quantileNormalize-methods: Quantile normalization (methods)

In HELP: Tools for HELP data analysis

Description

Methods for applying quantile normalization to multiple bins of data, divided by a sliding window approach

Methods

x = "missing", y = "missing"

Handle empty function call

x = "matrix", y = "missing"

Handle matrix input, reinterpret function call with two vector input if matrix has two columns, otherwise handle as empty function call

x = "vector", y = "missing"

Handle empty function call

x = "vector", y = "ExpressionSet"

Handle input of an object of class ExpressionSet. Derive binning information from this class but use data from a vector input.

x = "vector", y = "vector"

Handle input of two vectors specifying data and binning information, respectively.

x = "ExpressionSet", y = "missing"

Handle input of an object of class ExpressionSet. Derive both data and binning information from a single object.

x = "ExpressionSet", y = "vector"

Handle input of an object of class ExpressionSet. Derive data from this class but use binning information from a vector input.

x = "ExpressionSet", y = "ExpressionSet"

Handle input of two objects of class ExpressionSet. Derive data and binning information from each one, respectively.

Author(s)

Reid F. Thompson ([e-mail])

See Also

quantileNormalize

HELP documentation built on Nov. 8, 2020, 11:08 p.m.