knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  warning = FALSE,
  message = TRUE,
  out.width = "100%"
)

In this version, we just added a new function output_eic(). This can be used to generate peaks in some samples after you run process_data(). For example, you analyzed data, and found some features are very important, so you want to check the peak shapes of them in QC samples, so you can use output_eic() function.


Set work directory


First, you need to set the work directory to the folder which you used to run the process_data() function. For example, in our example for process_Data, we set the work directory in example/POS, so here, we also set work directory in this folder.


Run output_eic()


Then we can run output_eic() function.

library(massprocesser)

output_eic(path = ".", 
           query_sample_name = c("QC_1"), 
           query_peak_name = c("M70T54_POS", "M70T579_POS"),
           polarity = "positive", 
           threads = 4)

Then the peak shape of plots will be outputted in example/POS/Result.


Session information


sessionInfo()


tidymass/massprocesser documentation built on Oct. 8, 2024, 10:32 p.m.