APL

R package for computing Association Plots

https://github.com/vingronlab/apl

Science Score: 13.0%

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Low similarity (15.0%) to scientific vocabulary

Last synced: 10 months ago · JSON representation

Repository

R package for computing Association Plots

Basic Info

Host: GitHub
Owner: VingronLab
License: gpl-3.0
Language: R
Default Branch: main
Homepage: https://vingronlab.github.io/APL/
Size: 15.8 MB

Statistics

Stars: 16
Watchers: 2
Forks: 5
Open Issues: 0
Releases: 0

Created over 4 years ago · Last pushed over 1 year ago

Metadata Files

Readme Changelog License

APL

APL is a package developed for computation of Association Plots, a method for visualization and analysis of single cell transcriptomics data. The main focus of APL is the identification of genes characteristic for individual clusters of cells from input data.

When working with APL package please cite: Gralinska, E., Kohl, C., Fadakar, B. S., & Vingron, M. (2022). Visualizing Cluster-specific Genes from Single-cell Transcriptomics Data Using Association Plots. Journal of Molecular Biology, 434(11), 167525.

Installation

The APL can be installed from GitHub:

library(devtools)
install_github("VingronLab/APL")

To additionally build the package vignette, run instead:

install_github("VingronLab/APL", build_vignettes = TRUE, dependencies = TRUE)

Building the vignette will however take considerable time.

The vignette can also be found under the link: https://vingronlab.github.io/APL/ (hyperlink in the GitHub repository description).

To install the APL from Bioconductor, run:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("APL")

Pytorch installation

In order to speed up the singular value decomposition, we highly recommend the installation of pytorch. Users can instead also opt to use the slower R native SVD. For this, please set the argument python = FALSE wherever applicable in the package vignette.

Install pytorch with reticulate

library(reticulate)
install_miniconda() 
conda_install(envname = "r-reticulate", packages = "numpy")
conda_install(envname = "r-reticulate", packages = "pytorch")

Manually install pytorch with conda

Download the appropriate Miniconda installer for your system from the conda website. Follow the installation instructions on their website and make sure the R package reticulate is also installed before proceeding. Once installed, list all available conda environments via
conda info --envs
One of the environments should have r-reticulate in its name. Depending on where you installed it and your system, the exact path might be different. Activate the environment and install pytorch into it.

conda activate ~/.local/share/r-miniconda/envs/r-reticulate # change path accordingly.
conda install numpy
conda install pytorch

Feature overview

Please run

vignette("APL")

after installation with build_vignettes = TRUE for an introduction into the package.

Owner

Name: VingronLab
Login: VingronLab
Kind: user
Location: Berlin, Germany
Company: Max Planck Institute for Molecular Genetics

Website: https://www.molgen.mpg.de/93952/vingron-lab
Twitter: VingronLab
Repositories: 3
Profile: https://github.com/VingronLab

GitHub Events

Total

Issues event: 1
Watch event: 1
Delete event: 7
Issue comment event: 1
Push event: 29
Pull request review event: 2
Pull request event: 8
Create event: 3

Last Year

Issues event: 1
Watch event: 1
Delete event: 7
Issue comment event: 1
Push event: 29
Pull request review event: 2
Pull request event: 8
Create event: 3

Issues and Pull Requests

Last synced: 10 months ago

All Time

Total issues: 7
Total pull requests: 9
Average time to close issues: about 1 month
Average time to close pull requests: about 1 month
Total issue authors: 5
Total pull request authors: 4
Average comments per issue: 2.43
Average comments per pull request: 0.33
Merged pull requests: 9
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 4
Average time to close issues: N/A
Average time to close pull requests: 1 minute
Issue authors: 0
Pull request authors: 2
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull requests: 4
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

ms-gx (3)
yanzhaobiomath (1)
Gesmira (1)
afederico-sci (1)
malcook (1)

Pull Request Authors

ClemensKohl (11)
VingronLab (2)
elagralinska (1)
MathurinD (1)

Top Labels

Issue Labels

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Packages

Total packages: 1
Total downloads:
- bioconductor 7,803 total

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 6
Total maintainers: 1

bioconductor.org: APL

Association Plots

Homepage: https://vingronlab.github.io/APL/
Documentation: https://bioconductor.org/packages/release/bioc/vignettes/APL/inst/doc/APL.pdf
License: GPL (>= 3)
Latest release: 1.12.0
published about 1 year ago

Versions: 6
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 7,803 Total

Rankings

Dependent repos count: 0.0%

Dependent packages count: 0.0%

Average: 27.5%

Downloads: 82.4%

Maintainers (1)

kohl.clemens@gmail.com