resamplescale: A function to create an attribute or column for each sample...

In normfluodbf: Cleans and Normalizes FLUOstar DBF and DAT Files from 'Liposome' Flux Assays

A function to create an attribute or column for each sample loaded into the microplate wells.

Description

Creates a data frame where each sample loaded into the microplate wells has a separate attribute.

Creates a data frame where each sample loaded into the microplate wells has a separate attribute. NA values are retained for more control.

A function that takes tuples or rows consisting of several samples and perform a putative resampling to yield another data frame with a separate attribute for each sample.

A function that takes tuples or rows consisting of several samples and perform a putative resampling to yield another data frame with a separate attribute for each sample. NA values are retained.

A function that takes tuples or rows consisting of several samples and perform a putative resampling to yield another data frame with a separate attribute for each sample.

A function that takes tuples or rows consisting of several samples and perform a putative resampling to yield another data frame with a separate attribute for each sample.

Creates a data frame where each sample loaded into the microplate wells has a separate attribute.

Creates a data frame where each sample loaded into the microplate wells has a separate attribute. NA values are retained.

Creates a data frame where each sample loaded into the microplate wells has a separate attribute.

Creates a data frame where each sample loaded into the microplate wells has a separate attribute.

Usage

resample_dat_scale(df, tnp, cycles)

resample_dat_scale_naretainer(df, tnp, cycles)

resample_dat_scale_alt(df, tnp, cycles, na_omit = NULL)

resample_dat_scale_alt_na(df, tnp, cycles)

resample_dat_scale_alt_bf_na(df, tnp, cycles)

resample_dat_scale_alt_bfv(df, tnp, cycles)

resample_dat_scale_optimus(df, tnp, cycles)

resample_dat_scale_optimus_na(df, tnp, cycles)

resample_dat_scale_optimus_backend(df, tnp, cycles, na_omit = NULL)

resample_vect_scale(df, tnp, cycles, method = c("normal", "brute", "vector"))

Arguments

df	A clean data frame with attributes or tuples containing a mixture of samples.
tnp	A numeric value indicating the number of rows used. TNP is used as an acronym for Test, Negative, Positive.
cycles	A numeric value indicating the number of cycles selected by the user when running the FLUOstar instrument.
na_omit	Takes a string "yes" OR "no".
method	A string 'normal', 'brute' or 'vector' to specify the method of resampling.

Value

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

A new data frame where separated samples are assigned a separate attribute or column.

Note

This function builds on or scales-up @seealso resample_dat(), hence the suffix scale. This function is less optimized than @seealso resample_dat_scale_optimus().

This function builds on or scales-up @seealso resample_dat(), hence the suffix scale. This function is less optimized than @seealso resample_dat_scale_optimus().

This function builds on or scales-up @seealso resample_dat(), hence the suffix scale. This function is more optimized than @seealso resample_dat_scale(), hence the suffix scale_optimus.

This function builds on or scales-up @seealso resample_dat(), hence the suffix scale. This function is more optimized than @seealso resample_dat_scale(), hence the suffix scale_optimus.

This function builds on or scales-up @seealso resample_dat(), hence the suffix scale. This function is more optimized than @seealso resample_dat_scale(), hence the suffix scale_optimus.

This is the pseudo-vectorized approach and should be a more efficient function. This function will produce a vertical layout as defined in this package. This function inspired by the lapply approach pretty much applies the

Author(s)

Tingwei Adeck

See Also

resample_dat()

resample_dat()

resample_dat_alt()

resample_dat_alt()

resample_dat_alt(), resample_dat_scale_alt()

resample_dat_alt(), resample_dat_scale_alt()

resample_dat()

resample_dat()

resample_dat()

resample_dat_vect()

resample_dat_vect(). As a matter of fact, I took this approach to create compatibility with lapply and rapply but that failed.

Examples

## Not run: 
fpath <- system.file("extdata", "dat_4.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_4.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_naretainer(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_1.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_alt(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_1.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_alt_na(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_4.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_alt_bf_na(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_4.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_alt_bfv(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_1.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_optimus(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_1.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_optimus_na(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_1.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
resampled_scaled <- resample_dat_scale_optimus_backend(nocomma_dat, tnp=3, cycles=40)
## End(Not run)
## Not run: 
fpath <- system.file("extdata", "dat_3.dat", package = "normfluodbf", mustWork = TRUE)
dat_df <- read.table(file=fpath)
nocomma_dat <- clean_odddat_optimus(dat_df)
alt_test_scale <- resample_vect_scale(nocomma_dat,3,40, method = 'brute')
alt_test_scale <- resample_vect_scale(nocomma_dat,3,40, method = 'normal')
alt_test_scale <- resample_vect_scale(nocomma_dat,3,40, method = 'vector')
alt_test_scale_norm <- lapply(alt_test_scale, min_max_norm)
## End(Not run)

normfluodbf documentation built on Sept. 28, 2024, 1:06 a.m.