Skip to contents

exploreDE

exploreDE is a Shiny app for exploring differential expression results from RNA-seq, proteomics and CRISPR screens, and for making publication-quality figures from them.

Documentation website: https://fgcz.github.io/exploreDE/ (help pages, the bring-your-own-data vignette, changelog).

Install and run 

install.packages("BiocManager")
BiocManager::install("fgcz/exploreDE") # pulls in the Bioconductor dependencies (anndataR >= 1.2.3: Bioconductor >= 3.23)
# optional: KEGG views, GLM-PCA, formatted level labels (hidden or plain without them)
BiocManager::install(c("pathview", "glmpca", "ggtext", "gridtext"))

library(exploreDE)
exploreDE()                   # landing page: upload a file or load the demo
exploreDE("my_data.h5ad")     # or open straight into your own file

With no file, the app opens on its landing page, where you can upload an exploreDE .h5ad (see below) or load the demo dataset that ships with the package. On a server, ?data= opens a dataset from the link:

  • ?data=<result directory>: A SUSHI result on FGCZ’s gStore (LDAP-checked).
  • ?data=<percent-encoded https link to an .h5ad>: A file from an allowed source (by default APB Export jobs and public pStore; set EXPLOREDE_URL_SOURCES to change the list). Plain https:// only, no redirects, up to 1 GB.

The LDAP check takes the user from the SHINYPROXY_USERNAME environment variable, read once per R process, so run the app behind ShinyProxy with one container per user. Without that variable (plain Shiny Server, for example) every gStore link is refused; the demo, uploads and https:// links still work.

Bring your own data

exploreDE reads one file format: an .h5ad (AnnData) file in the exploreDE/1.0 layout, for "rnaseq", "proteomics", or "crispr" data from any pipeline. In R, build_explore_h5ad() writes it. Only counts, sample metadata, and the omics type are required; a DE table and pathway results are optional, and the app shows the tabs your data supports.

build_explore_h5ad(
  counts,                        # features x samples matrix
  out     = "my_data.h5ad",
  omics   = "rnaseq",
  coldata = coldata,             # one row per sample, rownames = colnames(counts)
  rowdata = annotation,          # optional: gene IDs, symbols, GO terms, ...
  de      = list(Treat_vs_Ctrl = de_table)   # optional: one table per contrast
)

You don’t need to rename columns: A built-in dictionary recognises the usual DESeq2, edgeR, limma, prolfqua, and SAINTexpress column names, and warns when it can’t place one.

  • Full guide: vignette("bring-your-own-data", package = "exploreDE") covers counts-only, proteomics, and RNA-seq + pathway examples (all runnable on the data shipped with the package), checking a file, and what to do when a column isn’t recognised.
  • Using an AI assistant: give it system.file("skills/exploreDE-byod/SKILL.md", package = "exploreDE"). It’s written so an assistant can write the import script for your data.
  • Argument reference: ?build_explore_h5ad.
  • Writing files from another tool (Python, an exporter app): system.file("spec/exploreDE-h5ad-1.0.md", package = "exploreDE") is the written .h5ad format spec, including the proteomics profile and a minimal Python writer. APB Export’s exploreDE output follows it.
  • Also opens as it is: The prolfquapp DEA’s AnnData.h5ad (prolfquapp 2.10.x; spec §10).

Saving your settings

The Save / Load Session tab downloads your settings across every tab (widgets, the feature bucket, pathway selections, and Multi DE datasets) as one .json file, and restores them on the same dataset later. It never holds data. The format is exploreDE-session/2: system.file("spec/exploreDE-session-2.md", package = "exploreDE"). The earlier .rds session files were retired in 3.9.0.

Citing exploreDE

See CITATION.cff.