Git Product home page Git Product logo

apl's Introduction

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:

Association Plots: Visualizing associations in high-dimensional correspondence analysis biplots
Elzbieta Gralinska, Martin Vingron
bioRxiv 2020.10.23.352096; doi: https://doi.org/10.1101/2020.10.23.352096

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.

apl's People

Contributors

elagralinska avatar clemenskohl avatar vingronlab avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.