KBoost
Inference of gene regulatory networks from gene expression data
Bioconductor version: Release (3.19)
Reconstructing gene regulatory networks and transcription factor activity is crucial to understand biological processes and holds potential for developing personalized treatment. Yet, it is still an open problem as state-of-art algorithm are often not able to handle large amounts of data. Furthermore, many of the present methods predict numerous false positives and are unable to integrate other sources of information such as previously known interactions. Here we introduce KBoost, an algorithm that uses kernel PCA regression, boosting and Bayesian model averaging for fast and accurate reconstruction of gene regulatory networks. KBoost can also use a prior network built on previously known transcription factor targets. We have benchmarked KBoost using three different datasets against other high performing algorithms. The results show that our method compares favourably to other methods across datasets.
Author: Luis F. Iglesias-Martinez [aut, cre] , Barbara de Kegel [aut], Walter Kolch [aut]
Maintainer: Luis F. Iglesias-Martinez <luis.iglesiasmartinez at ucd.ie>
citation("KBoost")
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Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("KBoost")
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("KBoost")
KBoost | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Bayesian, GeneExpression, GeneRegulation, GraphAndNetwork, Network, NetworkInference, PrincipalComponent, Regression, Software, SystemsBiology, Transcription, Transcriptomics |
Version | 1.12.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (3.5 years) |
License | GPL-2 | GPL-3 |
Depends | R (>= 4.1), stats, utils |
Imports | |
System Requirements | |
URL | https://github.com/Luisiglm/KBoost |
See More
Suggests | knitr, rmarkdown, 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 | KBoost_1.12.0.tar.gz |
Windows Binary (x86_64) | KBoost_1.12.0.zip |
macOS Binary (x86_64) | KBoost_1.12.0.tgz |
macOS Binary (arm64) | KBoost_1.12.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/KBoost |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/KBoost |
Bioc Package Browser | https://code.bioconductor.org/browse/KBoost/ |
Package Short Url | https://bioconductor.org/packages/KBoost/ |
Package Downloads Report | Download Stats |