Loading and re-analysing public data through ReactomeGSA (original) (raw)
Datasets found through the find_public_datasets
function can subsequently loaded using the load_public_dataset
function.
# find the correct entry in the search result
# this must be the complete row of the data.frame returned
# by the find_public_datasets function
dataset_search_entry <- datasets[datasets$id == "E-MTAB-7453", ]
str(dataset_search_entry)
#> 'data.frame': 1 obs. of 7 variables:
#> $ title : chr "RNA-seq of the human melanoma cell-line A375P treated with the BRAF inhibitor PLX4720 and a DMSO control"
#> $ id : chr "E-MTAB-7453"
#> $ resource_name : chr "EBI Expression Atlas"
#> $ description : chr ""
#> $ resource_loading_id: chr "ebi_gxa"
#> $ loading_parameters :List of 1
#> ..$ :'data.frame': 1 obs. of 2 variables:
#> .. ..$ name : chr "dataset_id"
#> .. ..$ value: chr "E-MTAB-7453"
#> $ web_link : chr "https://www.ebi.ac.uk/gxa/experiments/E-MTAB-7453/Results"
# this function only takes one argument, which must be
# a single row from the data.frame returned by the
# find_public_datasets function
mel_cells_braf <- load_public_dataset(dataset_search_entry, verbose = TRUE)
#> Downloading data from ExpressionAtlas
#> Converting ExpressionAtlas data
The returned object is an ExpressionSet
object that already contains all available metada.
# use the biobase functions to access the metadata
library(Biobase)
#> Loading required package: BiocGenerics
#> Loading required package: generics
#>
#> Attaching package: 'generics'
#> The following object is masked from 'package:dplyr':
#>
#> explain
#> The following objects are masked from 'package:base':
#>
#> as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
#> setequal, union
#>
#> Attaching package: 'BiocGenerics'
#> The following object is masked from 'package:dplyr':
#>
#> combine
#> The following object is masked from 'package:limma':
#>
#> plotMA
#> The following objects are masked from 'package:stats':
#>
#> IQR, mad, sd, var, xtabs
#> The following objects are masked from 'package:base':
#>
#> Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#> as.data.frame, basename, cbind, colnames, dirname, do.call,
#> duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
#> mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
#> rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
#> unsplit, which.max, which.min
#> Welcome to Bioconductor
#>
#> Vignettes contain introductory material; view with
#> 'browseVignettes()'. To cite Bioconductor, see
#> 'citation("Biobase")', and for packages 'citation("pkgname")'.
# basic metadata
pData(mel_cells_braf)
#> Sample.Id AtlasAssayGroup organism cell_line organism_part
#> ERR2950741 ERR2950741 g2 Homo sapiens A375-P skin
#> ERR2950742 ERR2950742 g2 Homo sapiens A375-P skin
#> ERR2950743 ERR2950743 g2 Homo sapiens A375-P skin
#> ERR2950744 ERR2950744 g1 Homo sapiens A375-P skin
#> ERR2950745 ERR2950745 g1 Homo sapiens A375-P skin
#> ERR2950746 ERR2950746 g1 Homo sapiens A375-P skin
#> cell_type disease compound dose
#> ERR2950741 epithelial cell melanoma none
#> ERR2950742 epithelial cell melanoma none
#> ERR2950743 epithelial cell melanoma none
#> ERR2950744 epithelial cell melanoma PLX4720 1 micromolar
#> ERR2950745 epithelial cell melanoma PLX4720 1 micromolar
#> ERR2950746 epithelial cell melanoma PLX4720 1 micromolar
Detailed descriptions of the loaded study are further stored in the metadata slot.
# access the stored metadata using the experimentData function
experimentData(mel_cells_braf)
#> Experiment data
#> Experimenter name: E-MTAB-7453
#> Laboratory:
#> Contact information:
#> Title: RNA-seq of the human melanoma cell-line A375P treated with the BRAF inhibitor PLX4720 and a DMSO control
#> URL: https://www.ebi.ac.uk/gxa/experiments/E-MTAB-7453/Results
#> PMIDs:
#> No abstract available.
#> notes:
#> notes:
#> Public dataset loaded from EBI Expression Atlas through ReactomeGSA.
# for some datasets, longer descriptions are available. These
# can be accessed using the abstract function
abstract(mel_cells_braf)
#> [1] ""
Additionally, you can use the table
function to quickly get the number of available samples for a specific metadata field.
table(mel_cells_braf$compound)
#>
#> PLX4720 none
#> 3 3