2026-04-14T06:25:44Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1742792025-12-04T22:42:51Zcom_2072_1057col_2072_478825col_2072_478917

00925njm 22002777a 4500 dc Martínez Otzeta, José María author Irigoien, Itziar author Sierra, Basilio author Arenas Solà, Concepción author 2021-02-24T17:47:55Z 2021-02-24T17:47:55Z 2020-04-07 2021-02-24T17:47:55Z 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. Expressió gènica Biotecnologia ADN Biosensors Gene expression Biotechnology DNA Biosensors ORdensity: user-friendly R package to identify differentially expressed genes