Load a series of ADATs and return a list of soma_adat
objects, one for each ADAT file.
collapseAdats() concatenates a list of ADATs from loadAdatsAsList(),
while maintaining the relevant attribute entries (mainly the HEADER
element). This makes writing out the final object possible without the
loss of HEADER information.
Usage
loadAdatsAsList(files, collapse = FALSE, verbose = interactive(), ...)
collapseAdats(x)Arguments
- files
A character string of files to load.
- collapse
Logical. Should the resulting list of ADATs be collapsed into a single ADAT object?
- verbose
Logical. Should the function call be run in verbose mode.
- ...
Additional arguments passed to
read_adat().- x
A list of
soma_adatclass objects returned fromloadAdatsAsList().
Value
A list of ADATs named by files, each a soma_adat object
corresponding to an individual file in files. For collapseAdats(),
a single, collapsed soma_adat object.
Details
- Note 1:
The default behavior is to "vertically bind" (
rbind()) on the intersect of the column variables, with unique columns silently dropped.- Note 2:
If "vertically binding" on the column union is desired, use
bind_rows(), however this results inNAsin non-intersecting columns. For many files with little variable intersection, a sparse RFU-matrix will result (and will likely break ADAT attributes):adats <- loadAdatsAsList(files) union_adat <- dplyr::bind_rows(adats, .id = "SourceFile")
See also
Other IO:
parseHeader(),
read_adat(),
soma_adat,
write_adat()
Examples
# only 1 file in directory
dir(system.file("extdata", package = "SomaDataIO"))
#> [1] "example_data10.adat"
files <- system.file("extdata", package = "SomaDataIO") |>
dir(pattern = "[.]adat$", full.names = TRUE) |> rev()
adats <- loadAdatsAsList(files)
class(adats)
#> [1] "list"
# collapse into 1 ADAT
collapsed <- collapseAdats(adats)
class(collapsed)
#> [1] "soma_adat" "data.frame"
# Alternatively use `collapse = TRUE`
# \donttest{
loadAdatsAsList(files, collapse = TRUE)
#> ══ SomaScan Data ═════════════════════════════════════════════════════════
#> SomaScan version V4 (5k)
#> Signal Space 5k
#> Attributes intact ✓
#> Rows 10
#> Columns 5318
#> Clinical Data 34
#> Features 5284
#> ── Column Meta ───────────────────────────────────────────────────────────
#> ℹ SeqId, SeqIdVersion, SomaId, TargetFullName, Target, UniProt,
#> ℹ EntrezGeneID, EntrezGeneSymbol, Organism, Units, Type,
#> ℹ Dilution, PlateScale_Reference, CalReference,
#> ℹ Cal_Example_Adat_Set001, ColCheck,
#> ℹ CalQcRatio_Example_Adat_Set001_170255, QcReference_170255,
#> ℹ Cal_Example_Adat_Set002, CalQcRatio_Example_Adat_Set002_170255,
#> ℹ Dilution2
#> ── Tibble ────────────────────────────────────────────────────────────────
#> # A tibble: 10 × 5,319
#> row_names PlateId PlateRunDate ScannerID PlatePosition SlideId Subarray
#> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 25849580… Exampl… 2020-06-18 SG152144… H9 2.58e11 3
#> 2 25849580… Exampl… 2020-06-18 SG152144… H8 2.58e11 7
#> 3 25849580… Exampl… 2020-06-18 SG152144… H7 2.58e11 8
#> 4 25849580… Exampl… 2020-06-18 SG152144… H6 2.58e11 4
#> 5 25849580… Exampl… 2020-06-18 SG152144… H5 2.58e11 4
#> 6 25849580… Exampl… 2020-06-18 SG152144… H4 2.58e11 8
#> 7 25849580… Exampl… 2020-06-18 SG152144… H3 2.58e11 3
#> 8 25849580… Exampl… 2020-06-18 SG152144… H2 2.58e11 8
#> 9 25849580… Exampl… 2020-06-18 SG152144… H12 2.58e11 8
#> 10 25849580… Exampl… 2020-06-18 SG152144… H11 2.58e11 3
#> # ℹ 5,312 more variables: SampleId <chr>, SampleType <chr>,
#> # PercentDilution <int>, SampleMatrix <chr>, Barcode <lgl>,
#> # Barcode2d <chr>, SampleName <lgl>, SampleNotes <lgl>,
#> # AliquotingNotes <lgl>, SampleDescription <chr>, …
#> ══════════════════════════════════════════════════════════════════════════
# }