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Make scores

Source: R/make_scores.R
make_scores.Rd

Make scores

Usage

make_scores(input.df, cols, directions, weights = NULL)

Arguments

input.df

data.frame, table with only snps that are to be included. Must have "marker.ID" column

cols

character, vector of column names indicating which variables to included in the score

directions

numeric, a vector indicating which direction is to be considered more indicative of an association. 1 indicates higher is better, -1 indicates lower is better. The order should correspond with the order in cols.

weights

numeric, a vector indicating weights for the variables. These must add up to 1.

Value

A table with a score for each marker based on aggregating the variables indicated.

  1. Variables are first made negative if indicated by directions vector.

  2. Min/max normalization is applied to put all variables on same scale.

  3. A weighted mean based on the weights vector is taken of the normalized variables and output as the final score.

Examples

gwas.df <- read.csv(system.file(
    "extdata", 
    "PanvarExample_GLM_GWASresults.csv", 
    package = "panvaR"))

# use direction to specify which direction in each variable indicates 
# greater predicted impact
scores.out <- make_scores(
  input.df = gwas.df,
  cols = c("EFF", "PVAL"),
  directions = c(1, -1),
  weights = c(.5, .5))