Coonen Maarten Lj, Theunissen Daniel Hj, Kleinjans Jos Cs, Jennen Danyel Gj
Department of Toxicogenomics, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Source Code Biol Med. 2015 Mar 26;10:4. doi: 10.1186/s13029-015-0035-5. eCollection 2015.
MicroRNA expression can be quantified using sequencing techniques or commercial microRNA-expression arrays. Recently, the AgiMicroRna R-package was published that enabled systematic preprocessing and statistical analysis for Agilent microRNA arrays. Here we describe MagiCMicroRna, which is a user-friendly web interface for this package, together with a new filtering approach.
We used MagiCMicroRna to normalize and filter an Agilent miRNA microarray dataset of cancerous and normal tissues from 14 different patients. With the standard filtering procedure, 250 out of 817 microRNAs remained, whereas the new group-specific filtering approach resulted in broader datasets for further analysis in most groups (>279 microRNAs remaining).
The user-friendly web interface of MagiCMicroRna enables researchers to normalize and filter Agilent microarrays by the click of one button. Furthermore, MagiCMicroRna provides flexibility in choosing the filtering method. The new group-specific filtering approach lead to an increased number and additional tissue-specific microRNAs remaining for subsequent analysis compared to the standard procedure. The MagiCMicroRna web interface and source code can be downloaded from https://bitbucket.org/mutgx/magicmicrorna.git.
可使用测序技术或商业微RNA表达芯片对微RNA表达进行定量分析。最近，发布了AgiMicroRna R包，可对安捷伦微RNA芯片进行系统预处理和统计分析。在此，我们介绍MagiCMicroRna，它是该包的一个用户友好型网络界面，同时还介绍了一种新的过滤方法。
我们使用MagiCMicroRna对来自14名不同患者的癌组织和正常组织的安捷伦miRNA微阵列数据集进行标准化和过滤。采用标准过滤程序时，817个微RNA中剩下250个，而新的组特异性过滤方法在大多数组中产生了更广泛的数据集以供进一步分析（剩下超过279个微RNA）。
MagiCMicroRna的用户友好型网络界面使研究人员能够通过点击一个按钮对安捷伦微阵列进行标准化和过滤。此外，MagiCMicroRna在选择过滤方法方面提供了灵活性。与标准程序相比，新的组特异性过滤方法使得后续分析中剩余的微RNA数量增加，并且有额外的组织特异性微RNA。MagiCMicroRna网络界面和源代码可从https://bitbucket.org/mutgx/magicmicrorna.git下载。
