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 4.2.0 RC (2022-04-21 r82226)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
## 
## 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       
## 
## attached base packages:
## [1] parallel  stats4    stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] minfi_1.43.0                bumphunter_1.39.0          
##  [3] locfit_1.5-9.5              iterators_1.0.14           
##  [5] foreach_1.5.2               Biostrings_2.65.0          
##  [7] XVector_0.37.0              SummarizedExperiment_1.27.0
##  [9] MatrixGenerics_1.9.0        matrixStats_0.62.0         
## [11] GenomicRanges_1.49.0        GenomeInfoDb_1.33.0        
## [13] IRanges_2.31.0              S4Vectors_0.35.0           
## [15] rexposome_1.19.0            Biobase_2.57.0             
## [17] BiocGenerics_0.43.0         BiocStyle_2.25.0           
## 
## loaded via a namespace (and not attached):
##   [1] utf8_1.2.2                gmm_1.6-6                
##   [3] tidyselect_1.1.2          lme4_1.1-29              
##   [5] RSQLite_2.2.12            AnnotationDbi_1.59.0     
##   [7] htmlwidgets_1.5.4         FactoMineR_2.4           
##   [9] grid_4.2.0                BiocParallel_1.31.0      
##  [11] norm_1.0-10.0             munsell_0.5.0            
##  [13] preprocessCore_1.59.0     codetools_0.2-18         
##  [15] DT_0.22                   colorspace_2.0-3         
##  [17] filelock_1.0.2            knitr_1.38               
##  [19] rstudioapi_0.13           leaps_3.1                
##  [21] GenomeInfoDbData_1.2.8    bit64_4.0.5              
##  [23] rhdf5_2.41.0              vctrs_0.4.1              
##  [25] generics_0.1.2            xfun_0.30                
##  [27] BiocFileCache_2.5.0       R6_2.5.1                 
##  [29] illuminaio_0.39.0         bitops_1.0-7             
##  [31] rhdf5filters_1.9.0        cachem_1.0.6             
##  [33] reshape_0.8.9             DelayedArray_0.23.0      
##  [35] assertthat_0.2.1          BiocIO_1.7.0             
##  [37] scales_1.2.0              nnet_7.3-17              
##  [39] gtable_0.3.0              lsr_0.5.2                
##  [41] sandwich_3.0-1            rlang_1.0.2              
##  [43] genefilter_1.79.0         scatterplot3d_0.3-41     
##  [45] GlobalOptions_0.1.2       splines_4.2.0            
##  [47] rtracklayer_1.57.0        GEOquery_2.65.0          
##  [49] impute_1.71.0             checkmate_2.1.0          
##  [51] BiocManager_1.30.17       yaml_2.3.5               
##  [53] reshape2_1.4.4            GenomicFeatures_1.49.0   
##  [55] backports_1.4.1           Hmisc_4.7-0              
##  [57] tools_4.2.0               bookdown_0.26            
##  [59] nor1mix_1.3-0             ggplot2_3.3.5            
##  [61] ellipsis_0.3.2            gplots_3.1.3             
##  [63] jquerylib_0.1.4           RColorBrewer_1.1-3       
##  [65] siggenes_1.71.0           Rcpp_1.0.8.3             
##  [67] plyr_1.8.7                base64enc_0.1-3          
##  [69] sparseMatrixStats_1.9.0   progress_1.2.2           
##  [71] zlibbioc_1.43.0           purrr_0.3.4              
##  [73] RCurl_1.98-1.6            prettyunits_1.1.1        
##  [75] openssl_2.0.0             rpart_4.1.16             
##  [77] zoo_1.8-10                ggrepel_0.9.1            
##  [79] cluster_2.1.3             magrittr_2.0.3           
##  [81] data.table_1.14.2         circlize_0.4.14          
##  [83] pcaMethods_1.89.0         mvtnorm_1.1-3            
##  [85] xtable_1.8-4              hms_1.1.1                
##  [87] evaluate_0.15             XML_3.99-0.9             
##  [89] jpeg_0.1-9                mclust_5.4.9             
##  [91] gridExtra_2.3             shape_1.4.6              
##  [93] compiler_4.2.0            biomaRt_2.53.0           
##  [95] tibble_3.1.6              KernSmooth_2.23-20       
##  [97] crayon_1.5.1              minqa_1.2.4              
##  [99] htmltools_0.5.2           tzdb_0.3.0               
## [101] Formula_1.2-4             tidyr_1.2.0              
## [103] DBI_1.1.2                 corrplot_0.92            
## [105] dbplyr_2.1.1              MASS_7.3-57              
## [107] tmvtnorm_1.5              rappdirs_0.3.3           
## [109] boot_1.3-28               readr_2.1.2              
## [111] Matrix_1.4-1              cli_3.3.0                
## [113] imputeLCMD_2.0            pryr_0.1.5               
## [115] quadprog_1.5-8            pkgconfig_2.0.3          
## [117] flashClust_1.01-2         GenomicAlignments_1.33.0 
## [119] foreign_0.8-82            xml2_1.3.3               
## [121] annotate_1.75.0           bslib_0.3.1              
## [123] rngtools_1.5.2            multtest_2.53.0          
## [125] beanplot_1.3.1            scrime_1.3.5             
## [127] doRNG_1.8.2               stringr_1.4.0            
## [129] digest_0.6.29             base64_2.0               
## [131] rmarkdown_2.14            htmlTable_2.4.0          
## [133] DelayedMatrixStats_1.19.0 restfulr_0.0.13          
## [135] curl_4.3.2                Rsamtools_2.13.0         
## [137] gtools_3.9.2              rjson_0.2.21             
## [139] nloptr_2.0.0              lifecycle_1.0.1          
## [141] nlme_3.1-157              jsonlite_1.8.0           
## [143] Rhdf5lib_1.19.0           askpass_1.1              
## [145] limma_3.53.0              fansi_1.0.3              
## [147] pillar_1.7.0              lattice_0.20-45          
## [149] KEGGREST_1.37.0           fastmap_1.1.0            
## [151] httr_1.4.2                survival_3.3-1           
## [153] glue_1.6.2                png_0.1-7                
## [155] glmnet_4.1-4              bit_4.0.4                
## [157] stringi_1.7.6             sass_0.4.1               
## [159] HDF5Array_1.25.0          blob_1.2.3               
## [161] latticeExtra_0.6-29       caTools_1.18.2           
## [163] memoise_2.0.1             dplyr_1.0.8