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This resource contains material presented at the ARTNet2023 Annual Meeting, June, 2023 in Buffalo, New York.
This two-hour workshop provides an introduction to using R and Bioconductor to explore single-cell gene expression data. We focus on ‘downstream’ analysis, for example after a bioinformatics core has performed initial cell type classification, differential gene expression, etc. Example tasks we will cover include data input of ‘csv’ and other files, visualization (e.g., UMAPs), and essential statistical analysis (e.g., simple survivorship). Participants with some exposure to R and RStudio will be well-positioned to benefit from this workshop.
The workshop consists of 3 short articles:
- Introduction to R -- R vectors, data.frames, and packages for data management and visualization. Kaplan-Meier curves.
- Exploring Bioinformatic Data -- Summarizing single cell samples, UMAP visualization, differential expression.
- R and Bioconductor for Single-Cell Analysis -- introducing R packages for comprehensive analysis of single-cell data.
In addition to the material for the material in these notes, the workshop includes
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A pre-configured cloud-based instance for 'following along' in your own RStudio session during the workshop.
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A 'docker' image to use locally after the workshop is over. After runnig the following comand, join the RStudio session at
https://localhost:8787.docker run -e PASSWORD=<FIXME> -p 8787:8787 ghcr.io/mtmorgan/ARTNet2023:latest