatics >A rapid method for computationally inferring transcriptome coverage and microarray sensitivity
【24h】

A rapid method for computationally inferring transcriptome coverage and microarray sensitivity

机译:一种计算推断转录组覆盖率和微阵列敏感性的快速方法

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译: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。对于每种感兴趣的生物,转录组和基因组的覆盖范围将有所不同。我们解决了以下问题:利用不同技术的敏感性需要多少水平的覆盖率?在实验研究中不同方法的敏感性是什么?结果:我们通过从预先定义的样本中随机抽取转录本来估算转录组的覆盖率标签到基因的映射功能。对于给定的微阵列实验,我们以定义转录本丰度分布的强度定位阈值。将这些值与通过对差异表达基因的强度施加相同阈值而获得的分布进行比较。这两个分布的比率满足定义灵敏度的平衡。我们得出的结论是,对于微阵列而言,足够收集约34万个序列,但不足以最大程度地利用基于标签的技术。在没有大规模测序的情况下,后一种方法检测到的大多数标签在基因组序列可用之前将一直不确定。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号