From 71c5690c9fbc42f636e1b5d75499d52d020ee886 Mon Sep 17 00:00:00 2001 From: lgeistlinger Date: Fri, 10 May 2024 15:20:56 -0400 Subject: [PATCH] HCA session: another shot at getting the image to render --- README.md | 11 ++++------- episodes/hca.Rmd | 4 +++- episodes/intro-sce.Rmd | 2 +- 3 files changed, 8 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 9845770..c7135bb 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,5 @@ # Orchestrating Single-Cell Analysis with Bioconductor -This is a pre-alpha adaptation of the 2023 ISMB OSCA tutorial using The Carpentries Workbench lesson template. - -### Vignettes converted - -As individual vignettes are converted into lessons, they can be added to `config.yaml` to be rendered and shown in the final Github Pages lesson. - ## Description In the last few years, the profiling of a large number of genome-wide features @@ -44,5 +38,8 @@ In particular, participants will learn: ## Source -This lesson is a template lesson that uses [The Carpentries Workbench](https://carpentries.github.io/sandpaper-docs/) and is based on materials from the [OSCA tutorial at the ISMB 2023](https://bioconductor.github.io/ISMB.OSCA/). +This lesson uses [The Carpentries Workbench](https://carpentries.github.io/sandpaper-docs/) and is based on materials from the [OSCA tutorial at the ISMB 2023](https://bioconductor.github.io/ISMB.OSCA/). + +As individual vignettes are converted into lessons, they can be added to `config.yaml` to be rendered and shown in the final Github Pages lesson. + diff --git a/episodes/hca.Rmd b/episodes/hca.Rmd index c85ce35..1fa17c4 100644 --- a/episodes/hca.Rmd +++ b/episodes/hca.Rmd @@ -69,7 +69,9 @@ bulk counts are also available to facilitate large-scale, summary analyses of transcriptional profiles. This platform offers a standardized workflow for accessing atlas-level datasets programmatically and reproducibly. -![](figures/curatedAtlasQuery.png) +```{r, echo = FALSE} +knitr::include_graphics("https://raw.githubusercontent.com/ccb-hms/osca-workbench/main/episodes/figures/curatedAtlasQuery.png") +``` ## Data Sources in R / Bioconductor diff --git a/episodes/intro-sce.Rmd b/episodes/intro-sce.Rmd index 7124c84..846c665 100644 --- a/episodes/intro-sce.Rmd +++ b/episodes/intro-sce.Rmd @@ -104,7 +104,7 @@ Users should be able to analyze their data using functions from different Biocon This class implements a data structure that stores all aspects of our single-cell data - gene-by-cell expression data, per-cell metadata and per-gene annotation - and manipulate them in a synchronized manner. ```{r, echo=FALSE} -knitr::include_graphics("http://bioconductor.org/books/3.17/OSCA.intro/images/SingleCellExperiment.png") +knitr::include_graphics("http://bioconductor.org/books/release/OSCA.intro/images/SingleCellExperiment.png") ``` Let's start with an example dataset.