Introduction

The iModMixData package provides example datasets for the iModMix package.
These datasets are preprocessed and ready to use for testing and demonstrating the iModMix workflows.

The datasets include:

PartialCorGenes: partial correlation values between genes (ccRCC4 study)
PartialCorMetabolites: partial correlation values between metabolites (FloresData_K_TK study)
PartialCorProt: partial correlation values between proteins (FloresData_K_TK study)

These datasets allow users to explore correlation networks and test reproducible analysis pipelines.

Loading the Package

First, load the iModMixData package:

library(iModMixData)

Accessing the Data

The package provides functions to access datasets stored in ExperimentHub.

Load PartialCorGenes

genes <- loadPartialCorGenes()

## Registered S3 method overwritten by 'bit64':
##   method          from 
##   print.bitstring tools

## see ?iModMixData and browseVignettes('iModMixData') for documentation

## downloading 1 resources

## retrieving 1 resource

## loading from cache

# Preview first rows
genes[1:5, 1:5]

##      A1BG NAT2 ADA        CDH2        AKT3
## A1BG   NA    0   0  0.00000000  0.00000000
## NAT2    0   NA   0  0.00000000  0.00000000
## ADA     0    0  NA  0.00000000  0.00000000
## CDH2    0    0   0          NA -0.01663876
## AKT3    0    0   0 -0.01663876          NA

# Check dimensions
dim(genes)

## [1] 17240 17240

The PartialCorGenes dataset contains genes as rows and samples as columns. Each entry represents a partial correlation value of a gene with other genes, adjusted for covariates. Data were preprocessed using load_data() (filtering low-variance features, KNN imputation, scaling) and partial correlations were calculated using partial_cors().

This dataset can be used to explore gene correlation networks and for demonstrating iModMix workflows.

Load PartialCorMetabolites

metabolites <- loadPartialCorMetabolites()

## see ?iModMixData and browseVignettes('iModMixData') for documentation

## downloading 1 resources

## retrieving 1 resource

## loading from cache

metabolites[1:5, 1:5]

##           neg_00001 neg_00002 neg_00003 neg_00004 neg_00005
## neg_00001        NA         0         0         0         0
## neg_00002         0        NA         0         0         0
## neg_00003         0         0        NA         0         0
## neg_00004         0         0         0        NA         0
## neg_00005         0         0         0         0        NA

dim(metabolites)

## [1] 6733 6733

The PartialCorMetabolites dataset contains metabolites as rows and samples as columns. Partial correlations can be used to study metabolic networks or integrate with other omics datasets.

Load PartialCorProt

proteins <- loadPartialCorProt()

## see ?iModMixData and browseVignettes('iModMixData') for documentation

## downloading 1 resources

## retrieving 1 resource

## loading from cache

proteins[1:5, 1:5]

##      395 396        6678        6906        5643
## 395   NA   0  0.00000000  0.00000000  0.00000000
## 396    0  NA  0.00000000  0.00000000  0.00000000
## 6678   0   0          NA -0.04620583  0.00000000
## 6906   0   0 -0.04620583          NA -0.09714395
## 5643   0   0  0.00000000 -0.09714395          NA

dim(proteins)

## [1] 7205 7205

The PartialCorProt dataset contains proteins as rows and samples as columns. Users can explore protein correlations or use it in multi-omics analyses.

Suggested Uses

Testing and demonstrating iModMix pipelines
Exploratory analysis of gene, metabolite, and protein correlations
Reproducible examples in publications or teaching

Session Information

## R version 4.6.0 RC (2026-04-17 r89917)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.4 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.24-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: America/New_York
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] iModMixData_1.1.0
## 
## loaded via a namespace (and not attached):
##  [1] rappdirs_0.3.4       sass_0.4.10          generics_0.1.4      
##  [4] BiocVersion_3.23.1   RSQLite_2.4.6        digest_0.6.39       
##  [7] magrittr_2.0.5       evaluate_1.0.5       fastmap_1.2.0       
## [10] blob_1.3.0           AnnotationHub_4.1.0  jsonlite_2.0.0      
## [13] AnnotationDbi_1.73.1 DBI_1.3.0            BiocManager_1.30.27 
## [16] httr_1.4.8           purrr_1.2.2          Biostrings_2.79.5   
## [19] httr2_1.2.2          jquerylib_0.1.4      cli_3.6.6           
## [22] crayon_1.5.3         rlang_1.2.0          XVector_0.51.0      
## [25] dbplyr_2.5.2         Biobase_2.71.0       bit64_4.6.0-1       
## [28] withr_3.0.2          cachem_1.1.0         yaml_2.3.12         
## [31] otel_0.2.0           tools_4.6.0          memoise_2.0.1       
## [34] dplyr_1.2.1          filelock_1.0.3       ExperimentHub_3.1.0 
## [37] BiocGenerics_0.57.1  curl_7.0.0           vctrs_0.7.3         
## [40] R6_2.6.1             png_0.1-9            stats4_4.6.0        
## [43] BiocFileCache_3.1.0  lifecycle_1.0.5      Seqinfo_1.1.0       
## [46] KEGGREST_1.51.1      S4Vectors_0.49.2     IRanges_2.45.0      
## [49] bit_4.6.0            pkgconfig_2.0.3      pillar_1.11.1       
## [52] bslib_0.10.0         glue_1.8.1           xfun_0.57           
## [55] tibble_3.3.1         tidyselect_1.2.1     knitr_1.51          
## [58] htmltools_0.5.9      rmarkdown_2.31       compiler_4.6.0

Using iModMixData

Isis Narvaez-Bandera

2026-04-21