Shamir Ron, Maron-Katz Adi, Tanay Amos, Linhart Chaim, Steinfeld Israel, Sharan Roded, Shiloh Yosef, Elkon Ran
School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel.
BMC Bioinformatics. 2005 Sep 21;6:232. doi: 10.1186/1471-2105-6-232.
Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis.
Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER) software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO) and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms.
EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander.
基因表达微阵列是功能基因组学中一种重要的实验工具,为全面、系统地理解转录网络提供了契机。应用该技术的实验通常会产生海量数据,这在生物学研究中是前所未有的。因此,从原始数据中挖掘有意义的生物学知识是生物信息学面临的一项重大挑战。特别需要的是集成软件包,它能为生物学家用户提供先进且易于使用的算法集,涵盖微阵列数据分析的所有步骤。
我们在此展示EXPANDER 2.0(表达分析与展示器)软件包。EXPANDER 2.0是一个用于分析基因表达数据的集成软件包,设计为一个“一站式”工具,实现了从归一化和过滤的初始步骤,到聚类和双聚类,再到高级功能富集分析(指出在所研究条件下活跃的生物学过程)以及启动子顺式调控元件分析(阐明控制观察到的转录反应的转录因子)等各种数据分析算法。EXPANDER附带了针对酵母、线虫、果蝇、大鼠、小鼠和人类预先编译的功能基因本体(GO)和启动子序列衍生数据文件,支持对从这六种生物获得的数据进行高级分析。
EXPANDER的集成功能及其对多种生物的内置支持使其成为分析微阵列数据的强大工具。该软件包可供学术用户从http://www.cs.tau.ac.il/~rshamir/expander免费获取。