w4m_filter_no_imputation: Do not impute missing intensities to zero for W4M data...

Description Usage Arguments Value Author(s) See Also Examples

View source: R/ClassFilter.R

Description

Substitute zero for negative intensity values in W4M data matrix, but not for missing intensity values

Usage

1

Arguments

m

matrix: W4M data matrix potentially containing negative values

Value

matrix: input data matrix with zeros substituted for negative values

Author(s)

Art Eschenlauer, esch0041@umn.edu

See Also

https://github.com/HegemanLab/w4mclassfilter

http://workflow4metabolomics.org/

Examples

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# input contains negative and missing values
my_input <- matrix(c(NA,1,-1,2), ncol = 2, nrow = 2)

# expected output converts negative and missing values to zero
my_expected <- matrix(c(NA,1,0,2), ncol = 2, nrow = 2)

# run the imputation method to generate actual output
my_output <- w4m_filter_no_imputation(my_input)

# validate actual output against expected output
all.equal(my_output, my_expected, check.attributes = FALSE)

HegemanLab/w4mclassfilter documentation built on March 14, 2021, 1:19 a.m.