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 4.4.0 beta (2024-04-15 r86425)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.19-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
## 
## 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_1.50.0                bumphunter_1.46.0          
##  [3] locfit_1.5-9.9              iterators_1.0.14           
##  [5] foreach_1.5.2               Biostrings_2.72.0          
##  [7] XVector_0.44.0              SummarizedExperiment_1.34.0
##  [9] MatrixGenerics_1.16.0       matrixStats_1.3.0          
## [11] GenomicRanges_1.56.0        GenomeInfoDb_1.40.0        
## [13] IRanges_2.38.0              S4Vectors_0.42.0           
## [15] rexposome_1.26.0            Biobase_2.64.0             
## [17] BiocGenerics_0.50.0         BiocStyle_2.32.0           
## 
## loaded via a namespace (and not attached):
##   [1] splines_4.4.0             norm_1.0-11.1            
##   [3] BiocIO_1.14.0             bitops_1.0-7             
##   [5] tibble_3.2.1              preprocessCore_1.66.0    
##   [7] XML_3.99-0.16.1           rpart_4.1.23             
##   [9] lifecycle_1.0.4           base64_2.0.1             
##  [11] lattice_0.22-6            MASS_7.3-60.2            
##  [13] scrime_1.3.5              flashClust_1.01-2        
##  [15] backports_1.4.1           magrittr_2.0.3           
##  [17] limma_3.60.0              Hmisc_5.1-2              
##  [19] sass_0.4.9                rmarkdown_2.26           
##  [21] jquerylib_0.1.4           yaml_2.3.8               
##  [23] askpass_1.2.0             doRNG_1.8.6              
##  [25] RColorBrewer_1.1-3        DBI_1.2.2                
##  [27] minqa_1.2.6               multcomp_1.4-25          
##  [29] abind_1.4-5               zlibbioc_1.50.0          
##  [31] quadprog_1.5-8            purrr_1.0.2              
##  [33] RCurl_1.98-1.14           nnet_7.3-19              
##  [35] TH.data_1.1-2             sandwich_3.1-0           
##  [37] circlize_0.4.16           GenomeInfoDbData_1.2.12  
##  [39] ggrepel_0.9.5             genefilter_1.86.0        
##  [41] annotate_1.82.0           DelayedMatrixStats_1.26.0
##  [43] codetools_0.2-20          DelayedArray_0.30.0      
##  [45] xml2_1.3.6                DT_0.33                  
##  [47] tidyselect_1.2.1          gmm_1.8                  
##  [49] shape_1.4.6.1             UCSC.utils_1.0.0         
##  [51] beanplot_1.3.1            lme4_1.1-35.3            
##  [53] base64enc_0.1-3           illuminaio_0.46.0        
##  [55] GenomicAlignments_1.40.0  jsonlite_1.8.8           
##  [57] multtest_2.60.0           Formula_1.2-5            
##  [59] survival_3.6-4            emmeans_1.10.1           
##  [61] tools_4.4.0               pryr_0.1.6               
##  [63] Rcpp_1.0.12               glue_1.7.0               
##  [65] gridExtra_2.3             SparseArray_1.4.0        
##  [67] xfun_0.43                 dplyr_1.1.4              
##  [69] HDF5Array_1.32.0          BiocManager_1.30.22      
##  [71] fastmap_1.1.1             boot_1.3-30              
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##  [79] estimability_1.5          imputeLCMD_2.1           
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##  [83] RSQLite_2.3.6             tidyr_1.3.1              
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##  [87] data.table_1.15.4         rtracklayer_1.64.0       
##  [89] httr_1.4.7                htmlwidgets_1.6.4        
##  [91] S4Arrays_1.4.0            scatterplot3d_0.3-44     
##  [93] pkgconfig_2.0.3           gtable_0.3.5             
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##  [97] impute_1.78.0             htmltools_0.5.8.1        
##  [99] bookdown_0.39             multcompView_0.1-10      
## [101] scales_1.3.0              tmvtnorm_1.6             
## [103] leaps_3.1                 png_0.1-8                
## [105] corrplot_0.92             knitr_1.46               
## [107] rstudioapi_0.16.0         tzdb_0.4.0               
## [109] reshape2_1.4.4            rjson_0.2.21             
## [111] coda_0.19-4.1             checkmate_2.3.1          
## [113] nlme_3.1-164              curl_5.2.1               
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## [117] zoo_1.8-12                rhdf5_2.48.0             
## [119] GlobalOptions_0.1.2       stringr_1.5.1            
## [121] KernSmooth_2.23-22        foreign_0.8-86           
## [123] AnnotationDbi_1.66.0      restfulr_0.0.15          
## [125] GEOquery_2.72.0           reshape_0.8.9            
## [127] pillar_1.9.0              grid_4.4.0               
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## [131] pcaMethods_1.96.0         xtable_1.8-4             
## [133] cluster_2.1.6             htmlTable_2.4.2          
## [135] evaluate_0.23             readr_2.1.5              
## [137] GenomicFeatures_1.56.0    mvtnorm_1.2-4            
## [139] cli_3.6.2                 compiler_4.4.0           
## [141] Rsamtools_2.20.0          rlang_1.1.3              
## [143] crayon_1.5.2              rngtools_1.5.2           
## [145] nor1mix_1.3-3             mclust_6.1.1             
## [147] plyr_1.8.9                stringi_1.8.3            
## [149] lsr_0.5.2                 BiocParallel_1.38.0      
## [151] munsell_0.5.1             glmnet_4.1-8             
## [153] Matrix_1.7-0              hms_1.1.3                
## [155] sparseMatrixStats_1.16.0  bit64_4.0.5              
## [157] ggplot2_3.5.1             Rhdf5lib_1.26.0          
## [159] statmod_1.5.0             KEGGREST_1.44.0          
## [161] FactoMineR_2.11           memoise_2.0.1            
## [163] bslib_0.7.0               bit_4.0.5