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Add renv for reproducibility, good practices for deployment #11

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20b8cd9
add renv for reproducibility
amrukwa Aug 18, 2025
49f6096
update README
amrukwa Aug 19, 2025
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1 change: 1 addition & 0 deletions .Rprofile
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source("renv/activate.R")
19 changes: 15 additions & 4 deletions README.md
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Expand Up @@ -16,22 +16,33 @@ Implemented thresholding solutions:
3) GMM thresholding with Top 1 and k-means adjustment (Zyla et al. 2025?)

## Installation
As the FUNCellA uses other packages from Biocunductor please install at first GSVA and AUCell pacakges.
### Traditional installation
As the FUNCellA uses other packages from Bioconductor please install at first GSVA and AUCell packages.
``` r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
install.packages("BiocManager")
BiocManager::install(c("GSVA", "AUCell"))
```
Next install package from git by devtools.

``` r
install.packages("devtools")
devtools::install_github("ZAEDPolSl/dpGMM")
devtools::install_github("ZAEDPolSl/FUNCellA")
```
### Installation with renv
You can install the package with renv. It is similar to the traditional approach, you just don't need to install the repositories manually.
```r
install.packages("renv")
renv::install("ZAEDPolSl/FUNCellA")
```
This should work without any additional steps. However, if the GSVA or AUCell are not available and you get errors, please install them manually.

## Running on the remote server
Alternatively, you can use our website application available [here](https://dssoftware.aei.polsl.pl/FUNCellA). It is free of charge and it does not store your data. Feel free to use it!

## Example of run
### Data
At first let's perpare a data. You need a matrix or data.frame of your molecular biology data e.g. scRNA-Seq counts. You can use your own data or check the example from Seurat Pacakge.
At first let's prepare a data. You need a matrix or data.frame of your molecular biology data e.g. scRNA-Seq counts. You can use your own data or check the example from Seurat Pacakge.
It is very important that in rownames you will have features names (genes/transripts) of the same name as in the pathways you would like to chcek.
``` r
library(FUNCellA)
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