HEssRNA (version 1.0.1)

smplSizPred: Predict Number of Replicates Based on Heritability, Power, and Fold Change

Description

This function predicts the number of replicates required for a given experiment based on heritability, power, fold change, and tissue type. The model is constructed using the provided data, and the prediction is adjusted based on the selected trait's mean heritability value. The function ensures that the predicted replicates are valid, rounding negative or unrealistic values to sensible minimums based on the heritability class.

Usage

smplSizPred(
  df4model = df4modelInpt,
  hIndexMeanDFinput = hIndexMeanDF,
  heritabilityClass,
  inptPwr,
  fc,
  trait = NULL,
  tissue = NULL
)

Value

A numeric value representing the predicted number of replicates. The value is rounded to the nearest whole number and adjusted to ensure it is valid for the selected heritability class.

Arguments

df4model

A data frame containing the input data for the model. It should include the following columns: NoOfReplicates, HeritabilityValue, pwr, FoldChange, and optionally Tissue.

hIndexMeanDFinput

A data frame containing the mean heritability values for each trait. It should include at least the columns Trait.name and MeanValue.

heritabilityClass

A character string specifying the heritability class used for filtering and adjusting the prediction. Possible values are "low", "mid", and "high".

inptPwr

A numeric value representing the power used in the model.

fc

A numeric value representing the fold change used in the model.

trait

An optional parameter specifying the trait. If provided, the heritability value for the trait will be used to adjust the heritability class values.

tissue

An optional parameter specifying the tissue type. If provided, the model will include tissue as a factor in the regression. If not provided, tissue is excluded.

References

Sun et al. (2017) tools:::Rd_expr_doi("10.1093/nar/gkx204")

Examples

# \donttest{
# Example usage:
df4modelInpt <- data.frame(
    NoOfReplicates = c(3, 5, 7, 9, 11),
    HeritabilityClass = c("high", "mid", "low", "high", "mid"),
    HeritabilityValue = c(0.5, 0.6, 0.7, 0.5, 0.6),
    pwr = c(0.8, 0.9, 0.85, 0.88, 0.86),
    FoldChange = c(2, 3, 2.5, 2.8, 3.2),
    Tissue = c("Liver", "Liver", "Kidney", "Liver", "Kidney")
)
hIndexMeanDF <- data.frame(Trait.name = c("Trait1", "Trait2"),
                           MeanValue = c(0.3, 0.5))
NoOfReplicatesPred <- smplSizPred(df4model = df4modelInpt,
                      hIndexMeanDFinput = hIndexMeanDF,
                      heritabilityClass = "mid",
                      inptPwr = 0.85,
                      fc = 2.5,
                      trait = "Trait1",
                      tissue = "Liver")
print(NoOfReplicatesPred)
# }