Contents

1 Getting started

brgedata includes a collection of BRGE omic and exposome data from the same cohort. The diferent objects guarantees a minimum of samples in common between all sets.

Data available in this R package:

Data Type Number of Samples Number of Features Technology Object Name Class
Exposome 110 15 brge_expo ExposomeSet
Transcriptome 75 67528 Affymetrix HTA 2.0 brge_gexp ExpressionSet
Methylome 20 392277 Illumina Human Methylation 450K brge_methy GenomicRatioSet
Proteome 90 47 brge_prot ExpressionSet

sex and age was included as phenotipic data in each set. Moreover, the ExposomeSet includes asthma status and rhinitis status of each sample.

2 Data Resources

2.1 Exposome Data

To load the exposome data, stored in an ExposomeSet, run the follow commands:

data("brge_expo", package = "brgedata")
brge_expo
## Object of class 'ExposomeSet' (storageMode: environment)
##  . exposures description:
##     . categorical:  0 
##     . continuous:  15 
##  . exposures transformation:
##     . categorical: 0 
##     . transformed: 0 
##     . standardized: 0 
##     . imputed: 0 
##  . assayData: 15 exposures 110 individuals
##     . element names: exp, raw 
##     . exposures: Ben_p, ..., PCB153 
##     . individuals: x0001, ..., x0119 
##  . phenoData: 110 individuals 6 phenotypes
##     . individuals: x0001, ..., x0119 
##     . phenotypes: Asthma, ..., Age 
##  . featureData: 15 exposures 12 explanations
##     . exposures: Ben_p, ..., PCB153 
##     . descriptions: Family, ..., .imp 
## experimentData: use 'experimentData(object)'
## Annotation:

The summary of the data contained by brge_expo:

Data Type Number of Samples Number of Features Technology Object Name Class
Exposome 110 15 brge_expo ExposomeSet

2.2 Transcriptome Data

To load the transcriptome data, saved in an ExpressionSet, run the follow commands:

data("brge_gexp", package = "brgedata")
brge_gexp
## ExpressionSet (storageMode: lockedEnvironment)
## assayData: 67528 features, 100 samples 
##   element names: exprs 
## protocolData: none
## phenoData
##   sampleNames: x0001 x0002 ... x0139 (100 total)
##   varLabels: age sex
##   varMetadata: labelDescription
## featureData
##   featureNames: TC01000001.hg.1 TC01000002.hg.1 ...
##     TCUn_gl000247000001.hg.1 (67528 total)
##   fvarLabels: transcript_cluster_id probeset_id ... notes (11 total)
##   fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'
## Annotation:

The summary of the data contained by brge_gexp:

Data Type Number of Samples Number of Features Technology Object Name Class
Transcriptome 75 67528 Affymetrix HTA 2.0 brge_gexp ExpressionSet

2.3 Methylome Data

To load the methylation data, encapsulated in a GenomicRatioSet, run the follow commands:

data("brge_methy", package = "brgedata")
brge_methy
## class: GenomicRatioSet 
## dim: 392277 20 
## metadata(0):
## assays(1): Beta
## rownames(392277): cg13869341 cg24669183 ... cg26251715 cg25640065
## rowData names(14): Forward_Sequence SourceSeq ...
##   Regulatory_Feature_Group DHS
## colnames(20): x0017 x0043 ... x0077 x0079
## colData names(9): age sex ... Mono Neu
## Annotation
##   array: IlluminaHumanMethylation450k
##   annotation: ilmn12.hg19
## Preprocessing
##   Method: NA
##   minfi version: NA
##   Manifest version: NA

The summary of the data contained by brge_methy:

Data Type Number of Samples Number of Features Technology Object Name Class
Methylome 20 392277 Illumina Human Methylation 450K brge_methy GenomicRatioSet

2.4 Proteome Data

To load the protein data, stored in an ExpressionSet, run the follow commands:

data("brge_prot", package = "brgedata")
brge_prot
## ExpressionSet (storageMode: lockedEnvironment)
## assayData: 47 features, 90 samples 
##   element names: exprs 
## protocolData: none
## phenoData
##   sampleNames: x0001 x0002 ... x0090 (90 total)
##   varLabels: age sex
##   varMetadata: labelDescription
## featureData
##   featureNames: Adiponectin_ok Alpha1AntitrypsinAAT_ok ...
##     VitaminDBindingProte_ok (47 total)
##   fvarLabels: chr start end
##   fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'
## Annotation:

The summary of the data contained by brge_prot:

Data Type Number of Samples Number of Features Technology Object Name Class
Proteome 90 47 brge_prot ExpressionSet

Session info

## R version 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.20-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.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] parallel  stats4    stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] minfi_1.52.0                bumphunter_1.48.0          
##  [3] locfit_1.5-9.10             iterators_1.0.14           
##  [5] foreach_1.5.2               Biostrings_2.74.0          
##  [7] XVector_0.46.0              SummarizedExperiment_1.36.0
##  [9] MatrixGenerics_1.18.0       matrixStats_1.4.1          
## [11] GenomicRanges_1.58.0        GenomeInfoDb_1.42.0        
## [13] IRanges_2.40.0              S4Vectors_0.44.0           
## [15] rexposome_1.28.0            Biobase_2.66.0             
## [17] BiocGenerics_0.52.0         BiocStyle_2.34.0           
## 
## loaded via a namespace (and not attached):
##   [1] splines_4.4.1             norm_1.0-11.1            
##   [3] BiocIO_1.16.0             bitops_1.0-9             
##   [5] tibble_3.2.1              preprocessCore_1.68.0    
##   [7] XML_3.99-0.17             rpart_4.1.23             
##   [9] lifecycle_1.0.4           base64_2.0.2             
##  [11] lattice_0.22-6            MASS_7.3-61              
##  [13] scrime_1.3.5              flashClust_1.01-2        
##  [15] backports_1.5.0           magrittr_2.0.3           
##  [17] limma_3.62.0              Hmisc_5.2-0              
##  [19] sass_0.4.9                rmarkdown_2.28           
##  [21] jquerylib_0.1.4           yaml_2.3.10              
##  [23] askpass_1.2.1             doRNG_1.8.6              
##  [25] RColorBrewer_1.1-3        DBI_1.2.3                
##  [27] minqa_1.2.8               multcomp_1.4-26          
##  [29] abind_1.4-8               zlibbioc_1.52.0          
##  [31] quadprog_1.5-8            purrr_1.0.2              
##  [33] RCurl_1.98-1.16           nnet_7.3-19              
##  [35] TH.data_1.1-2             sandwich_3.1-1           
##  [37] circlize_0.4.16           GenomeInfoDbData_1.2.13  
##  [39] ggrepel_0.9.6             rentrez_1.2.3            
##  [41] genefilter_1.88.0         annotate_1.84.0          
##  [43] DelayedMatrixStats_1.28.0 codetools_0.2-20         
##  [45] DelayedArray_0.32.0       xml2_1.3.6               
##  [47] DT_0.33                   tidyselect_1.2.1         
##  [49] gmm_1.8                   shape_1.4.6.1            
##  [51] UCSC.utils_1.2.0          beanplot_1.3.1           
##  [53] lme4_1.1-35.5             base64enc_0.1-3          
##  [55] illuminaio_0.48.0         GenomicAlignments_1.42.0 
##  [57] jsonlite_1.8.9            multtest_2.62.0          
##  [59] Formula_1.2-5             survival_3.7-0           
##  [61] emmeans_1.10.5            tools_4.4.1              
##  [63] pryr_0.1.6                Rcpp_1.0.13              
##  [65] glue_1.8.0                gridExtra_2.3            
##  [67] SparseArray_1.6.0         xfun_0.48                
##  [69] dplyr_1.1.4               HDF5Array_1.34.0         
##  [71] BiocManager_1.30.25       fastmap_1.2.0            
##  [73] boot_1.3-31               rhdf5filters_1.18.0      
##  [75] fansi_1.0.6               openssl_2.2.2            
##  [77] caTools_1.18.3            digest_0.6.37            
##  [79] R6_2.5.1                  estimability_1.5.1       
##  [81] imputeLCMD_2.1            colorspace_2.1-1         
##  [83] gtools_3.9.5              RSQLite_2.3.7            
##  [85] tidyr_1.3.1               utf8_1.2.4               
##  [87] generics_0.1.3            data.table_1.16.2        
##  [89] rtracklayer_1.66.0        httr_1.4.7               
##  [91] htmlwidgets_1.6.4         S4Arrays_1.6.0           
##  [93] scatterplot3d_0.3-44      pkgconfig_2.0.3          
##  [95] gtable_0.3.6              blob_1.2.4               
##  [97] siggenes_1.80.0           impute_1.80.0            
##  [99] htmltools_0.5.8.1         bookdown_0.41            
## [101] multcompView_0.1-10       scales_1.3.0             
## [103] tmvtnorm_1.6              leaps_3.2                
## [105] png_0.1-8                 corrplot_0.95            
## [107] knitr_1.48                rstudioapi_0.17.1        
## [109] tzdb_0.4.0                reshape2_1.4.4           
## [111] rjson_0.2.23              coda_0.19-4.1            
## [113] checkmate_2.3.2           nlme_3.1-166             
## [115] curl_5.2.3                nloptr_2.1.1             
## [117] cachem_1.1.0              zoo_1.8-12               
## [119] rhdf5_2.50.0              GlobalOptions_0.1.2      
## [121] stringr_1.5.1             KernSmooth_2.23-24       
## [123] foreign_0.8-87            AnnotationDbi_1.68.0     
## [125] restfulr_0.0.15           GEOquery_2.74.0          
## [127] reshape_0.8.9             pillar_1.9.0             
## [129] grid_4.4.1                vctrs_0.6.5              
## [131] gplots_3.2.0              pcaMethods_1.98.0        
## [133] xtable_1.8-4              cluster_2.1.6            
## [135] htmlTable_2.4.3           evaluate_1.0.1           
## [137] readr_2.1.5               GenomicFeatures_1.58.0   
## [139] mvtnorm_1.3-1             cli_3.6.3                
## [141] compiler_4.4.1            Rsamtools_2.22.0         
## [143] rlang_1.1.4               crayon_1.5.3             
## [145] rngtools_1.5.2            nor1mix_1.3-3            
## [147] mclust_6.1.1              plyr_1.8.9               
## [149] stringi_1.8.4             lsr_0.5.2                
## [151] BiocParallel_1.40.0       munsell_0.5.1            
## [153] glmnet_4.1-8              Matrix_1.7-1             
## [155] hms_1.1.3                 sparseMatrixStats_1.18.0 
## [157] bit64_4.5.2               ggplot2_3.5.1            
## [159] Rhdf5lib_1.28.0           statmod_1.5.0            
## [161] KEGGREST_1.46.0           FactoMineR_2.11          
## [163] memoise_2.0.1             bslib_0.8.0              
## [165] bit_4.5.0