pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components.

Autor: Marini, Federico, Binder, Harald
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Zdroj: BMC Bioinformatics; 6/13/2019, Vol. 20 Issue 1, p1-8, 8p, 1 Color Photograph, 1 Diagram
Abstrakt: Background: Principal component analysis (PCA) is frequently used in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking. Results: We developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny framework and exploits data structures from the open-source Bioconductor project. Users can easily generate a wide variety of publication-ready graphs, while assessing the expression data in the different modules available, including a general overview, dimension reduction on samples and genes, as well as functional interpretation of the principal components. Conclusion: pcaExplorer is distributed as an R package in the Bioconductor project (http://bioconductor.org/packages/pcaExplorer/), and is designed to assist a broad range of researchers in the critical step of interactive data exploration. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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