MSstatsPrepareForSummarizationTMT: Prepare output of MSstatsTMT converters for protein-level...

View source: R/proteinSummarization.R

MSstatsPrepareForSummarizationTMTR Documentation

Prepare output of MSstatsTMT converters for protein-level summarization

Description

Prepare output of MSstatsTMT converters for protein-level summarization

Usage

MSstatsPrepareForSummarizationTMT(
  data,
  method,
  global_norm,
  reference_norm,
  remove_norm_channel,
  remove_empty_channel,
  MBimpute,
  maxQuantileforCensored
)

Arguments

data

Name of the output of PDtoMSstatsTMTFormat function or peptide-level quantified data from other tools. It should have columns ProteinName, PeptideSequence, Charge, PSM, Mixture, TechRepMixture, Run, Channel, Condition, BioReplicate, Intensity

method

Four different summarization methods to protein-level can be performed : "msstats"(default), "MedianPolish", "Median", "LogSum".

global_norm

Global median normalization on peptide level data (equalizing the medians across all the channels and MS runs). Default is TRUE. It will be performed before protein-level summarization.

reference_norm

Reference channel based normalization between MS runs on protein level data. TRUE(default) needs at least one reference channel in each MS run, annotated by 'Norm' in Condtion column. It will be performed after protein-level summarization. FALSE will not perform this normalization step. If data only has one run, then reference_norm=FALSE.

remove_norm_channel

TRUE(default) removes 'Norm' channels from protein level data.

remove_empty_channel

TRUE(default) removes 'Empty' channels from protein level data.

MBimpute

only for method="msstats". TRUE (default) imputes missing values by Accelated failure model. FALSE uses minimum value to impute the missing value for each peptide precursor ion.

maxQuantileforCensored

We assume missing values are censored. maxQuantileforCensored is Maximum quantile for deciding censored missing value, for instance, 0.999. Default is Null.

Value

data.table


Vitek-Lab/MSstatsTMT documentation built on Nov. 18, 2024, 11:30 a.m.