Pigengene
Infers biological signatures from gene expression data
Bioconductor version: 3.23 · Package version: 1.38.0
Pigengene package provides an efficient way to infer biological signatures from gene expression profiles. The signatures are independent from the underlying platform, e.g., the input can be microarray or RNA Seq data. It can even infer the signatures using data from one platform, and evaluate them on the other. Pigengene identifies the modules (clusters) of highly coexpressed genes using coexpression network analysis, summarizes the biological information of each module in an eigengene, learns a Bayesian network that models the probabilistic dependencies between modules, and builds a decision tree based on the expression of eigengenes.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Pigengene") Details
| Maintainer | Habil Zare <zare@u.washington.edu> |
| Author | Habil Zare, Amir Foroushani, Rupesh Agrahari, Meghan Short, Isha Mehta, Neda Emami, and Sogand Sajedi |
| License | GPL (>=2) |
| Downloads rank | 348 |
| Source branch | RELEASE_3_23 |
| biocViews | BiomedicalInformatics, Classification, Clustering, DecisionTree, DimensionReduction, GeneExpression, GraphAndNetwork, ImmunoOncology, Microarray, Network, NetworkInference, Normalization, PrincipalComponent, RNASeq, Software, SystemsBiology, Transcriptomics |
Documentation
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Dependencies
Depends: R (>= 4.0.3), graph, BiocStyle (>= 2.28.0)
Imports: bnlearn (>= 4.7), C50 (>= 0.1.2), MASS, matrixStats, partykit, Rgraphviz, WGCNA, GO.db, impute, preprocessCore, grDevices, graphics, stats, utils, parallel, pheatmap (>= 1.0.8), dplyr, gdata, clusterProfiler, ReactomePA, ggplot2, openxlsx, DBI, DOSE
Suggests: org.Hs.eg.db (>= 3.7.0), org.Mm.eg.db (>= 3.7.0), biomaRt (>= 2.30.0), knitr, AnnotationDbi, energy
Reverse dependencies
Imports Me (1): iNETgrate