首页> 外文期刊>Physiological genomics >The intraclass correlation coefficient applied for evaluation of data correction, labeling methods, and rectal biopsy sampling in DNA microarray experiments
【24h】

The intraclass correlation coefficient applied for evaluation of data correction, labeling methods, and rectal biopsy sampling in DNA microarray experiments

机译:类内相关系数用于评估DNA芯片实验中的数据校正,标记方法和直肠活检样本

获取原文
获取原文并翻译 | 示例
       

摘要

We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from an ANOVA table. It is based on the assessment of both systematic deviation and random variation, and it facilitates comparison of multiple samples at once. We used the ICC first to optimize our microarray data normalization method and found that the use of median values instead of mean values improves data correction. Then the reproducibility of different labeling methods was evaluated, and labeling by indirect fluorescent dye incorporation appeared to be more reproducible than direct labeling. Finally, we determined optimal biopsy sampling by analyzing overall variation in gene expression. The variation in gene expression of rectal biopsies within persons decreased when two biopsies were taken instead of one, but it did not considerably improve when more than two biopsies were taken from one person, indicating that it is sufficient to use two biopsies per person for DNA microarray analysis under our experimental conditions. To optimize the accuracy of the microarray data, biopsies from at least six different persons should be used per group.
机译:我们表明类内相关系数(ICC)可以用作相对简单的统计方法,以评估DNA芯片分析中的方法和生物学差异。 ICC是一种确定变量可重复性的度量,可以很容易地从ANOVA表计算得出。它基于对系统偏差和随机变化的评估,并且有助于一次比较多个样本。我们首先使用ICC优化了我们的微阵列数据标准化方法,发现使用中值代替平均值可以改善数据校正。然后评估了不同标记方法的可重复性,并且间接荧光染料掺入的标记似乎比直接标记具有更高的可复制性。最后,我们通过分析基因表达的总体变异来确定最佳的活检样本。当进行两次活检而不是一次活检时,人的直肠活检基因表达的变化减少了,但是当从一个人进行了两次以上活检时,并没有显着改善,表明每人使用两次活检足以用于DNA检测实验条件下的微阵列分析。为了优化微阵列数据的准确性,每组至少应使用六个不同的人进行活检。

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