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 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.13-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.13-bioc/R/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        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       
## 
## attached base packages:
## [1] stats4    parallel  stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] minfi_1.38.0                bumphunter_1.34.0          
##  [3] locfit_1.5-9.4              iterators_1.0.13           
##  [5] foreach_1.5.1               Biostrings_2.60.0          
##  [7] XVector_0.32.0              SummarizedExperiment_1.22.0
##  [9] MatrixGenerics_1.4.0        matrixStats_0.58.0         
## [11] GenomicRanges_1.44.0        GenomeInfoDb_1.28.0        
## [13] IRanges_2.26.0              S4Vectors_0.30.0           
## [15] rexposome_1.14.0            Biobase_2.52.0             
## [17] BiocGenerics_0.38.0         BiocStyle_2.20.0           
## 
## loaded via a namespace (and not attached):
##   [1] utf8_1.2.1                gmm_1.6-6                
##   [3] tidyselect_1.1.1          lme4_1.1-27              
##   [5] RSQLite_2.2.7             AnnotationDbi_1.54.0     
##   [7] htmlwidgets_1.5.3         FactoMineR_2.4           
##   [9] grid_4.1.0                BiocParallel_1.26.0      
##  [11] norm_1.0-9.5              munsell_0.5.0            
##  [13] codetools_0.2-18          preprocessCore_1.54.0    
##  [15] DT_0.18                   colorspace_2.0-1         
##  [17] filelock_1.0.2            knitr_1.33               
##  [19] rstudioapi_0.13           leaps_3.1                
##  [21] GenomeInfoDbData_1.2.6    bit64_4.0.5              
##  [23] rhdf5_2.36.0              vctrs_0.3.8              
##  [25] generics_0.1.0            xfun_0.23                
##  [27] BiocFileCache_2.0.0       R6_2.5.0                 
##  [29] illuminaio_0.34.0         bitops_1.0-7             
##  [31] rhdf5filters_1.4.0        cachem_1.0.5             
##  [33] reshape_0.8.8             DelayedArray_0.18.0      
##  [35] assertthat_0.2.1          BiocIO_1.2.0             
##  [37] scales_1.1.1              nnet_7.3-16              
##  [39] gtable_0.3.0              lsr_0.5                  
##  [41] sandwich_3.0-1            rlang_0.4.11             
##  [43] genefilter_1.74.0         scatterplot3d_0.3-41     
##  [45] GlobalOptions_0.1.2       splines_4.1.0            
##  [47] rtracklayer_1.52.0        GEOquery_2.60.0          
##  [49] impute_1.66.0             checkmate_2.0.0          
##  [51] BiocManager_1.30.15       yaml_2.2.1               
##  [53] reshape2_1.4.4            GenomicFeatures_1.44.0   
##  [55] backports_1.2.1           Hmisc_4.5-0              
##  [57] tools_4.1.0               bookdown_0.22            
##  [59] nor1mix_1.3-0             ggplot2_3.3.3            
##  [61] ellipsis_0.3.2            gplots_3.1.1             
##  [63] jquerylib_0.1.4           RColorBrewer_1.1-2       
##  [65] siggenes_1.66.0           Rcpp_1.0.6               
##  [67] plyr_1.8.6                base64enc_0.1-3          
##  [69] sparseMatrixStats_1.4.0   progress_1.2.2           
##  [71] zlibbioc_1.38.0           purrr_0.3.4              
##  [73] RCurl_1.98-1.3            prettyunits_1.1.1        
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##  [79] cluster_2.1.2             magrittr_2.0.1           
##  [81] data.table_1.14.0         circlize_0.4.12          
##  [83] pcaMethods_1.84.0         mvtnorm_1.1-1            
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##  [87] evaluate_0.14             XML_3.99-0.6             
##  [89] jpeg_0.1-8.1              mclust_5.4.7             
##  [91] gridExtra_2.3             shape_1.4.6              
##  [93] compiler_4.1.0            biomaRt_2.48.0           
##  [95] tibble_3.1.2              KernSmooth_2.23-20       
##  [97] crayon_1.4.1              minqa_1.2.4              
##  [99] htmltools_0.5.1.1         Formula_1.2-4            
## [101] tidyr_1.1.3               DBI_1.1.1                
## [103] corrplot_0.88             dbplyr_2.1.1             
## [105] MASS_7.3-54               tmvtnorm_1.4-10          
## [107] rappdirs_0.3.3            boot_1.3-28              
## [109] readr_1.4.0               Matrix_1.3-3             
## [111] imputeLCMD_2.0            pryr_0.1.4               
## [113] quadprog_1.5-8            pkgconfig_2.0.3          
## [115] flashClust_1.01-2         GenomicAlignments_1.28.0 
## [117] foreign_0.8-81            xml2_1.3.2               
## [119] annotate_1.70.0           bslib_0.2.5.1            
## [121] rngtools_1.5              multtest_2.48.0          
## [123] beanplot_1.2              doRNG_1.8.2              
## [125] scrime_1.3.5              stringr_1.4.0            
## [127] digest_0.6.27             base64_2.0               
## [129] rmarkdown_2.8             htmlTable_2.2.1          
## [131] DelayedMatrixStats_1.14.0 restfulr_0.0.13          
## [133] curl_4.3.1                Rsamtools_2.8.0          
## [135] gtools_3.8.2              rjson_0.2.20             
## [137] nloptr_1.2.2.2            lifecycle_1.0.0          
## [139] nlme_3.1-152              jsonlite_1.7.2           
## [141] Rhdf5lib_1.14.0           askpass_1.1              
## [143] limma_3.48.0              fansi_0.4.2              
## [145] pillar_1.6.1              lattice_0.20-44          
## [147] KEGGREST_1.32.0           fastmap_1.1.0            
## [149] httr_1.4.2                survival_3.2-11          
## [151] glue_1.4.2                png_0.1-7                
## [153] glmnet_4.1-1              bit_4.0.4                
## [155] stringi_1.6.2             sass_0.4.0               
## [157] HDF5Array_1.20.0          blob_1.2.1               
## [159] latticeExtra_0.6-29       caTools_1.18.2           
## [161] memoise_2.0.0             dplyr_1.0.6