Reads TMA spreadsheet from tma_file
which must contain one "TMA map" sheet and one or more
biomaker-specific sheets.
Value
A data frame with the deconvoluted data. The function will match core IDs from the TMA map sheet with the biomarker-specific sheets and return a data frame with a "core_id" column and as many columns for each biomarker as necessary.
For instance, if core ID 1 has 3 values for biomarker A, the output will contain 3 columns for biomarker A (A.c1, A.c2, A.c3); if another core ID has 2 values for biomaker A, its corresponding A.c1 and A.c2 columns will be filled with the values for that core ID and the A.c3 column will be filled with NA.
If there are no values for a given core ID in a biomarker-specific sheet, the corresponding columns will all be filled with NA.
Examples
library(TMAtools)
tma_file <- system.file("extdata", "example.xlsx", package = "TMAtools")
deconvoluted_data <- deconvolute(tma_file)
head(deconvoluted_data)
#> # A tibble: 6 × 13
#> core_id TP53.c1 TP53.c2 TP53.c3 TP53.c4 TP53.c5 TP53.c6 ER.c1 ER.c2 ER.c3
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 X1 X1 NA NA NA NA NA X1 NA NA
#> 2 X2 X2 NA NA NA NA NA X2 NA NA
#> 3 X3 X3 NA NA NA NA NA X3 NA NA
#> 4 1 x 4 0 2 NA NA x x 0
#> 5 4 1 9 2 1 5 8 9 9 x
#> 6 X4 X4 NA NA NA NA NA X4 NA NA
#> # ℹ 3 more variables: ER.c4 <chr>, ER.c5 <chr>, ER.c6 <chr>