摘要
目的以具体实验数据为例探讨在使用RNA测序技术时如何选择恰当的数据处理方法。方法以左归丸作用于高糖负荷的小鼠胚胎的转录组数据为例,分别运用目前通过转录组数据进行差异表达基因分析常用的cuffdiff、DESeq-2、edgeR 3种数据处理方法对数据进行了处理。结果不同的数据处理方法得到的差异基因数及后续的分析结果均出现了明显的不同。纵使基于共同的计算理念,参数选择的不同除了导致差异基因数的不同之外,差异基因在组间的差异程度上也会受到很大影响。这种差异会导致对相应研究目的的阐释出现偏差。结论在运用生物信息学恰当地处理和分析RNA测序技术带来的海量数据时,根据研究内容选择恰当的基因表达差异分析方法至关重要。
Objective Provides a reference to researchers that how to use bioinformatics appropriately to process and analyze the huge amounts of data from RNA sequencing technology then better serve further research of Traditional Chinese Medicine. Methods Using the transcriptome data of Zuo - Gui - Wan on high glucose loaded mouse embryo as an example, three differential expression analysis methods, cuffdiff, DESeq2, edgeR,were used separately to analyze the sequencing data. Results Different gene numbers and the subsequent analysis results are got and accompanied by the different research aim illustration from different expression analysis methods base on same samples. Conclusion Expression analysis method play important role in the illustration of research.
出处
《世界中西医结合杂志》
2017年第5期650-657,672,共9页
World Journal of Integrated Traditional and Western Medicine
基金
国家国际科技合作专项项目基金资助(2012DFA31330)
