README.md

In arh2207/APJaccard: Functions that assist using Jaccard similarity with AP clustering

title: "APJaccard Tutorial" authors: - Andrew Howe - Kelly Jones

Authors: Andrew Howe, Kelly Jones Contacts:

• Andrew Howe: [e-mail]
• Kelly Jones: [e-mail]

Overview

A package with functions that facilitate analysis of AP Clustering solutions using the Jaccard similarity index

Installation

Here's how you can install the APJaccard package:

install.packages(c("cluster", "ggplot2", "devtools", "Seurat", 
                   "pheatmap", "BiocManager", "RColorBrewer", 
           "stringr", "apcluster", "igraph", "Matrix",
                   "tidyverse", "mcclust", "philentropy"))
BiocManager::install("viper")
BiocManager::install("biomaRt")
devtools::install_github("JEFworks/MUDAN")
devtools::install_github(repo = "califano-lab/PISCES", force = TRUE, build_vignettes = TRUE)
devtools::install_github('https://github.com/arh2207/APTestPipeline')
devtools::install_github('https://github.com/jchiquet/aricode')

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References

1. Frey, J. and Dueck, D. (2007) Clustering by Passing Messages Between Data Points. Science, 135, 972-6.
2. Kozakura, Y. et al. (2017) Comparison of Methods for Single-Cell Transcrip-tome Analysis Information Processing. Society of Japan Technical Report, BIO-51, 1-6.

Acknowledgements

Philippe Chlenski - TA of Computational Genomics at Columbia University Dr. Itsik Pe'er - Professor of Computational Genomics at Columbia University

arh2207/APJaccard documentation built on May 19, 2022, 11:59 p.m.