write_control_file: Write a control file for QTL data

Description

Write the control file (in YAML or JSON) needed by read_cross2() for a set of QTL data.

Usage

write_control_file(
  output_file,
  crosstype = NULL,
  geno_file = NULL,
  founder_geno_file = NULL,
  gmap_file = NULL,
  pmap_file = NULL,
  pheno_file = NULL,
  covar_file = NULL,
  phenocovar_file = NULL,
  sex_file = NULL,
  sex_covar = NULL,
  sex_codes = NULL,
  crossinfo_file = NULL,
  crossinfo_covar = NULL,
  crossinfo_codes = NULL,
  geno_codes = NULL,
  alleles = NULL,
  xchr = NULL,
  sep = ",",
  na.strings = c("-", "NA"),
  comment.char = "#",
  geno_transposed = FALSE,
  founder_geno_transposed = FALSE,
  pheno_transposed = FALSE,
  covar_transposed = FALSE,
  phenocovar_transposed = FALSE,
  description = NULL,
  comments = NULL,
  overwrite = FALSE
)

Value

(Invisibly) The data structure that was written.

Arguments

output_file: File name (with path) of the YAML or JSON file to be created, as a character string. If extension is .json, JSON format is used; otherwise, YAML is used.
crosstype: Character string with the cross type.
geno_file: File name for genotype data.
founder_geno_file: File name for the founder genotype data.
gmap_file: File name for genetic map.
pmap_file: File name for the physical map.
pheno_file: File name for the phenotype data.
covar_file: File name for the covariate data.
phenocovar_file: File name for the phenotype covariate data (i.e., metadata about the phenotypes).
sex_file: File name for the individuals' sex. (Specify just one of sex_file or sex_covar.)
sex_covar: Column name in the covariate data that corresponds to sex. (Specify just one of sex_file or sex_covar.)
sex_codes: Named vector of character strings specifying the encoding of sex. The names attribute should be the codes used in the data files; the values within the vector should be "female" and "male".
crossinfo_file: File name for the cross_info data. (Specify just one of crossinfo_file or crossinfo_covar.)
crossinfo_covar: Column name in the covariate data that corresponds to the cross_info data. (Specify just one of crossinfo_file or crossinfo_covar.)
crossinfo_codes: In the case that there is a single cross info column (whether in a file or as a covariate), you can provide a named vector of character strings specifying the encoding of cross_info. The names attribute should be the codes used; the values within the vector should be the codes to which they will be converted (for example, 0 and 1 for an intercross).
geno_codes: Named vector specifying the encoding of genotypes. The names attribute has the codes used within the genotype and founder genotype data files; the values within the vector should be the integers to which the genotypes will be converted.
alleles: Vector of single-character codes for the founder alleles.
xchr: Character string with the ID for the X chromosome.
sep: Character string that separates columns in the data files.
na.strings: Vector of character strings with codes to be treated as missing values.
comment.char: Character string that is used as initial character in a set of leading comment lines in the data files.
geno_transposed: If TRUE, genotype file is transposed (with markers as rows).
founder_geno_transposed: If TRUE, founder genotype file is transposed (with markers as rows).
pheno_transposed: If TRUE, phenotype file is transposed (with phenotypes as rows).
covar_transposed: If TRUE, covariate file is transposed (with covariates as rows).
phenocovar_transposed: If TRUE, phenotype covariate file is transposed (with phenotype covariates as rows).
description: Optional character string describing the data.
comments: Vector of character strings to be inserted as comments at the top of the file (in the case of YAML), with each string as a line. For JSON, the comments are instead included within the control object.
overwrite: If TRUE, overwrite file if it exists. If FALSE (the default) and the file exists, stop with an error.

Details

This function takes a set of parameters and creates the control file (in YAML or JSON format) needed for the new input data file format for R/qtl2. See the sample data files and the vignette describing the input file format.

Examples

Run this code

# Control file for the sample dataset, grav2
grav2_control_file <- file.path(tempdir(), "grav2.yaml")
write_control_file(grav2_control_file,
                   crosstype="riself",
                   geno_file="grav2_geno.csv",
                   gmap_file="grav2_gmap.csv",
                   pheno_file="grav2_pheno.csv",
                   phenocovar_file="grav2_phenocovar.csv",
                   geno_codes=c(L=1L, C=2L),
                   alleles=c("L", "C"),
                   na.strings=c("-", "NA"))

# Control file for the sample dataset, iron
iron_control_file <- file.path(tempdir(), "iron.yaml")
write_control_file(iron_control_file,
                   crosstype="f2",
                   geno_file="iron_geno.csv",
                   gmap_file="iron_gmap.csv",
                   pheno_file="iron_pheno.csv",
                   covar_file="iron_covar.csv",
                   phenocovar_file="iron_phenocovar.csv",
                   geno_codes=c(SS=1L, SB=2L, BB=3L),
                   sex_covar="sex",
                   sex_codes=c(f="female", m="male"),
                   crossinfo_covar="cross_direction",
                   crossinfo_codes=c("(SxB)x(SxB)"=0L, "(BxS)x(BxS)"=1L),
                   xchr="X",
                   alleles=c("S", "B"),
                   na.strings=c("-", "NA"))

# Remove these files, to clean up temporary directory
unlink(c(grav2_control_file, iron_control_file))