MSstatsSummarizeWithMultipleCores: Feature-level data summarization with multiple cores

View source: R/dataProcess.R

MSstatsSummarizeWithMultipleCoresR Documentation

Feature-level data summarization with multiple cores

Description

Feature-level data summarization with multiple cores

Usage

MSstatsSummarizeWithMultipleCores(
  input,
  method,
  impute,
  censored_symbol,
  remove50missing,
  equal_variance,
  numberOfCores = 1
)

Arguments

input

feature-level data processed by dataProcess subfunctions

method

summarization method: "linear" or "TMP"

impute

only for summaryMethod = "TMP" and censoredInt = 'NA' or '0'. TRUE (default) imputes 'NA' or '0' (depending on censoredInt option) by Accelated failure model. FALSE uses the values assigned by cutoffCensored

censored_symbol

Missing values are censored or at random. 'NA' (default) assumes that all 'NA's in 'Intensity' column are censored. '0' uses zero intensities as censored intensity. In this case, NA intensities are missing at random. The output from Skyline should use '0'. Null assumes that all NA intensites are randomly missing.

remove50missing

only for summaryMethod = "TMP". TRUE removes the proteins where every run has at least 50% missing values for each peptide. FALSE is default.

equal_variance

only for summaryMethod = "linear". Default is TRUE. Logical variable for whether the model should account for heterogeneous variation among intensities from different features. Default is TRUE, which assume equal variance among intensities from features. FALSE means that we cannot assume equal variance among intensities from features, then we will account for heterogeneous variation from different features.

numberOfCores

Number of cores for parallel processing. When > 1, a logfile named 'MSstats_dataProcess_log_progress.log' is created to track progress. Only works for Linux & Mac OS. Default is 1.

Value

list of length one with run-level data.


MeenaChoi/MSstats documentation built on July 13, 2024, 10:59 a.m.