| Title: | Data for iModMix Package |
|---|---|
| Description: | Provides example datasets for the iModMix package, including gene, protein, and metabolite partial correlation matrices derived from ccRCC4 and FloresData_K_TK studies. The data are preprocessed and ready to use for testing, demonstrating iModMix workflows, and exploring correlation networks. |
| Authors: | Isis Narvaez-Bandera [aut, cre] (ORCID: <https://orcid.org/0000-0001-7320-618X>) |
| Maintainer: | Isis Narvaez-Bandera <[email protected]> |
| License: | GPL-3 |
| Version: | 1.2.0 |
| Built: | 2026-10-10 11:21:03 UTC |
| Source: | https://github.com/bioc/iModMixData |
Loads the PartialCorGenes dataset from ExperimentHub.
loadPartialCorGenes()loadPartialCorGenes()
The dataset contains partial correlation values between genes derived from
the ccRCC4 study.
The original expression data were preprocessed using load_data()
which includes:
Filtering features with >10% missing values
Removing features with low variance
Scaling and KNN imputation of missing values
Partial correlations were then calculated using partial_cors(): rho = 0.25.
Rows correspond to genes, columns correspond to samples. Each entry represents the partial correlation of the gene with other genes, adjusted for covariates.
A data.frame with genes as rows and samples as columns.
ccRCC4 study. Original data processed for iModMix.
genes <- loadPartialCorGenes() head(genes) dim(genes)genes <- loadPartialCorGenes() head(genes) dim(genes)
Loads the PartialCorMetabolites dataset from ExperimentHub.
loadPartialCorMetabolites()loadPartialCorMetabolites()
The dataset contains partial correlation values between metabolites derived from the FloresData_K_TK study. Data were preprocessed similarly to genes:
Filtering features with >10% missing values
Removing features with low variance
Scaling and KNN imputation of missing values
Partial correlations were calculated using partial_cors() with rho = 0.25.
Rows correspond to metabolites, columns correspond to samples. Each entry represents the partial correlation of the metabolite with other metabolites, adjusted for covariates.
A data.frame with metabolites as rows and samples as columns.
FloresData_K_TK study. Original data processed for iModMix.
metabolites <- loadPartialCorMetabolites() head(metabolites) dim(metabolites)metabolites <- loadPartialCorMetabolites() head(metabolites) dim(metabolites)
Loads the PartialCorProt dataset from ExperimentHub.
loadPartialCorProt()loadPartialCorProt()
The dataset contains partial correlation values between proteins derived from the FloresData_K_TK study. Data were preprocessed similarly to genes and metabolites:
Filtering features with >10% missing values
Removing features with low variance
Scaling and KNN imputation of missing values
Partial correlations were calculated using partial_cors() with rho = 0.25.
Rows correspond to proteins, columns correspond to samples. Each entry represents the partial correlation of the protein with other proteins, adjusted for covariates.
A data.frame with proteins as rows and samples as columns.
FloresData_K_TK study. Original data processed for iModMix.
proteins <- loadPartialCorProt() head(proteins) dim(proteins)proteins <- loadPartialCorProt() head(proteins) dim(proteins)