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Write a pipeline sample sheet from a cohort

Source: R/sample_sheet.R
sample_sheet.Rd

Builds the sample sheet a pipeline expects, from a cohort's sample map and subject table. A few common shapes ship with the package (see sample_sheet_templates()); pass a custom mapping or a function for anything else.

Usage

sample_sheet(
  cohort,
  template = "nf-core/rnaseq",
  assay = NULL,
  path = NULL,
  ...
)

Arguments

cohort

A Cohort object.

template

One of:

  • A character scalar naming a built-in template (see sample_sheet_templates()).

  • A named character vector mapping an output column name to a column of samples(cohort, with_subjects = TRUE), e.g. c(sample = "sample_id", path = "fastq_1").

  • A function function(joined, ...) returning a data.frame, where joined is samples(cohort, assay = assay, with_subjects = TRUE).

Default "nf-core/rnaseq".

assay

Character scalar naming the assay to include. Required when the cohort has more than one assay; optional when it has exactly one.

path

Optional output file path. When given, the sheet is written there as CSV and returned invisibly.

...

Passed to a function template. Ignored for a built-in or a named-vector template.

Value

A tibble with one row per sample. Invisible when path is given.

Details

The built-in templates are:

  • "nf-core/rnaseq": sample, fastq_1, fastq_2, strandedness ("auto" when the manifest has no strandedness column).

  • "nf-core/rnavar": sample, fastq_1, fastq_2.

  • "nf-core/atacseq": sample, fastq_1, fastq_2, replicate (1 when the manifest has no replicate column).

  • "nf-core/sarek": patient, sex ("XX"/"XY", from a sex column of "F"/"M"), status (1 for a "tumor" or "resistant" role, 0 otherwise), sample, lane (1 when absent), fastq_1, fastq_2.

Every template needs fastq_1 in the sample map (and fastq_2 where the template writes it); declare it with validate_manifest(sample_cols = ) or read_manifest(sample_cols = ) if your manifest names it differently.

See also

sample_sheet_templates(), samples(), check_paths()

Examples

manifest <- data.frame(
  subject_id = c("R1", "R1"),
  species = "rat",
  sex = "F",
  assay = "wes",
  sample_id = c("T1", "N1"),
  role = c("tumor", "normal"),
  fastq_1 = c("t1_R1.fq.gz", "n1_R1.fq.gz"),
  fastq_2 = c("t1_R2.fq.gz", "n1_R2.fq.gz"),
  stringsAsFactors = FALSE
)
parsed <- validate_manifest(manifest)
cohort <- cohort_new(parsed$subject_tbl, parsed$sample_map)

sample_sheet(cohort, template = "nf-core/sarek")
#> # A tibble: 2 × 7
#>   patient sex   status sample  lane fastq_1     fastq_2    
#>   <chr>   <chr>  <int> <chr>  <int> <chr>       <chr>      
#> 1 R1      XX         1 T1         1 t1_R1.fq.gz t1_R2.fq.gz
#> 2 R1      XX         0 N1         1 n1_R1.fq.gz n1_R2.fq.gz

# A custom mapping
sample_sheet(cohort, template = c(sample = "sample_id", read1 = "fastq_1"))
#> # A tibble: 2 × 2
#>   sample read1      
#>   <chr>  <chr>      
#> 1 T1     t1_R1.fq.gz
#> 2 N1     n1_R1.fq.gz