https://github.com/seandavi/refinebioc
The bridge between refine.bio and Bioconductor
https://github.com/seandavi/refinebioc
bioconductor bioinformatics cancer cancer-genomics genomics oncology u24ca289073
Last synced: about 2 months ago
JSON representation
The bridge between refine.bio and Bioconductor
- Host: GitHub
- URL: https://github.com/seandavi/refinebioc
- Owner: seandavi
- License: other
- Created: 2021-12-15T04:35:54.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2025-03-05T04:56:25.000Z (7 months ago)
- Last Synced: 2025-04-12T07:39:43.278Z (6 months ago)
- Topics: bioconductor, bioinformatics, cancer, cancer-genomics, genomics, oncology, u24ca289073
- Language: R
- Homepage: https://seandavi.github.io/refinebioc/
- Size: 10.8 MB
- Stars: 1
- Watchers: 2
- Forks: 2
- Open Issues: 5
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
Awesome Lists containing this project
README
---
output:
github_document
---
# refinebioc
This package provides the bridge between Bioconductor and the vast,
homogeneously-processed transcriptomic
data from [refine.bio](https://www.refine.bio).
Cite the refine.bio project as:
> Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets. URL: https://www.refine.bio
## Status
This project is undergoing active development and not meant for general use.
## Installation
```{r eval=FALSE}
install.packages("BiocManager")
BiocManager::install("seandavi/RefineBio")
```
## Usage
### Available Experiments
RefineBio has a large number of experiments available. You can get a list of
all of them with:
```{r cache=TRUE}
library(RefineBio)
experiments <- experiment_listing()
head(experiments)
dim(experiments)
```
Refine.bio uses multiples sources for data. A simple breakdown can
be obtained with:
```{r}
sort(
table(gsub("[0-9]", "", experiments$accession_code)),
decreasing = TRUE
)
```
### Create and download a dataset
An "experiment" for refine.bio is a collection of samples that were
processed together. A "dataset" is a collection of experiments that
you want to analyze together. You can create a dataset with:
```{r eval=FALSE}
dset <- rb_dataset_request("GSE1133")
```
This will create a dataset object that you can use to download and
analyze the data. The "request" is just that. It does not download
or process the data. To get to actual data loaded into R, you
need to do the following:
```{r eval=FALSE}
rb_dataset_ensure_started(dset)
rb_wait_for_dataset(dset)
rb_dataset_download(dset)
rb_dataset_extract(dset)
gselist <- rb_dataset_load(dset)
```
And the resulting list of SummarizedExperiment objects is:
```{r eval=FALSE}
gselist
```
```
$GSE1133
class: SummarizedExperiment
dim: 11868 158
metadata(13): accession_code description ... technology title
assays(1): exprs
rownames: NULL
rowData names(1): Gene
colnames(158): GSM18865 GSM18866 ... GSM19021 GSM19022
colData names(57): refinebio_accession_code experiment_accession ... title type
```
## Developer checklist
- [ ] Add tests
- [ ] Run `devtools::test()`
- [ ] Run `devtools::check()`
- [ ] Run `devtools::document()`
- [ ] Run `devtools::build()`
- [ ] Update `READMERmd`
- [ ] Run `devtools::build_readme()`
- [ ] Update `NEWS.md`
- [ ] Update `DESCRIPTION`
### Notes
- We use [`roxygen2`](https://roxygen2.r-lib.org/) for documentation, including for [R6 classes](https://github.com/mlr-org/mlr3/wiki/Roxygen-R6-Guide)
- We use [`testthat`](https://testthat.r-lib.org/) for testing
- We use the [tidyverse style for the NEWS.md file](https://style.tidyverse.org/news.html)