Read and validate a long-format manifest CSV file

Reads a tidy, long-format manifest CSV (one row per sample) and delegates to validate_manifest() for validation and structuring.

Usage

read_manifest_csv(path, ..., allow_duplicates = FALSE)

Arguments

path

Character scalar with file path to a CSV manifest file. Path must exist and the file must be readable.

...

Additional named arguments passed to readr::read_csv(), such as col_types, skip, comment, etc.

allow_duplicates

Logical. If TRUE, a repeated sample_id is permitted. If FALSE (default), it raises an error. Passed through to validate_manifest().

Value

The list returned by validate_manifest(): subject_tbl, sample_map, and completeness_tbl.

Details

Superseded by read_manifest(), which also reads TSV and Excel files. This function stays for existing code; new code should call read_manifest() instead. Every column is read as character unless ... supplies its own col_types.

See also

read_manifest() for CSV, TSV, and Excel in one function, validate_manifest() for the validation rules, cohort_new() for creating a Cohort from manifest data

Examples

# Create a temporary long-format CSV manifest
manifest_file <- tempfile(fileext = ".csv")
writeLines(
  c(
    "subject_id,species,assay,sample_id,role",
    "RAT001,rat,wes,WES_T1,tumor",
    "RAT001,rat,wes,WES_N1,normal",
    "RAT001,rat,scrna,RNA_1,tumor",
    "MOUSE1,mouse,atac,ATAC_1,NA",
    "HUM01,human,wgs,WGS_T1,tumor"
  ),
  manifest_file
)

# Read and validate the manifest
parsed <- read_manifest_csv(manifest_file)
parsed$subject_tbl
#> # A tibble: 3 × 2
#>   subject_id species
#>   <chr>      <chr>  
#> 1 RAT001     rat    
#> 2 MOUSE1     mouse  
#> 3 HUM01      human  
parsed$sample_map
#> # A tibble: 5 × 4
#>   subject_id assay sample_id role  
#>   <chr>      <chr> <chr>     <chr> 
#> 1 RAT001     wes   WES_T1    tumor 
#> 2 RAT001     wes   WES_N1    normal
#> 3 RAT001     scrna RNA_1     tumor 
#> 4 MOUSE1     atac  ATAC_1    NA    
#> 5 HUM01      wgs   WGS_T1    tumor 
parsed$completeness_tbl
#> # A tibble: 4 × 3
#>   subject_id assay n_samples
#>   <chr>      <chr>     <int>
#> 1 HUM01      wgs           1
#> 2 MOUSE1     atac          1
#> 3 RAT001     scrna         1
#> 4 RAT001     wes           2