omada

DOI: 10.18129/B9.bioc.omada  

This is the development version of omada; for the stable release version, see omada.

Machine learning tools for automated transcriptome clustering analysis

Bioconductor version: Development (3.18)

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 "4.3") and enter:

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("omada")

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

Documentation

PDF		Reference Manual

Details

biocViews	Clustering, GeneExpression, RNASeq, Software
Version	1.3.0
In Bioconductor since	BioC 3.16 (R-4.2) (0.5 years)
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
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Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/omada
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/omada
Package Short Url	https://bioconductor.org/packages/omada/
Package Downloads Report	Download Stats