inst/extdata/about.md

About pcaExplorer

pcaExplorer is a Bioconductor package containing a Shiny application for analyzing expression data in different conditions and experimental factors.

pcaExplorer guides the user in exploring the Principal Components of the data, providing tools and functionality to detect outlier samples, genes that show particular patterns, and additionally provides a functional interpretation of the principal components for further quality assessment and hypothesis generation on the input data.

Thanks to its interactive/reactive design, it is designed to become a practical companion to any RNA-seq dataset analysis, making exploratory data analysis accessible also to the bench biologist, while providing additional insight also for the experienced data analyst.

Moreover, pcaExplorer supports reproducible research with state saving and automated report generation.

pcaExplorer was developed in the Bioinformatics Division led by Harald Binder at the IMBEI (Institut für Medizinische Biometrie, Epidemiologie und Informatik) in the University Medical Center of the Johannes Gutenberg University Mainz.

Developers

Federico Marini

Code

All code for pcaExplorer is available on GitHub.

Citation info

If you use pcaExplorer for your analysis, please cite it as here below:

citation("pcaExplorer")
To cite package ‘pcaExplorer’ in publications use:

  Federico Marini (2018). pcaExplorer: Interactive Visualization of RNA-seq Data Using
  a Principal Components Approach. R package version 2.6.0.
  https://github.com/federicomarini/pcaExplorer

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {pcaExplorer: Interactive Visualization of RNA-seq Data Using a Principal Components Approach},
    author = {Federico Marini},
    year = {2018},
    note = {R package version 2.6.0},
    url = {https://github.com/federicomarini/pcaExplorer},
  }


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pcaExplorer documentation built on Nov. 8, 2020, 5:29 p.m.