Package: CoNI 0.1.0

CoNI: Correlation Guided Network Integration (CoNI)

Integrates two numerical omics data sets from the same samples using partial correlations. The output can be represented as a network, bipartite graph or a hypergraph structure. The method used in the package refers to Klaus et al (2021) <doi:10.1016/j.molmet.2021.101295>.

Authors:José Manuel Monroy Kuhn [aut, cre], Dominik Lutter [ths], Valentina Klaus [ctb]

CoNI_0.1.0.tar.gz
CoNI_0.1.0.zip(r-4.7)CoNI_0.1.0.zip(r-4.6)CoNI_0.1.0.zip(r-4.5)
CoNI_0.1.0.tgz(r-4.6-any)CoNI_0.1.0.tgz(r-4.5-any)
CoNI_0.1.0.tar.gz(r-4.7-any)CoNI_0.1.0.tar.gz(r-4.6-any)
CoNI_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CoNI/json (API)

# Install 'CoNI' in R:

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

Bug tracker:https://github.com/jmanuelmk/coni/issues

Datasets:

Chow_GeneExpData - Chow gene expression data
Chow_MetaboliteData - Chow metabolite data
CoNIResults_Chow - CoNI Results Chow
CoNIResults_HFD - CoNI Results HFD
CoNIResultsHFDToy - Toy data HFD results
GeneExpToy - Toy data gene expression
HFD_GeneExpData - HFD gene expression data
HFD_MetaboliteData - HFD metabolite data
MetaboExpToy - Toy data metabolite expression
MetaboliteAnnotation - Metabolite Annotation
MetColorTable - Toy data annotation
VertexClassesSharedGenes_HFDvsChow - Toy data comparison treatments

On CRAN:

3.70 score 2 scripts 248 downloads 17 exports 111 dependencies

Last updated from:a5b5530328. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	252
source / vignettes	OK	240
linux-release-x86_64	NOTE	234
macos-release-arm64	NOTE	223
macos-oldrel-arm64	NOTE	224
windows-devel	NOTE	251
windows-release	NOTE	199
windows-oldrel	NOTE	177
wasm-release	OK	145

Exports:assign_colorsAnnotation Compare_Triplets Compare_VertexClasses_sharedEdgeFeatures CoNI create_edgeFBarplot create_GlobalBarplot create_stackedGlobalBarplot_perTreatment createBipartiteGraph find_localControllingFeatures generate_network getstackedGlobalBarplot_and_Grid getVertexsPerEdgeFeature getVertexsPerEdgeFeature_and_Grid NetStats plotPcorvsCor tableLCFs_VFs top_n_LF_byMagnitude

Dependencies:annotate AnnotationDbi askpass backports base64enc Biobase BiocGenerics Biostrings bit bit64 bitops blob bslib cachem caTools checkmate cli cluster cocor codetools colorspace cpp11 crayon curl data.table DBI digest doParallel dplyr evaluate farver fastmap fontawesome forcats foreach foreign Formula fs genefilter generics ggplot2 ggrepel glue gplots gridExtra gtable gtools highr Hmisc htmlTable htmltools htmlwidgets httr igraph IRanges isoband iterators jquerylib jsonlite KEGGREST KernSmooth knitr labeling lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats memoise mime nnet openssl pillar pkgconfig plyr png ppcor purrr R6 rappdirs RColorBrewer Rcpp rlang rmarkdown rpart RSQLite rstudioapi S4Vectors S7 sass scales Seqinfo stringi stringr survival sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun XML xtable XVector yaml

CoNI

José Manuel Monroy Kuhn

Rendered fromFull_RunCoNI.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2022-03-29
Started: 2021-07-23

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Assing Colors to Class	assign_colorsAnnotation
Chow gene expression data	Chow_GeneExpData
Chow metabolite data	Chow_MetaboliteData
Compare triplets	Compare_Triplets
Table VertexClass pairs of shared Edge Features	Compare_VertexClasses_sharedEdgeFeatures
Correlation guided Network Integration	CoNI
CoNI Results Chow	CoNIResults_Chow
CoNI Results HFD	CoNIResults_HFD
Toy data HFD results	CoNIResultsHFDToy
Vertex-class pairs profile of one shared edge feature	create_edgeFBarplot
Vertex-class pairs profile of shared features	create_GlobalBarplot
Stacked Global Barplot (One treatment)	create_stackedGlobalBarplot_perTreatment
Bipartite Network	createBipartiteGraph
Find local controlling features	find_localControllingFeatures
Toy data gene expression	GeneExpToy
Create network	generate_network
Stacked Global Barplot Side-by-side (two treatments)	getstackedGlobalBarplot_and_Grid
Vertex Class profile per edge feature (one treatment)	getVertexsPerEdgeFeature
Vertex-Class profile per edge feature Side-by-Side (two treatments)	getVertexsPerEdgeFeature_and_Grid
HFD gene expression data	HFD_GeneExpData
HFD metabolite data	HFD_MetaboliteData
Toy data metabolite expression	MetaboExpToy
Metabolite Annotation	MetaboliteAnnotation
Toy data annotation	MetColorTable
Network Statistics	NetStats
Correlation vs Partial correlation	plotPcorvsCor
Table local controlling edge features and vertex pairs	tableLCFs_VFs
Linker Features by magnitude of effect	top_n_LF_byMagnitude
Toy data comparison treatments	VertexClassesSharedGenes_HFDvsChow