sim.CC.data: Simulate Collaborative Cross (CC) phenotype data from the...
In gkeele/sparcc: Simulated Power Analysis in the Realized Collaborative Cross

This function takes various input parameters to simulate CC data to be used in power calculations or as input data for other tools that analyze CC data.

sim.CC.data(genomecache, CC.lines = NULL, num.lines = NULL,
  vary.lines = TRUE, locus = NULL, vary.locus = TRUE, num.replicates,
  num.sim, M.ID = NULL, sample.as.method = c("uniform", "crp"),
  num.alleles = 8, num.founders = 8, qtl.effect.size, beta = NULL,
  strain.effect.size = 0, impute = TRUE, scale.qtl.mode = c("B",
  "MB", "DAMB", "none"), return.value = c("raw", "fixef.resid",
  "ranef.resid"), return.means = TRUE)

`genomecache`	The path to the genome cache directory. The genome cache is a particularly structured directory that stores the haplotype probabilities/dosages at each locus. It has an additive model subdirectory and a full model subdirectory. Each contains subdirectories for each chromosome, which then store .RData files for the probabilities/dosages of each locus.
`CC.lines`	DEFAULT: NULL. If NULL is specified, sim.CC.data() will randomly draw samples of the available CC lines of the size specified in num.lines.
`num.lines`	DEFAULT: NULL. If NULL, sim.CC.data() expects that CC.lines is non-NULL. If CC.lines is NULL, num.lines determines the number of CC lines that are sampled.
`vary.lines`	DEFAULT: TRUE. If CC.lines is NULL and vary.lines is TRUE, then sim.CC.data() will sample multiple sets of CC lines of the size specified in num.lines. If CC.lines is NULL and vary.lines is FALSE, then just one set of CC lines will be sampled.
`locus`	DEFAULT: NULL. If NULL is specified, sim.CC.data() will randomly draw a locus stored in the genome cache.
`vary.locus`	DEFAULT: TRUE. If locus is NULL and vary.locus is TRUE, then sim.CC.data() will sample as many loci as specified in num.sim. If locus is NULL and vary.locus is FALSE, then sim.CC.data() will only sample one locus.
`num.replicates`	The number of replicates of each CC line that will be simulated. Mapping for power calculations will use strain means. Currently requires that all lines have the same number of replicates.
`num.sim`	The number of phenotypes to be simulated for a given parameter setting.
`M.ID`	DEFAULT: NULL. M is a matrix that maps from counts of founder haplotypes to counts of functional alleles. Mapping will be based on haplotype association, but potentially there are two to the number of founders alleles at the QTL. M.ID is a string that codifies this mapping. One potential balanced two allele M.ID would be "c(0,0,0,0,1,1,1,1)". With 8 functional alleles, on per founder, the only M.ID is "c(0,1,2,3,4,5,6,7)". If M.ID is NULL, M.ID will be sampled.
`sample.as.method`	DEFAULT: "uniform". The procedure used for sampling the allelic series. If every strain has its own allele, this option does not matter. Alternatively, a Chinese restaurant process ("crp") can be used, which is possibly more biologically accurate, and will favor allelic series that are less balanced (1 vs 7).
`num.alleles`	DEFAULT: 8. The number of functional alleles. Must be less than or equal to the number of founders.
`num.founders`	DEFAULT: 8. The number of founders, which must correspond to the genome cache. The CC has eight.
`qtl.effect.size`	The size of the simulated QTL effect. The scale of the input is in proportion of the phenotypic variance due to the QTL, thus should be greater than or equal to zero, and less than one.
`beta`	DEFAULT: NULL. Allows for the manual specification of QTL effect. Is expected to be a vector the length of the number of alleles. It will be scaled based on qtl.effect.size.
`strain.effect.size`	DEFAULT: 0. The size of the simulated strain effect, which represents something akin to a polygenic effect. Other variants specific to CC lines will result in overall strain-specific effects. The scale of the input is in proportion of the phenotypic variance due to the strain, thus should be greater than or equal to zero, and less than one.
`impute`	DEFAULT: TRUE. If TRUE, the QTL portion of the design matrix in the simulation is a realized sampling of haplotypes from the probabilities. If FALSE, the simulations are based on the probabilities, which is flawed in terms of biological reality.
`scale.qtl.mode`	DEFAULT: "B". Specifies how the QTL effect is scaled. If "B", then the variance of the qtl effect vector beta is scaled to the effect size specified in qtl.effect.size, which would be the variance explained in a population perfectly balanced in terms of the functional alleles. If "MB", the the variance of M the variance explained in a population balanced in terms of founder strains with the allelic series that is specified in M. If "DAMB", the variance of D specific set of CC strains (specified in D).
`return.value`	DEFAULT: "raw". If "raw", residuals are not taken. If "fixef.resid", then the data are residuals after regressing phenotype on strain. If "ranef.resid", then the data have had the strain BLUP effect subtracted.
`return.means`	DEFAULT: TRUE. If TRUE, strain means are returned. If FALSE, the full data with replicate observations of strains are returned.