MagiCMicroRna: a web implementation of AgiMicroRna using shiny.

Q2 Decision Sciences Source Code for Biology and Medicine Pub Date : 2015-03-26 eCollection Date: 2015-01-01 DOI:10.1186/s13029-015-0035-5

Maarten Lj Coonen, Daniel Hj Theunissen, Jos Cs Kleinjans, Danyel Gj Jennen

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引用次数: 9

Abstract

Background: 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.

Results: 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).

Conclusions: 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.

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MagiCMicroRna:一个使用shiny的AgiMicroRna的web实现。

背景:MicroRNA的表达可以通过测序技术或商用MicroRNA表达阵列进行量化。最近，AgiMicroRna r包发布，可以对Agilent microRNA阵列进行系统预处理和统计分析。在这里，我们描述MagiCMicroRna，这是一个用户友好的网络界面，为这个包，以及一个新的过滤方法。结果: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微阵列数据集进行归一化和过滤。使用标准过滤程序，817个microrna中有250个保留下来，而新的组特异性过滤方法在大多数组(>279个microrna)中产生了更广泛的数据集，用于进一步分析。结论:MagiCMicroRna的用户友好的web界面使研究人员能够通过点击一键对安捷伦微阵列进行规范化和筛选。此外，MagiCMicroRna提供了选择过滤方法的灵活性。与标准程序相比，新的组特异性过滤方法导致增加数量和额外的组织特异性microrna用于后续分析。MagiCMicroRna的web界面和源代码可以从https://bitbucket.org/mutgx/magicmicrorna.git下载。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Source Code for Biology and Medicine Decision Sciences-Information Systems and Management

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期刊介绍： Source Code for Biology and Medicine is a peer-reviewed open access, online journal that publishes articles on source code employed over a wide range of applications in biology and medicine. The journal"s aim is to publish source code for distribution and use in the public domain in order to advance biological and medical research. Through this dissemination, it may be possible to shorten the time required for solving certain computational problems for which there is limited source code availability or resources.

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