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ORdensity: user-friendly R package to identify differentially expressed genes.
BMC Bioinformatics ( IF 3 ) Pub Date : 2020-04-07 , DOI: 10.1186/s12859-020-3463-4
José María Martínez-Otzeta 1 , Itziar Irigoien 1 , Basilio Sierra 1 , Concepción Arenas 2
Affiliation  

BACKGROUND Microarray technology provides the expression level of many genes. Nowadays, an important issue is to select a small number of informative differentially expressed genes that provide biological knowledge and may be key elements for a disease. With the increasing volume of data generated by modern biomedical studies, software is required for effective identification of differentially expressed genes. Here, we describe an R package, called ORdensity, that implements a recent methodology (Irigoien and Arenas, 2018) developed in order to identify differentially expressed genes. The benefits of parallel implementation are discussed. RESULTS ORdensity gives the user the list of genes identified as differentially expressed genes in an easy and comprehensible way. The experimentation carried out in an off-the-self computer with the parallel execution enabled shows an improvement in run-time. This implementation may also lead to an important use of memory load. Results previously obtained with simulated and real data indicated that the procedure implemented in the package is robust and suitable for differentially expressed genes identification. CONCLUSIONS The new package, ORdensity, offers a friendly and easy way to identify differentially expressed genes, which is very useful for users not familiar with programming. AVAILABILITY https://github.com/rsait/ORdensity.

中文翻译:

ORdensity:用户友好的R包,用于识别差异表达的基因。

背景技术微阵列技术提供了许多基因的表达水平。如今,一个重要的问题是选择少量信息性差异表达基因,这些基因可提供生物学知识,并且可能是疾病的关键要素。随着现代生物医学研究产生的数据量的增加,需要有效识别差异表达基因的软件。在这里,我们描述了一个名为ORdensity的R包,该R包实现了一种新方法(Irigoien and Arenas,2018),该方法用于鉴定差异表达的基因。讨论了并行实现的好处。结果ORdensity以简单易懂的方式向用户提供了鉴定为差异表达基因的基因列表。在启用了并行执行的自带计算机上进行的实验表明运行时有所改善。此实现还可能导致内存负载的重要使用。先前使用模拟和真实数据获得的结果表明,该程序包中执行的过程稳定可靠,适用于差异表达基因的鉴定。结论新的程序包ORdensity提供了一种友好而简便的方法来鉴定差异表达的基因,这对不熟悉编程的用户非常有用。可用性https://github.com/rsait/ORdensity。先前使用模拟和真实数据获得的结果表明,该程序包中执行的过程稳定可靠,适用于差异表达基因的鉴定。结论新的程序包ORdensity提供了一种友好而简便的方法来鉴定差异表达的基因,这对不熟悉编程的用户非常有用。可用性https://github.com/rsait/ORdensity。先前使用模拟和真实数据获得的结果表明,该程序包中执行的过程稳定可靠,适用于差异表达基因的鉴定。结论新的程序包ORdensity提供了一种友好而简便的方法来鉴定差异表达的基因,这对不熟悉编程的用户非常有用。可用性https://github.com/rsait/ORdensity。
更新日期:2020-04-22
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