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Update the tutorial
- Adding an additional section on isotope identification.
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DESCRIPTION

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Package: xcmsTutorials
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Title: Exploring and Analyzing LC-MS data with Spectra and xcms
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Version: 1.0.4
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Version: 1.1.0
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Authors@R: c(
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person(given = "Johannes", family = "Rainer",
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email = "[email protected]",
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knitr,
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rmarkdown,
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RColorBrewer,
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SummarizedExperiment
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SummarizedExperiment,
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pheatmap
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URL: https://jorainer.github.io/xcmsTutorials/
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BugReports: https://github.com/jorainer/xcmsTutorials/issues/new
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VignetteBuilder: knitr

Dockerfile

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FROM bioconductor/bioconductor_docker:RELEASE_3_18
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FROM bioconductor/bioconductor_docker:devel
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LABEL name="jorainer/xcms_tutorials" \
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url="https://github.com/jorainer/xcmsTutorials" \

NEWS.md

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# xcmsTutorials 1.0
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## Changes in 1.1.0
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- Use Bioconductor 3.19 devel release.
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- Add examples for simple quality assessment of BPC or BPS data.
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- Introduce parameter `ppm` for `PeakDensityParam` correspondence analysis
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method.
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- Add an additional section for extraction of chromatographic or spectra data
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for identified chromatographic peaks and perform isotopologue search in these.
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## Changes in 1.0.4
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- Use the Bioconductor 3.18 release docker image.

README.md

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![MsCoreUtils](man/figures/MsCoreUtils.png)
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This workshop provides an overview of recent developments in Bioconductor to
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work with mass spectrometry
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work with mass spectrometry data
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([MsExperiment](https://github.com/RforMassSpectrometry/MsExperiment),
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[Spectra](https://github.com/RforMassSpectrometry/Spectra)) and specifically
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LC-MS data ([xcms](https://github.com/sneumann/xcms)) and walks through the
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preprocessing of a small data set emphasizing on selection of data-dependent
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settings for the individual pre-processing steps.
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settings for the individual preprocessing steps.
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Covered topics are:
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## Installation
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For on-line code evaluation, the workshop can also be run using a self-contained
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docker image with all R packages and a server version of RStudio (Posit)
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pre-installed:
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The workshop files along with an R runtime environment including all required
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packages and the RStudio (Posit) editor are all bundled in a *docker*
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container. After installation, this docker container can be run on the computer
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and the code and examples from the workshop can be evaluated within this
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environment (without the need to install any additional packages or files). The
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required steps for installation are:
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- If you don't already have, install [docker](https://www.docker.com/). Find
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installation information [here](https://docs.docker.com/desktop/).
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-e PASSWORD=bioc \
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-p 8787:8787 \
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jorainer/xcms_tutorials:latest
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```
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```
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- Enter `http://localhost:8787` in a web browser and log in with username
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`rstudio` and password `bioc`.
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- In the RStudio server version: open any of the R-markdown (*.Rmd*) files in
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the *vignettes* folder and evaluate the R code blocks.
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the *vignettes* folder and evaluate the R code blocks in that document.
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For manual installation, an R version >= 4.3.0 is required as well as recent
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https://rformassspectrometry.github.io/MetaboAnnotation/
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- Repository of the `CompoundDb` package:
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https://rformassspectrometry.github.io/CompoundDb/
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# Acknowledgments
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Thank you to [Philippine Louail](https://github.com/philouail) for fixing typos
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and suggesting improvements.

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