Process data from assay tab files
Process data from assay tab files with technology type mass spectrometry (ms). Processing those files requires the xcms package to be installed.
Process data from assay tab files with technology type DNA microarray (ms). Processing those files requires the Biobase and affy packages to be installed.
Usage
processAssay(isaObject, aTabObject, type = c("raw", "derived"))
# S4 method for ISA,assayTab,character
processAssay(isaObject, aTabObject, type = c("raw", "derived"))
# S4 method for ISA,msAssayTab,character
processAssay(isaObject, aTabObject, type = c("raw", "derived"))
# S4 method for ISA,microarrayAssayTab,character
processAssay(isaObject, aTabObject, type = c("raw", "derived"))Arguments
- isaObject
An object of the ISA.
- aTabObject
An object of the microarrayAssayTab.
- type
A character string indicating which data files should be processed, either "raw" for raw data files, or "derived" for derived data files. The file names are taken from the corresponding column in the
aTabObject.
Examples
### Atwell data.
## Read example Atwell data set.
isaObject1 <- readISATab(path = file.path(system.file("extdata/Atwell",
package = "isatabr")))
## Get assay tabs for isaObject1.
aTabObjects <- getAssayTabs(isaObject1)
## Process assay data.
isaDat <- processAssay(isaObject = isaObject1,
aTabObject = aTabObjects$s_study1.txt$a_study1.txt,
type = "derived")
## Display first rows and columns.
head(isaDat[, 1:10])
#> Assay Name LD LDV SD SDV FT10 FT16 FT22 Seed Dormancy Emco5
#> 1 assay152 6.84105 32.6 93.0417 4.97494 74 87 89 NA NA
#> 2 assay279 NA NA NA NA NA NA NA NA NA
#> 3 assay211 NA NA NA NA NA NA NA NA NA
#> 4 assay256 NA NA NA NA NA NA NA NA NA
#> 5 assay907 NA NA NA NA NA NA NA NA NA
#> 6 assay948 NA NA NA NA NA NA NA NA NA
# \donttest{
### faahKO data. - This requires the xcms package to be installed.
## Read ISA-Tab files for faahKO.
if (requireNamespace("xcms")) {
isaObject3 <- readISATab(path = file.path(system.file("extdata/faahKO",
package = "isatabr")))
## Get assay tabs for isaObject3.
aTabObjects3 <- getAssayTabs(isaObject3)
## Process assay data.
isaDat3 <-
processAssay(isaObject = isaObject3,
aTabObject = aTabObjects3$s_Proteomic_profiling_of_yeast.txt$a_metabolite.txt,
type = "raw")
## Display output.
isaDat3
}
#> Loading required namespace: xcms
#> Loading required package: xcms
#> Loading required package: BiocParallel
#> Loading required package: MSnbase
#> Loading required package: BiocGenerics
#>
#> Attaching package: ‘BiocGenerics’
#> 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, intersect, is.unsorted,
#> lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#> pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
#> tapply, union, unique, unsplit, which.max, which.min
#> Loading required package: Biobase
#> Welcome to Bioconductor
#>
#> Vignettes contain introductory material; view with
#> 'browseVignettes()'. To cite Bioconductor, see
#> 'citation("Biobase")', and for packages 'citation("pkgname")'.
#> Loading required package: mzR
#> Loading required package: Rcpp
#> Loading required package: S4Vectors
#> Loading required package: stats4
#>
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:utils’:
#>
#> findMatches
#> The following objects are masked from ‘package:base’:
#>
#> I, expand.grid, unname
#> Loading required package: ProtGenerics
#>
#> Attaching package: ‘ProtGenerics’
#> The following object is masked from ‘package:stats’:
#>
#> smooth
#>
#> This is MSnbase version 2.26.0
#> Visit https://lgatto.github.io/MSnbase/ to get started.
#>
#> Attaching package: ‘MSnbase’
#> The following object is masked from ‘package:base’:
#>
#> trimws
#>
#> This is xcms version 3.22.0
#>
#> Attaching package: ‘xcms’
#> The following object is masked from ‘package:stats’:
#>
#> sigma
#> An "xcmsSet" object with 1 samples
#>
#> Time range: 2506.1-4132.1 seconds (41.8-68.9 minutes)
#> Mass range: 200.1-599.3129 m/z
#> Peaks: 470 (about 470 per sample)
#> Peak Groups: 0
#> Sample classes:
#>
#> Feature detection:
#> o Peak picking performed on MS1.
#> Profile settings: method = bin
#> step = 0.1
#>
#> Memory usage: 0.0804 MB
# }