MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data.

MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data.
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DOI:
10.1186/1471-2105-15-69
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发表时间:
2014-03-12
期刊:
影响因子:
3
通讯作者:
Zambon AC
Zambon AC
中科院分区:
生物学4区
文献类型:
--
作者:
Gan Z;Wang J;Salomonis N;Stowe JC;Haddad GG;McCulloch AD;Altintas I;Zambon AC

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在研究出版之前,强制性存款原始微阵列数据文件供公众访问,这为在多个数据集内和跨多个数据集进行新的生物信息学分析提供了重要机会。原始微阵列数据文件(例如Affymbox CEL文件)的分析可能是耗时的、复杂的,并且需要基本的计算和生物信息学技能。开发分析工作流程以自动化这些任务,简化了处理,提高了效率,并用于标准化多个和连续的分析。安装后,工作流简化了运行快速数据集内和数据集间比较所需的繁琐步骤。我们开发了一个工作流程,以促进和标准化开普勒中的Affyssin微阵列数据分析(MAAMD)的荟萃分析。两个免费提供的独立软件工具,R和AltAnalyze嵌入在MAAMD中。MAAMD的输入是用户可编辑的csv文件,其中包含样本信息和描述输入文件和所需工具位置的参数。通过分析来自小鼠和果蝇的4个不同GEO数据集来测试MAAMD。MAAMD自动化数据下载,数据组织,数据质量控制评估,差异基因表达分析,聚类分析,途径可视化,基因集富集分析和跨物种直系同源基因比较。利用MAAMD在小鼠和果蝇中鉴定对缺氧或高氧反应的基因直向同源物。4个数据集(总共34个微阵列)的整套分析在约1小时内完成。MAAMD节省了时间,最大限度地减少了所需的计算机技能,并为用户提供了一个标准化的程序来分析微阵列数据集,并进行新的数据集内和数据集间的比较。
Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons.
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