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qtl2

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
)

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.

Value

(Invisibly) The data structure that was written.

See Also

Examples

# 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))
qtl2

Quantitative Trait Locus Mapping in Experimental Crosses

v0.24
GPL-3
Authors
Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), R Core Team [ctb]
Initial release
2020-12-16

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