微阵列数据处理平台设计与实现

Design and realization of a microarray data analysis platform

目的研制一个基于高性能计算机和Linux下运行的采用B/S模式的微阵列数据处理平台。方法构建以Apache服务器为平台的WEB服务器,采用Perl语言编程,整合R语言与Bioconductor中的微阵列数据分析软件包,满足寡核苷酸微阵列和双色点样微阵列实验数据的处理和分析,用户可在网页上提交数据和设置参数,结果通过网页以图形化的方式返回。结果该平台可处理寡核苷酸微阵列和双色点样微阵列的数据,实现了数据质量评估、预处理、注释、统计分析等功能,操作简单,分析速度快。运用本平台处理了结核杆菌不同临床分型的人类巨噬细胞寡核苷酸微阵列数据,即潜伏期、结核病、结核性脑膜炎,为识别结核杆菌的敏感基因提供了线索。利用本平台还分析不同条件下用异烟肼处理结核分支杆菌的效果,例如低氧条件和敲除katG基因的条件所获得的相关cDNA微阵列数据,发现用异烟肼处理的对数生长期调节的基因将不会在休眠期模型中被差异调节;并且在休眠期,被差异调节的基因总数将减少。结论该平台功能资源整合较全面,克服了当前微阵列数据分析软件或工具包在操作使用方面的不足,应用界面友好,结果显示直观,为生物学家开展微阵列数据分析提供了方便。针对结核分支杆菌的案例研究验证了平台的有效性。

Objective To design a platform for microarray data analysis and processing in the browser/server mode running in Linux operating system.Methods Based on the Apache HTTP server,the platform,programmed with Perl language,integrated R language and Bioconductor packages for processing and analysis of the input data of oligonucleotide arrays and two-color spotted arrays.Users were allowed to submit data and parameter configurations to the platform via the web page,and the results of analysis were also returned via the web page.Results With an easy operation and high performance,the platform fulfilled the functions of processing,quality assessment,biological annotation and statistical analysis of the data from oligonucleotide arrays and two-color spotted arrays.Using the platform,we analyzed the gene expression profiles in Mtb-stimulated macrophages of three clinical phenotypes,namely latent TB（LTB）,pulmonary（PTB） and meningeal（TBM）,and obtained valuable clues for identifying tuberculosis susceptibility genes.We also analyzed the effect of INH treatment on Mycobacterium tuberculosis gene expression in various dormancy models,such as hypoxia and KatG mutant,and found that a set of genes responded to INH treatment during exponential growth but not in dormancy,and that the overall number of differentially regulated genes was reduced in the cells in low metabolic state.Conclusion The platform we have constructed integrates comprehensive resources,and with a user-friendly interface,allows direct result visualization to facilitate microarray data analysis.