Package: GWENA 1.15.0

Gwenaëlle Lemoine

GWENA: Pipeline for augmented co-expression analysis

The development of high-throughput sequencing led to increased use of co-expression analysis to go beyong single feature (i.e. gene) focus. We propose GWENA (Gene Whole co-Expression Network Analysis) , a tool designed to perform gene co-expression network analysis and explore the results in a single pipeline. It includes functional enrichment of modules of co-expressed genes, phenotypcal association, topological analysis and comparison of networks configuration between conditions.

Authors:Gwenaëlle Lemoine [aut, cre], Marie-Pier Scott-Boyer [ths], Arnaud Droit [fnd]

GWENA_1.15.0.tar.gz
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GWENA.pdf |GWENA.html✨
GWENA/json (API)

# Install 'GWENA' in R:

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

Bug tracker:https://github.com/kumquatum/gwena/issues

Datasets:

gtex_expr - Transcriptomic muscle data from GTEx consorsium RNA-seq data
gtex_traits - Traits data linked to samples in transcriptomic data from GTEx
kuehne_expr - Transcriptomic data from the Kuehne et al. publication
kuehne_traits - Traits data linked to samples in transcriptomic data from the Kuehne et al. publication

On BioConductor:GWENA-1.15.0(bioc 3.20)GWENA-1.14.0(bioc 3.19)

bioconductor-package

27 exports 0.61 score 132 dependencies 1 mentions

Last updated 2 months agofrom:3f995f08ec

Exports:associate_phenotype bio_enrich build_graph_from_sq_mat build_net compare_conditions detect_modules filter_low_var filter_RNA_seq get_fit.cor get_fit.expr get_hub_degree get_hub_genes get_hub_high_co get_hub_kleinberg get_sub_clusters is_data_expr is_gost is_module is_network join_gost plot_comparison_stats plot_enrichment plot_expression_profiles plot_module plot_modules_merge plot_modules_phenotype z_summary

Dependencies:abind AnnotationDbi askpass backports base64enc BH Biobase BiocGenerics Biostrings bit bit64 bitops blob bslib cachem checkmate cli cluster codetools colorspace cpp11 crayon crosstalk curl data.table DBI DelayedArray digest doParallel dplyr dynamicTreeCut evaluate fansi farver fastcluster fastmap fontawesome foreach foreign Formula fs generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue GO.db gprofiler2 gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets httr igraph impute IRanges isoband iterators jquerylib jsonlite KEGGREST knitr labeling later lattice lazyeval lifecycle magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime munsell NetRep nlme nnet openssl pillar pkgconfig plogr plotly png preprocessCore promises purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo RCurl RhpcBLASctl rlang rlist rmarkdown rpart RSQLite rstudioapi S4Arrays S4Vectors sass scales SparseArray statmod stringi stringr SummarizedExperiment survival sys tibble tidyr tidyselect tinytex UCSC.utils utf8 vctrs viridis viridisLite WGCNA withr xfun XML XVector yaml zlibbioc

GWENA - Tutorial

Gwenaëlle Lemoine

Rendered fromGWENA_guide.Rmdusingknitr::rmarkdownon Jun 24 2024.

Last update: 2021-06-24
Started: 2019-10-17

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Run checks on an object to test if it's a data_expr	.check_data_expr
Run checks on an object to test if it's a gost result	.check_gost
Run checks on an object to test if it's a module or a list of modules	.check_module
Run checks on an object to test if it's a network	.check_network
Calculate a contigency table of module overlap between datasets	.contingencyTable
Match a correlation function based on a name	.cor_func_match
Modules phenotpic association	associate_phenotype
Modules enrichment	bio_enrich
Return graph from squared matrix network	build_graph_from_sq_mat
Network building by co-expression score computation	build_net
Compare modules topology between conditions	compare_conditions
Modules detection in a network	detect_modules
Filtering genes with low variability	filter_low_var
Filtering of low counts	filter_RNA_seq
Calculating best fit of a power low on correlation matrix computed on expression data	get_fit.cor
Calculating best fit of a power low on expression data	get_fit.expr
Determine hub genes based on degree	get_hub_degree
Determine hub genes inside each module	get_hub_genes
Determine hub genes based on connectivity	get_hub_high_co
Determine hub genes based on Kleinberg's score	get_hub_kleinberg
Detect sub clusters	get_sub_clusters
Mimicking ggplot palette Source : https://stackoverflow.com/questions/8197559/emulate-ggplot2-default-color-palette	gg_palette
Transcriptomic muscle data from GTEx consorsium RNA-seq data	gtex_expr
Traits data linked to samples in transcriptomic data from GTEx	gtex_traits
Determine if an object is a data_expr in sens of GWENA	is_data_expr
Determine if an object is a gost object	is_gost
Determine if an object is a module or a list of modules	is_module
Determine if an object is a network	is_network
Join gprofiler2::gost results	join_gost
Transcriptomic data from the Kuehne et al. publication	kuehne_expr
Traits data linked to samples in transcriptomic data from the Kuehne et al. publication	kuehne_traits
Heatmap of comparison statistics	plot_comparison_stats
Plot module from bio_enrich	plot_enrichment
Modules expression profiles	plot_expression_profiles
Plot co-expression network	plot_module
Modules merge plot	plot_modules_merge
Heatmap of modules phenotpic association	plot_modules_phenotype
Muting a function	quiet
Calculating Z summary	z_summary