omada

DOI: 10.18129/B9.bioc.omada  

Machine learning tools for automated transcriptome clustering analysis

Bioconductor version: Release (3.16)

Symptomatic heterogeneity in complex diseases reveals differences in molecular states that need to be investigated. However, selecting the numerous parameters of an exploratory clustering analysis in RNA profiling studies requires deep understanding of machine learning and extensive computational experimentation. Tools that assist with such decisions without prior field knowledge are nonexistent and further gene association analyses need to be performed independently. We have developed a suite of tools to automate these processes and make robust unsupervised clustering of transcriptomic data more accessible through automated machine learning based functions. The efficiency of each tool was tested with four datasets characterised by different expression signal strengths. Our toolkit’s decisions reflected the real number of stable partitions in datasets where the subgroups are discernible. Even in datasets with less clear biological distinctions, stable subgroups with different expression profiles and clinical associations were found.

Author: Sokratis Kariotis [aut, cre]

Maintainer: Sokratis Kariotis <sokratiskariotis at gmail.com>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("omada")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("omada")

 

HTML	R Script	my-vignette
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	Clustering, GeneExpression, RNASeq, Software
Version	1.0.0
In Bioconductor since	BioC 3.16 (R-4.2) (< 6 months)
License	GPL-3
Depends	pdfCluster (>= 1.0-3), kernlab (>= 0.9-29), R (>= 4.2), fpc (>= 2.2-9), Rcpp (>= 1.0.7), diceR (>= 0.6.0), ggplot2 (>= 3.3.5), reshape (>= 0.8.8), clusterCrit (>= 1.2.8), clValid (>= 0.7), glmnet (>= 4.1.3), dplyr (>= 1.0.7), stats (>= 4.1.2)
Imports
LinkingTo
Suggests	rmarkdown, knitr, testthat
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	omada_1.0.0.tar.gz
Windows Binary	omada_1.0.0.zip
macOS Binary (x86_64)	omada_1.0.0.tgz
macOS Binary (arm64)	omada_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/omada
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/omada
Bioc Package Browser	https://code.bioconductor.org/browse/omada/
Package Short Url	https://bioconductor.org/packages/omada/
Package Downloads Report	Download Stats