make_feature_from_expression: Create a feature vector from expression data

Description Usage Arguments Value

View source: R/make_feature_from_expression.R

Description

Convert a gene or protein expression matrix into a feature vector that matches the dimensions of a data frame used as input to a classifier, such as a naive Bayes, random forests, or support vector machine classifier, by calculating the correlation between each pair of genes or proteins.

Usage

1
make_feature_from_expression(expr, dat, node_columns = c(1, 2), ...)

Arguments

expr

a matrix containing gene or protein expression data, with genes/proteins in columns and samples in rows

dat

the data frame of features to be used by the classifier, with protein pairs in the columns specified by the node_columns argument

node_columns

a vector of length two, denoting either the indices (integer vector) or column names (character vector) of the columns within the data frame containing the nodes participating in pairwise interactions; defaults to the first two columns of the data frame (c(1, 2))

...

arguments passed to cor

Value

a vector matching the dimensions and order of the feature data frame, to use as input for a classifier in interaction prediction


fosterlab/PrInCE documentation built on Dec. 13, 2020, 5:50 a.m.