Model PTM and/or protein data and make adjustments if needed

Source: R/groupComparisonPTM.R

Takes summarized PTM and protein data from proteinSummarization. If protein data is unavailable, PTM data only can be passed into the function. Including protein data allows for adjusting PTM Fold Change by the change in protein abundance without modification. MSstatsContrastMatrix

groupComparisonPTM(
  data,
  data.type,
  contrast.matrix = "pairwise",
  moderated = FALSE,
  adj.method = "BH",
  log_base = 2,
  use_log_file = TRUE,
  append = FALSE,
  verbose = TRUE,
  log_file_path = NULL,
  base = "MSstatsPTM_log_"
)

Arguments

data

list of summarized datasets. Output of MSstatsPTM summarization function dataSummarizationPTM or dataSummarizationPTM_TMT depending on acquisition type.
data.type

string indicating experimental acquisition type. "TMT" is used for TMT labeled experiments. For all other experiments (Label Free/ DDA/ DIA) use "LabelFree".
contrast.matrix

comparison between conditions of interests. Default models full pairwise comparison between all conditions
moderated

For TMT experiments only. TRUE will moderate t statistic; FALSE (default) uses ordinary t statistic. Default is FALSE.
adj.method

For TMT experiemnts only. Adjusted method for multiple comparison. "BH" is default. "BH" is used for all other experiment types
log_base

For non-TMT experiments only. The base of the logarithm used in summarization.
use_log_file

logical. If TRUE, information about data processing will be saved to a file.
append

logical. If TRUE, information about data processing will be added to an existing log file.
verbose

logical. If TRUE, information about data processing will be printed to the console.
log_file_path

character. Path to a file to which information about data processing will be saved. If not provided, such a file will be created automatically. If append = TRUE, has to be a valid path to a file.
base

start of the file name.

Value

list of modeling results. Includes PTM, PROTEIN, and ADJUSTED data.tables with their corresponding model results.

Examples


model.lf.msstatsptm <- groupComparisonPTM(summary.data, 
                                     data.type = "LabelFree",
                                     verbose = FALSE)

#> Starting PTM modeling...
#> 
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#> Starting Protein modeling...
#> 
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#> Starting adjustment...