inst/extdata/help_eda.md

In ideal: Interactive Differential Expression AnaLysis

Performing EDA before DE

For the purpose of Exploratory Data Analysis, fundamental in -omics data like in many low-throughput experimental datasets, we can recommend another package we developed, pcaExplorer (https://bioconductor.org/packages/pcaExplorer/, published at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2879-1). There you can have PCA plots, heatmaps of distances across samples, and much more (e.g. hints towards a functional interpretation of principal components).

By splitting the steps of Exploratory Data Analysis and Differential Expression analysis, while still keeping a common framework (with similar input objects and formats), we hope to raise the awareness of the importance of proper exploratory steps, before testing for differential expression - and at the same time, not increase the burden for users by having to learn yet another software interface and its requirements.

You can use pcaExplorer both as an interactive Shiny app, as well as with its functionality from the exported functions, inserted e.g. in fully fledged analysis reports.

If you want to try out pcaExplorer, you can do so by checking out http://shiny.imbei.uni-mainz.de:3838/pcaExplorer/ - or using it on your local machine (it is imported directed by ideal).

ideal documentation built on Nov. 8, 2020, 5:02 p.m.