Export the quantitative data from an tidyproteomics data-object

export_quant() returns the main quantitative data object as a tibble with identifier as the designation for the measured observation.

Usage

export_quant(
  data = NULL,
  file_name = NULL,
  raw_data = TRUE,
  normalized = FALSE,
  scaled = c("none", "between", "proportion")
)

Arguments

data

tidyproteomics data object

file_name

character string vector

raw_data

a boolean

normalized

a boolean

scaled

a boolean

Value

a tibble

Examples

library(dplyr, warn.conflicts = FALSE)
library(tidyproteomics)
hela_proteins %>%
   normalize(.method = "loess") %>%
   export_quant(file_name = "hela_quant_data.xlsx", normalized = "loess")
#> ℹ Normalizing quantitative data
#> ℹ ... using loess regression
#> ✔ ... using loess regression [1.2s]
#> 
#> ℹ Selecting best normalization method
#> ✔ Selecting best normalization method ... done
#> 
#> ℹ  ... selected loess