LFQDataTransformer: Decorate LFQData with Methods for transforming Intensities

In wolski/prolfqua: Proteomics Label Free Quantification

Decorate LFQData with Methods for transforming Intensities

Description

Decorate LFQData with Methods for transforming Intensities

Decorate LFQData with Methods for transforming Intensities

Public fields

lfq

LFQData object

Methods

Public methods

• LFQDataTransformer$new()

• LFQDataTransformer$log2()

• LFQDataTransformer$get_scales()

• LFQDataTransformer$robscale()

• LFQDataTransformer$robscale_subset()

• LFQDataTransformer$intensity_array()

• LFQDataTransformer$intensity_matrix()

• LFQDataTransformer$clone()

---

Method new()

initialize

Usage

LFQDataTransformer$new(lfqdata)

Arguments

lfqdata

LFQData object to transform

---

Method log2()

log2 transform data

Usage

LFQDataTransformer$log2(force = FALSE)

Arguments

force

if FALSE, then data already log2 transformed will not be transformed a second time. TRUE force log transformation.

Returns

LFQDataTransformer

---

Method get_scales()

get mean and variance and standard deviation in each sample

Usage

LFQDataTransformer$get_scales()

Returns

list with means and mads

---

Method robscale()

robust scale data

Usage

LFQDataTransformer$robscale(
  preserveMean = TRUE,
  colname = "transformedIntensity"
)

Arguments

preserveMean

should original mean value be preserved TRUE, if FALSE then center at zero

colname

new name of transformed column

Returns

LFQDataTransformer (self)

---

Method robscale_subset()

log2 transform and robust scale data based on subset

Usage

LFQDataTransformer$robscale_subset(
  lfqsubset,
  preserveMean = TRUE,
  colname = "transformedIntensity"
)

Arguments

lfqsubset

LFQData subset to use for normalization

preserveMean

should original mean value be preserved TRUE, if FALSE then center at zero

colname

- how to name the transformed intensities, default transformedIntensity

Returns

LFQDataTransformer (self)

---

Method intensity_array()

Transforms intensities

Usage

LFQDataTransformer$intensity_array(.func = log2, force = FALSE)

Arguments

.func

transformation function working with arrays e.g. log2, log10, asinh etc.

force

transformation on already transformed data.

Returns

LFQDataTransformer (self)

---

Method intensity_matrix()

pass a function which works with matrices, e.g., vsn::justvsn

Usage

LFQDataTransformer$intensity_matrix(.func = robust_scale, force = FALSE)

Arguments

.func

any function taking a matrix and returning a matrix (columns sample, rows feature e.g. base::scale) default robust_scale

force

transformation on data already transformed

Returns

LFQDataTransformer (self)

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LFQDataTransformer$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

istar <- prolfqua_data('data_ionstar')$filtered()
istar$config <- old2new(istar$config)
data <- istar$data |> dplyr::filter(protein_Id %in% sample(protein_Id, 100))
lfqdata <- LFQData$new(data, istar$config)

lfqcopy <- lfqdata$get_copy()
lfqTrans <- lfqcopy$get_Transformer()

x <- lfqTrans$intensity_array(log2)
x$lfq$config$table$is_response_transformed
x <- x$intensity_matrix(robust_scale)
plotter <- x$lfq$get_Plotter()
plotter$intensity_distribution_density()

# transform by asinh root and scale

lfqcopy <- lfqdata$get_copy()
lfqTrans <- lfqcopy$get_Transformer()
x <- lfqTrans$intensity_array(asinh)
mads1 <- mean(x$get_scales()$mads)
x <- lfqTrans$intensity_matrix(robust_scale, force = TRUE)
mads2 <- mean(x$get_scales()$mads)

stopifnot(abs(mads1 - mads2) < 1e-8)


stopifnot(abs(mean(x$get_scales()$medians)) < 1e-8)
lfqcopy <- lfqdata$get_copy()
lfqTrans <- lfqcopy$get_Transformer()
lfqTrans$log2()
before <- lfqTrans$get_scales()
lfqTrans$robscale()
after <- lfqTrans$get_scales()
stopifnot(abs(mean(before$medians) - mean(after$medians)) < 1e-8)
stopifnot(abs(mean(before$mads) - mean(after$mads)) < 1e-8)

# normalize data using vsn
lfqcopy <- lfqdata$get_copy()
lfqTrans <- lfqcopy$get_Transformer()
lfqTransCheck <- lfqcopy$get_Transformer()

lfqTransCheck$log2()
lfqTransCheck$get_scales()
lfqTransCheck$lfq$get_Plotter()$intensity_distribution_density()

if(require("vsn")){
 res <- lfqTrans$intensity_matrix( .func = vsn::justvsn)
 res$lfq$get_Plotter()$intensity_distribution_density()
 res$get_scales()
}
if(require("preprocessCore")){
quant <- function(y){
 ynorm <- preprocessCore::normalize.quantiles(y)
 rownames(ynorm) <- rownames(y)
 colnames(ynorm) <- colnames(y)
 return(ynorm)
}
 res <- lfqTrans$intensity_matrix( .func = quant)
 res$lfq$get_Plotter()$intensity_distribution_density()
}

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.