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index.Rmd
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index.Rmd
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---
title: "Cytomapper publication"
author:
- name: Nils Eling
affiliation: Department for Quantitative Biomedicine, University of Zurich
email: nils.eling@dqbm.uzh.ch
- name: Nicolas Damond
affiliation: Department for Quantitative Biomedicine, University of Zurich
email: nicolas.damond@dqbm.uzh.ch
- name: Tobias Hoch
affiliation: Department for Quantitative Biomedicine, University of Zurich
email: tobias.hoch@dqbm.uzh.ch
date: "`r Sys.Date()`"
site: workflowr::wflow_site
output:
workflowr::wflow_html:
toc: false
editor_options:
chunk_output_type: console
---
The scripts hosted on this website serve the purpose of testing, validating and publishing the [cytomapper](https://www.bioconductor.org/packages/release/bioc/html/cytomapper.html) package.
## Setting up the environment
For reproducibility purposes, we use [Docker](https://www.docker.com/) and [workflowr](https://jdblischak.github.io/workflowr/index.html) to organize the scripts and the computational environment.
Please follow these steps to set-up and run the analysis presented on this website:
1. Install [Docker](https://docs.docker.com/get-docker/)
2. Pull the [docker image](https://hub.docker.com/repository/docker/nilseling/bioconductor_cytomapper/tags?page=1)
```
docker pull nilseling/bioconductor_cytomapper:0.0.1
```
3. Run the docker image
```
docker run -e PASSWORD=bioc -p 8787:8787 nilseling/bioconductor_cytomapper:0.0.1
```
Here, the set `PASSWORD` is bioc. This will be used to login to RStudio later.
4. Open a browser window at `http://localhost:8787/`
5. Sign in to RStudio using `Username: rstudio` and `Password: bioc`
You have now a running instance of all the software needed to reproduce the analysis.
## Running the code
The following steps will guide you through running the analsysis:
1. Within RStudio, navigate to `cytmapper_publication`
2. By clicking `cytomapper_publication.Rproj`, open the correct R project
3. Navigate to `analysis` and run the scripts in the provided order
Further instructions can be found in the individual scripts.
## Installing `cytomapper`
The `cytomapper` version used for the bioRxiv submission can be installed via:
```r
install.packages(c("devtools", "workflowr", "tidyverse"))
devtools::install_github("BodenmillerGroup/cytomapper@v1.1.2")
```
The Bioconductor release version of `cytomapper` can be obtained from [Bioconductor](https://www.bioconductor.org/packages/release/bioc/html/cytomapper.html).
The following code will also install additional packages needed to perform the analysis.
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("cytomapper", "workflowr", "tidyverse"))
```
The Bioconductor development version of `cytomapper` can be installed via:
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(version = "3.12", update = TRUE, ask = FALSE)
BiocManager::install(c("cytomapper", "workflowr", "tidyverse"))
```
## Data
The example dataset used for this analysis has been published in:
[https://www.cell.com/cell-metabolism/fulltext/S1550-4131(18)30691-0](https://www.cell.com/cell-metabolism/fulltext/S1550-4131(18)30691-0)
The dataset is available for download from Mendeley Data: [http://dx.doi.org/10.17632/cydmwsfztj.2](http://dx.doi.org/10.17632/cydmwsfztj.2)
Specifically, the following files are used in the current analysis:
- `CellSubset`: Single cell data for a subset of 100 images from the original publication.
- `ImageSubset`: Image stacks for a subset of 100 images from the original publication.
- `Masks`: Cell masks as TIFF files.
- `Image`: Image metadata.
- `CellTypes`: Cell type information.
- `Donors`: Pancreas donors metadata.
- `Panel`: Antibody panel.
- `ChannelMass`: File used to match channels (stack slices) and metals (antibodies).