https://github.com/lgatto/qfeaturesworkshop2020
QFeatures: Quantitative features for mass spectrometry data
https://github.com/lgatto/qfeaturesworkshop2020
Last synced: about 2 months ago
JSON representation
QFeatures: Quantitative features for mass spectrometry data
- Host: GitHub
- URL: https://github.com/lgatto/qfeaturesworkshop2020
- Owner: lgatto
- Created: 2020-11-30T11:30:04.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-12-15T15:53:23.000Z (over 4 years ago)
- Last Synced: 2025-01-20T22:55:23.874Z (3 months ago)
- Language: Dockerfile
- Homepage: https://lgatto.github.io/QFeaturesWorkshop2020/
- Size: 1.37 MB
- Stars: 1
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
README
# QFeatures EuroBioc2020 Workshop
The
[`QFeatures`](https://rformassspectrometry.github.io/QFeatures/articles/QFeatures.html)
package provides infrastructure (that is classes to store data and the
methods to process and manipulate them) to manage and analyse
quantitative features from mass spectrometry experiments. It is based
on the `SummarizedExperiment` and `MultiAssayExperiment` Bioconductor
classes. Assays in a QFeatures object have a hierarchical relation:
proteins are composed of peptides, themselves produced by
spectra. Throughout the aggregation and processing of these data, the
relations between assays are tracked and recorded, thus allowing users
to easily navigate across spectra, peptide and protein quantitative
data. In this workshop, we will demonstrate how to import data as
QFeatures objects, how to process and analyse data in QFeatures
objects, and how to interpret the results. Some familiarity with
Bioconductor data analysis, in particular the SummarizedExperiment
class, is recommended to follow this short workshop.
The content of this workshop is provided under a [CC-BY
ShareAlike](https://creativecommons.org/licenses/by-sa/2.0/) license.
```{r, warning = FALSE, echo = FALSE, comment = ""}
citation("QFeaturesWorkshop2020")
```
## Running the workshop
You can install all necessary packages to run the workshop locally by
installing the following packages:
```r
## general
install.packages("tidyverse")
install.packages("patchwork")
install.packages("factoextra")
## Bioconductor packages
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("QFeatures")
BiocManager::install("msdata")
BiocManager::install("limma")
```
The
[lgatto/qfeaturesworkshop2020](https://hub.docker.com/repository/docker/lgatto/qfeaturesworkshop2020)
docker container has all packages necessary for running the workshop vignettes.
The container can be downloaded and run with
```sh
docker run -e PASSWORD=bioc -p 8787:8787 lgatto/qfeaturesworkshop2020:latest
```
(you can choose any passwork, not only `bioc`, above)
Once running, navigate to https://localhost:8787/ and then login with
user `rstudio` and password `bioc`.
During the
[EuroBioc2020](https://eurobioc2020.bioconductor.org/workshops)
conference, the workshop can be [run in the
cloud](http://app.orchestra.cancerdatasci.org/).