Reads TMA spreadsheet from tma_file
which must contain one "TMA map" sheet and one or more
biomaker-specific sheets.
Usage
deconvolute(
tma_file,
metadata = NULL,
output_file = NULL,
tma_id = NULL,
partial_overlap_ok = TRUE
)Arguments
- tma_file
Path to input Excel spreadsheet. Both .xlsx and .xls formats are supported. Must contain one "TMA map" sheet and one or more biomarker-specific sheets.
- metadata
data.frame with core_id and accession_id columns
- output_file
Optional path to output Excel spreadsheet.
- tma_id
TMA identifier (from the directory's name)
- partial_overlap_ok
If FALSE, throws an error if the overlap between TMA map and score sheet is only partial (e.g., there is some non-empty value in the score sheet that does not match a value in the TMA map).
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)
#> Error: `path` does not exist: ‘’
head(deconvoluted_data)
#> Error: object 'deconvoluted_data' not found