Other packages > Find by keyword >

metasnf  

Meta Clustering with Similarity Network Fusion
View on CRAN: Click here


Download and install metasnf package within the R console
Install from CRAN:
install.packages("metasnf")

Install from Github:
library("remotes")
install_github("cran/metasnf")

Install by package version:
library("remotes")
install_version("metasnf", "2.0.0")



Attach the package and use:
library("metasnf")
Maintained by
Prashanth S Velayudhan
[Scholar Profile | Author Map]
First Published: 2024-11-08
Latest Update: 2024-11-08
Description:
Framework to facilitate patient subtyping with similarity network fusion and meta clustering. The similarity network fusion (SNF) algorithm was introduced by Wang et al. (2014) in <doi:10.1038/nmeth.2810>. SNF is a data integration approach that can transform high-dimensional and diverse data types into a single similarity network suitable for clustering with minimal loss of information from each initial data source. The meta clustering approach was introduced by Caruana et al. (2006) in <doi:10.1109/ICDM.2006.103>. Meta clustering involves generating a wide range of cluster solutions by adjusting clustering hyperparameters, then clustering the solutions themselves into a manageable number of qualitatively similar solutions, and finally characterizing representative solutions to find ones that are best for the user's specific context. This package provides a framework to easily transform multi-modal data into a wide range of similarity network fusion-derived cluster solutions as well as to visualize, characterize, and validate those solutions. Core package functionality includes easy customization of distance metrics, clustering algorithms, and SNF hyperparameters to generate diverse clustering solutions; calculation and plotting of associations between features, between patients, and between cluster solutions; and standard cluster validation approaches including resampled measures of cluster stability, standard metrics of cluster quality, and label propagation to evaluate generalizability in unseen data. Associated vignettes guide the user through using the package to identify patient subtypes while adhering to best practices for unsupervised learning.
How to cite:
Prashanth S Velayudhan (2024). metasnf: Meta Clustering with Similarity Network Fusion. R package version 2.0.0, https://cran.r-project.org/web/packages/metasnf. Accessed 20 Feb. 2025.
Previous versions and publish date:
1.1.1 (2024-11-08 16:00), 1.1.2 (2024-11-09 00:20)
Other packages that cited metasnf R package
View metasnf citation profile
Other R packages that metasnf depends, imports, suggests or enhances
Complete documentation for metasnf
Functions, R codes and Examples using the metasnf R package
Full metasnf package functions and examples
Downloads during the last 30 days
01/2101/2201/2301/2401/2501/2601/2701/2801/2901/3001/3102/0102/0202/0302/0402/0502/0602/0702/0802/0902/1002/1102/1202/1302/1402/1502/1602/1702/1802/19Downloads for metasnf0102030405060TrendBars
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

multgee  
GEE Solver for Correlated Nominal or Ordinal Multinomial Responses
GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parame ...
Download / Learn more Package Citations See dependency  
PLNmodels  
Poisson Lognormal Models
The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 ...
Download / Learn more Package Citations See dependency  
tigger  
Infers Novel Immunoglobulin Alleles from Sequencing Data
Infers the V genotype of an individual from immunoglobulin (Ig) repertoire sequencing data (AIRR-Seq ...
Download / Learn more Package Citations See dependency  
healthyR.ai  
The Machine Learning and AI Modeling Companion to 'healthyR'
Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This li ...
Download / Learn more Package Citations See dependency  
reader  
Suite of Functions to Flexibly Read Data from Files
A set of functions to simplify reading data from files. The main function, reader(), should read mos ...
Download / Learn more Package Citations See dependency  
EffectStars  
Visualization of Categorical Response Models
Notice: The package EffectStars2 provides a more up-to-date implementation of effect stars! EffectSt ...
Download / Learn more Package Citations See dependency  

23,712

R Packages

205,795

Dependencies

64,332

Author Associations

23,631

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA