omada
This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see omada.
Machine learning tools for automated transcriptome clustering analysis
Bioconductor version: 3.17
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>
citation("omada")):
Installation
To install this package, start R (version "4.3") 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")| my-vignette | HTML | R Script |
| Reference Manual | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | Clustering, GeneExpression, RNASeq, Software |
| Version | 1.1.0 |
| In Bioconductor since | BioC 3.16 (R-4.2) (1.5 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 | |
| System Requirements | |
| URL |
See More
| Suggests | rmarkdown, knitr, testthat |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | omada_1.1.0.tar.gz |
| Windows Binary | omada_1.1.0.zip |
| macOS Binary (x86_64) | |
| macOS Binary (arm64) | omada_1.1.0.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 |
| Old Source Packages for BioC 3.17 | Source Archive |