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1. MasteringShiny_work MasteringShiny_work Public

   R

2. sjmatkovich.github.io sjmatkovich.github.io Public

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3. Limma differential gene expression, ... Limma differential gene expression, without empirical Bayes moderation

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   # A *limma* workflow without empirical Bayes moderation of t-statistics

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   **Situation:** You are preparing differential gene expression calculations with the R/Bioconductor *limma* package (including RNA-sequencing extensions such as *limma-voom*). While *limma* offers empirical Bayes moderation of t-statistics ('borrowing' variance estimates across genes), you have a large number of individual samples or have other reasons to avoid this procedure.

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   **Problem:** Omitting the `eBayes` step in the limma workflow means that t-statistics are not calculated, and the useful `topTable` function of the package to summarize differential expression calculations does not function.

4. hbctraining_scRNA-seq_online hbctraining_scRNA-seq_online Public

   Forked from hbctraining/Intro-to-scRNAseq

   Harvard Chan bioinformatics core scRNAseq workshops

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5. Seurat_walkthroughs Seurat_walkthroughs Public

   Customized code and notes based on Seurat website vignettes

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6. OSCA_bioconductor_work OSCA_bioconductor_work Public

   follow-on work for Orchestrating Single-Cell Analysis with Bioconductor (book)

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