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 3.6.1 (2019-07-05)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.3 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.10-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.10-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_1.32.0                bumphunter_1.28.0          
##  [3] locfit_1.5-9.1              iterators_1.0.12           
##  [5] foreach_1.4.7               Biostrings_2.54.0          
##  [7] XVector_0.26.0              SummarizedExperiment_1.16.0
##  [9] DelayedArray_0.12.0         BiocParallel_1.20.0        
## [11] matrixStats_0.55.0          GenomicRanges_1.38.0       
## [13] GenomeInfoDb_1.22.0         IRanges_2.20.0             
## [15] S4Vectors_0.24.0            rexposome_1.8.0            
## [17] Biobase_2.46.0              BiocGenerics_0.32.0        
## [19] BiocStyle_2.14.0           
## 
## loaded via a namespace (and not attached):
##   [1] gmm_1.6-2                tidyselect_0.2.5        
##   [3] lme4_1.1-21              RSQLite_2.1.2           
##   [5] AnnotationDbi_1.48.0     htmlwidgets_1.5.1       
##   [7] FactoMineR_1.42          grid_3.6.1              
##   [9] norm_1.0-9.5             munsell_0.5.0           
##  [11] codetools_0.2-16         preprocessCore_1.48.0   
##  [13] withr_2.1.2              colorspace_1.4-1        
##  [15] knitr_1.25               rstudioapi_0.10         
##  [17] leaps_3.0                GenomeInfoDbData_1.2.2  
##  [19] bit64_0.9-7              rhdf5_2.30.0            
##  [21] vctrs_0.2.0              xfun_0.10               
##  [23] BiocFileCache_1.10.0     R6_2.4.0                
##  [25] illuminaio_0.28.0        bitops_1.0-6            
##  [27] reshape_0.8.8            assertthat_0.2.1        
##  [29] scales_1.0.0             nnet_7.3-12             
##  [31] gtable_0.3.0             lsr_0.5                 
##  [33] sandwich_2.5-1           rlang_0.4.1             
##  [35] zeallot_0.1.0            genefilter_1.68.0       
##  [37] scatterplot3d_0.3-41     GlobalOptions_0.1.1     
##  [39] splines_3.6.1            rtracklayer_1.46.0      
##  [41] lazyeval_0.2.2           acepack_1.4.1           
##  [43] impute_1.60.0            GEOquery_2.54.0         
##  [45] checkmate_1.9.4          BiocManager_1.30.9      
##  [47] yaml_2.2.0               reshape2_1.4.3          
##  [49] GenomicFeatures_1.38.0   backports_1.1.5         
##  [51] Hmisc_4.2-0              tools_3.6.1             
##  [53] bookdown_0.14            nor1mix_1.3-0           
##  [55] ggplot2_3.2.1            gplots_3.0.1.1          
##  [57] RColorBrewer_1.1-2       siggenes_1.60.0         
##  [59] Rcpp_1.0.2               plyr_1.8.4              
##  [61] base64enc_0.1-3          progress_1.2.2          
##  [63] zlibbioc_1.32.0          purrr_0.3.3             
##  [65] RCurl_1.95-4.12          prettyunits_1.0.2       
##  [67] rpart_4.1-15             openssl_1.4.1           
##  [69] zoo_1.8-6                ggrepel_0.8.1           
##  [71] cluster_2.1.0            magrittr_1.5            
##  [73] data.table_1.12.6        circlize_0.4.8          
##  [75] pcaMethods_1.78.0        mvtnorm_1.0-11          
##  [77] hms_0.5.2                evaluate_0.14           
##  [79] xtable_1.8-4             XML_3.98-1.20           
##  [81] mclust_5.4.5             gridExtra_2.3           
##  [83] shape_1.4.4              compiler_3.6.1          
##  [85] biomaRt_2.42.0           tibble_2.1.3            
##  [87] KernSmooth_2.23-16       crayon_1.3.4            
##  [89] minqa_1.2.4              htmltools_0.4.0         
##  [91] Formula_1.2-3            tidyr_1.0.0             
##  [93] DBI_1.0.0                corrplot_0.84           
##  [95] dbplyr_1.4.2             MASS_7.3-51.4           
##  [97] tmvtnorm_1.4-10          rappdirs_0.3.1          
##  [99] boot_1.3-23              Matrix_1.2-17           
## [101] readr_1.3.1              imputeLCMD_2.0          
## [103] pryr_0.1.4               quadprog_1.5-7          
## [105] gdata_2.18.0             pkgconfig_2.0.3         
## [107] flashClust_1.01-2        GenomicAlignments_1.22.0
## [109] registry_0.5-1           foreign_0.8-72          
## [111] xml2_1.2.2               annotate_1.64.0         
## [113] rngtools_1.4             pkgmaker_0.27           
## [115] multtest_2.42.0          beanplot_1.2            
## [117] bibtex_0.4.2             doRNG_1.7.1             
## [119] scrime_1.3.5             stringr_1.4.0           
## [121] digest_0.6.22            rmarkdown_1.16          
## [123] base64_2.0               htmlTable_1.13.2        
## [125] DelayedMatrixStats_1.8.0 curl_4.2                
## [127] Rsamtools_2.2.0          gtools_3.8.1            
## [129] nloptr_1.2.1             lifecycle_0.1.0         
## [131] nlme_3.1-141             Rhdf5lib_1.8.0          
## [133] askpass_1.1              limma_3.42.0            
## [135] pillar_1.4.2             lattice_0.20-38         
## [137] httr_1.4.1               survival_2.44-1.1       
## [139] glue_1.3.1               glmnet_2.0-18           
## [141] bit_1.1-14               stringi_1.4.3           
## [143] HDF5Array_1.14.0         blob_1.2.0              
## [145] latticeExtra_0.6-28      caTools_1.17.1.2        
## [147] memoise_1.1.0            dplyr_0.8.3