norm_maxquant: Normalizaiton, imputation and filtering for phosphoproteomics...

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

Normalizaiton, imputation and filtering for phosphoproteomics data from MaxQuant.

Description

Normalizaiton, imputation and filtering for phosphoproteomics data from MaxQuant.

Usage

norm_maxquant(
  qc_result,
  qc_result_for_motifanalysis,
  norm_method = "global",
  impute_method = "minimum/10",
  percent_of_kept_sites = 3/4
)

Arguments

qc_result	A data frame containing quality control result.
qc_result_for_motifanalysis	A data frame containing information required for motif analysis.
norm_method	Normalizaiton method. The default is 'global' and the options are 'global' and 'median'.
impute_method	Imputation method. The default is 'minimum/10' and the options are '0', 'minimum' and 'minimum/10'.
percent_of_kept_sites	A numeric value representing a cutoff used for filter psites. The default is 3/4.

Value

A data frame containing information required for all analysis.

Examples

## 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]]

summary_phos_norm <- norm_maxquant(qc_result, qc_result_for_motifanalysis, norm_method = "global", impute_method = "minimum/10", top = 0.9)

## End(Not run)

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