Package: Pigengene 1.39.0

Habil Zare

Pigengene: Infers biological signatures from gene expression data

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.

Authors:Habil Zare, Amir Foroushani, Rupesh Agrahari, Meghan Short, Isha Mehta, Neda Emami, and Sogand Sajedi

Pigengene_1.39.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Pigengene/json (API)

# Install 'Pigengene' in R:

install.packages('Pigengene', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

aml - AML gene expression profile
eigengenes33 - Eigengenes of 33 modules
mds - MDS gene expression profile
pigengene - An object of class 'Pigengene'

On BioConductor:Pigengene-1.39.0(bioc 3.24)Pigengene-1.38.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

geneexpression rnaseq networkinference network graphandnetwork biomedicalinformatics systemsbiology transcriptomics classification clustering decisiontree dimensionreduction principalcomponent microarray normalization immunooncology

4.64 score 1 packages 12 scripts 4 mentions 29 exports 171 dependencies

Last updated from:cc08c7aba6. Checks:3 ERROR, 5 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	331
linux-devel-x86_64	NOTE	711
source / vignettes	OK	484
linux-release-x86_64	ERROR	502
macos-release-arm64	NOTE	490
macos-oldrel-arm64	NOTE	454
windows-devel	NOTE	666
windows-release	NOTE	677
windows-oldrel	ERROR	481
wasm-release	OK	324

Exports:apply.filter balance calculate.beta check.nas check.pigengene.input combine.networks compact.tree compute.pigengene dcor.matrix determine.modules draw.bn gene.mapping get.enriched.pw get.fitted.leaf get.genes get.used.features learn.bn make.decision.tree make.filter message.if module.heatmap one.step.pigengene pheatmap.type plot.pigengene preds.at project.eigen pvalues.manova save.if wgcna.one.step

Dependencies:aisdk AnnotationDbi ape aplot askpass backports base64enc Biobase BiocGenerics BiocManager BiocStyle Biostrings bit bit64 blob bnlearn bookdown bslib C50 cachem callr checkmate cli cluster clusterProfiler codetools colorspace cpp11 crayon Cubist curl data.table DBI digest dir.expiry doParallel DOSE dplyr dynamicTreeCut enrichit enrichplot evaluate farver fastcluster fastmap filelock fontawesome fontBitstreamVera fontLiberation fontquiver foreach foreign Formula fs gdata gdtools generics ggforce ggfun ggiraph ggnewscale ggplot2 ggplotify ggraph ggrepel ggtangle ggtree glue GO.db GOSemSim graph graphite graphlayouts gridExtra gridGraphics gson gtable gtools highr Hmisc htmlTable htmltools htmlwidgets httr httr2 igraph impute inum IRanges isoband iterators jquerylib jsonlite KEGGREST knitr labeling lattice lazyeval libcoin lifecycle magrittr MASS Matrix matrixStats memoise mime mvtnorm nlme nnet openssl openxlsx otel partykit patchwork pheatmap pillar pkgconfig plyr png polyclip preprocessCore processx ps purrr qvalue R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen reactome.db ReactomePA reshape2 Rgraphviz rlang rmarkdown rpart RSQLite rstudioapi S4Vectors S7 sass scales scatterpie Seqinfo stringi stringr survival sys systemfonts tibble tidydr tidygraph tidyr tidyselect tidytree tinytex treeio tweenr utf8 vctrs viridis viridisLite WGCNA withr xfun XVector yaml yulab.utils zip

Pigengene: Computing and using eigengenes

1 Introduction | 2 How to run Pigengene ? | 3 Session Information

Rendered fromPigengene_inference.Rnwusingknitr::knitr

Last update: 2021-10-14
Started: 2016-05-26

Help page	Topics
Infers robust biological signatures from gene expression data	Pigengene-package Pigengene
AML gene expression profile	aml
Applies a given filter on the data	apply.filter
Balances the number of samples	balance
Estimates an appropriate power value	calculate.beta
Removes 'NA's from a data matrix	check.nas
Quality check on the imput	check.pigengene.input
Combines two or more networks	combine.networks
Reduces the number of genes in a decision tree	compact.tree
Computes the eigengenes	compute.pigengene
Computes distance correlation for give matrix	dcor.matrix
Identifies modules of the network	determine.modules
Draws a Bayesian network	draw.bn
Eigengenes of 33 modules	eigengenes33
Maps gene IDs	gene.mapping
Performs pathway over representation analysis	get.enriched.pw
Returs the leaf for each sample	get.fitted.leaf
List the (most relevant) genes for a decision tree.	get.genes
Return the features used in a tree	get.used.features
Learns a Bayesian network	learn.bn
Creates a decision tree to classify samples using the eigengenes values	make.decision.tree
Computes the filter based on a similarity network	make.filter
MDS gene expression profile	mds
Conditional messaging.	message.if
Plots heatmaps for modules	module.heatmap
Runs the entire Pigengene pipeline	one.step.pigengene
Plots heatmap with clustering only within types.	pheatmap.type
An object of class 'Pigengene'	pigengene
The pigengene class	pigengene-class plot, pigengene-method
Plots and saves a 'pigengene' object	plot.pigengene
Prediction using a possibly compacted tree	preds.at
Infers eigengenes for given expression data	project.eigen
Computes pvalues for multi-class differential expression	pvalues.manova
Saves an object verbosely.	save.if
Module identification	wgcna.one.step

Package: Pigengene 1.39.0

Pigengene: Infers biological signatures from gene expression data

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