norm_based_on_proteomics_maxquant: Normalizaiton for phosphoproteomics data from MaxQuant based...

In ecnuzdd/PhosMap: A Comprehensive R Package For Analyzing Quantitative Phosphoproteomics Data

Normalizaiton for phosphoproteomics data from MaxQuant based on proteomics data

Description

Normalizaiton for phosphoproteomics data from MaxQuant based on proteomics data

Usage

norm_based_on_proteomics_maxquant(
  summary_phos_norm,
  proteomics_data,
  experiment_code_file_path,
  proteomics_experiment_file_path,
  intensity_type = "Intensity",
  min_unique_peptide = 1,
  max_na_num = 2,
  norm_method = "global",
  impute_method = "minimum/10"
)

Arguments

summary_phos_norm	A data frame containing information required for all analysis.
proteomics_data	A data frame of proteinGroups.txt.
experiment_code_file_path	Experiment code file path for phosphoproteomics.
proteomics_experiment_file_path	Experiment code file path for proteomics.
intensity_type	Intensity type. The default is 'Intensity' and the options are 'iBAQ' and 'LFQ.intensity',depending on proteinGroups.txt.
min_unique_peptide	Threshold for MaxQuant unique peptide[proteinGroups.txt]. The default is 1.
max_na_num	Threshold for the number of missing values[proteinGroups.txt]. The default is 2.
norm_method	Normalizaiton method[proteinGroups.txt]. The default is 'global' and the options are 'global' and 'median'.
impute_method	Imputation method[proteinGroups.txt]. The default is 'minimum/10',the options are '0', 'minimum' and 'minimum/10'.

Value

A result list. Elements are a data frame containing information required for all analysis and a pre-processed proteomics data.

Examples

## Read phosphoproteomics data
## Not run: 
rawdata <- read.csv("Phospho (STY)Sites.txt",header=T,sep='\t')

## Quality control for phosphoproteomics data 
qc_results <- qc_maxquant(rawdata, "./experiment_code_file.txt", min_score = 40, min_loc_prob = 0.75, max_na_num = 2)
qc_result <- qc_results[[1]]
qc_result_for_motifanalysis <- qc_results[[2]]

## Normalizaiton, imputation and filtering
summary_phos_norm <- norm_maxquant(qc_result, qc_result_for_motifanalysis, norm_method = "global", impute_method = "minimum/10", top = 0.9)

## Read proteomics data
proteomics_data <- read.csv("./proteinGroups.txt", sep = "\t")

results <- norm_based_on_proteomics(summary_phos_norm, proteomics_data, "./phosphorylation_exp_design_info.txt", "./phosphorylation_exp_design_info.txt")
summary_phos_norm_based_on_pro <- results[[1]]
pro_norm <- results[[2]]

## End(Not run)

ecnuzdd/PhosMap documentation built on Dec. 7, 2022, 4:09 a.m.