transformations: Basic functions to do transformation / normalization of...

In KonradZych/phenotypes2genotypes: High-Throughput Generation of Genetic Markers and Maps from Molecular Phenotypes for Crosses Between Inbred Strains

Description

Basic functions to do transformation / normalization of phenotypes.

Usage

  transformation(x, transformations=c("nothing","log","sqrt","reciprocal","probit",
    "logit"), ..., verbose=TRUE)

Arguments

x	data matrix with measurements, Rows: Traits/Phenotypes columns: Individuals.
transformations	which function should be used to transform the data: nothing - no data transformation performed. log - log(data) sqrt - sqrt(data) reciprocal - 1/(data) probit - probit transformation logit - logit transformation
...	Passed to the underlying test function.
verbose	Be verbose.

Value

List with matrices.

Author(s)

Danny Arends [e-mail] Maintainer: Danny Arends [e-mail]

See Also

• cross.saturate - Saturate existing map.

• cross.denovo - Create de novo genetic map or chromosome assignment vector.

Examples

	data <- matrix(runif(1000),10,100)
  resA <- transformation(data, c("log","logit"))
  resB <- transformation(data, c("reciprocal","probit"))

KonradZych/phenotypes2genotypes documentation built on May 30, 2019, 2:45 p.m.