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 4.0.0 (2020-04-24)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.4 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.11-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.11-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_1.34.0                bumphunter_1.30.0          
##  [3] locfit_1.5-9.4              iterators_1.0.12           
##  [5] foreach_1.5.0               Biostrings_2.56.0          
##  [7] XVector_0.28.0              SummarizedExperiment_1.18.1
##  [9] DelayedArray_0.14.0         matrixStats_0.56.0         
## [11] GenomicRanges_1.40.0        GenomeInfoDb_1.24.0        
## [13] IRanges_2.22.1              S4Vectors_0.26.0           
## [15] rexposome_1.10.0            Biobase_2.48.0             
## [17] BiocGenerics_0.34.0         BiocStyle_2.16.0           
## 
## loaded via a namespace (and not attached):
##   [1] gmm_1.6-4                 tidyselect_1.0.0         
##   [3] lme4_1.1-23               RSQLite_2.2.0            
##   [5] AnnotationDbi_1.50.0      htmlwidgets_1.5.1        
##   [7] FactoMineR_2.3            grid_4.0.0               
##   [9] BiocParallel_1.22.0       norm_1.0-9.5             
##  [11] munsell_0.5.0             codetools_0.2-16         
##  [13] preprocessCore_1.50.0     statmod_1.4.34           
##  [15] colorspace_1.4-1          knitr_1.28               
##  [17] rstudioapi_0.11           leaps_3.1                
##  [19] GenomeInfoDbData_1.2.3    bit64_0.9-7              
##  [21] rhdf5_2.32.0              vctrs_0.2.4              
##  [23] xfun_0.13                 BiocFileCache_1.12.0     
##  [25] R6_2.4.1                  illuminaio_0.30.0        
##  [27] bitops_1.0-6              reshape_0.8.8            
##  [29] assertthat_0.2.1          scales_1.1.0             
##  [31] nnet_7.3-14               gtable_0.3.0             
##  [33] lsr_0.5                   sandwich_2.5-1           
##  [35] rlang_0.4.6               genefilter_1.70.0        
##  [37] scatterplot3d_0.3-41      GlobalOptions_0.1.1      
##  [39] splines_4.0.0             rtracklayer_1.48.0       
##  [41] acepack_1.4.1             impute_1.62.0            
##  [43] GEOquery_2.56.0           checkmate_2.0.0          
##  [45] BiocManager_1.30.10       yaml_2.2.1               
##  [47] reshape2_1.4.4            GenomicFeatures_1.40.0   
##  [49] backports_1.1.6           Hmisc_4.4-0              
##  [51] tools_4.0.0               bookdown_0.18            
##  [53] nor1mix_1.3-0             ggplot2_3.3.0            
##  [55] ellipsis_0.3.0            gplots_3.0.3             
##  [57] RColorBrewer_1.1-2        siggenes_1.62.0          
##  [59] Rcpp_1.0.4.6              plyr_1.8.6               
##  [61] base64enc_0.1-3           progress_1.2.2           
##  [63] zlibbioc_1.34.0           purrr_0.3.4              
##  [65] RCurl_1.98-1.2            prettyunits_1.1.1        
##  [67] rpart_4.1-15              openssl_1.4.1            
##  [69] zoo_1.8-8                 ggrepel_0.8.2            
##  [71] cluster_2.1.0             magrittr_1.5             
##  [73] data.table_1.12.8         circlize_0.4.9           
##  [75] pcaMethods_1.80.0         mvtnorm_1.1-0            
##  [77] hms_0.5.3                 evaluate_0.14            
##  [79] xtable_1.8-4              XML_3.99-0.3             
##  [81] jpeg_0.1-8.1              mclust_5.4.6             
##  [83] gridExtra_2.3             shape_1.4.4              
##  [85] compiler_4.0.0            biomaRt_2.44.0           
##  [87] tibble_3.0.1              KernSmooth_2.23-17       
##  [89] crayon_1.3.4              minqa_1.2.4              
##  [91] htmltools_0.4.0           Formula_1.2-3            
##  [93] tidyr_1.0.2               DBI_1.1.0                
##  [95] corrplot_0.84             dbplyr_1.4.3             
##  [97] MASS_7.3-51.6             tmvtnorm_1.4-10          
##  [99] rappdirs_0.3.1            boot_1.3-25              
## [101] Matrix_1.2-18             readr_1.3.1              
## [103] imputeLCMD_2.0            pryr_0.1.4               
## [105] quadprog_1.5-8            gdata_2.18.0             
## [107] pkgconfig_2.0.3           flashClust_1.01-2        
## [109] GenomicAlignments_1.24.0  foreign_0.8-79           
## [111] xml2_1.3.2                annotate_1.66.0          
## [113] rngtools_1.5              multtest_2.44.0          
## [115] beanplot_1.2              doRNG_1.8.2              
## [117] scrime_1.3.5              stringr_1.4.0            
## [119] digest_0.6.25             rmarkdown_2.1            
## [121] base64_2.0                htmlTable_1.13.3         
## [123] DelayedMatrixStats_1.10.0 curl_4.3                 
## [125] Rsamtools_2.4.0           gtools_3.8.2             
## [127] nloptr_1.2.2.1            lifecycle_0.2.0          
## [129] nlme_3.1-147              Rhdf5lib_1.10.0          
## [131] askpass_1.1               limma_3.44.1             
## [133] pillar_1.4.4              lattice_0.20-41          
## [135] httr_1.4.1                survival_3.1-12          
## [137] glue_1.4.0                png_0.1-7                
## [139] glmnet_3.0-2              bit_1.1-15.2             
## [141] stringi_1.4.6             HDF5Array_1.16.0         
## [143] blob_1.2.1                latticeExtra_0.6-29      
## [145] caTools_1.18.0            memoise_1.1.0            
## [147] dplyr_0.8.5