View source: R/dataProcessPTM.R
dataProcessPTM | R Documentation |
Function to perform data processing and summarization on an experiment targeting post-translational modifications. Performs normalization, missing value imputation, feature selection, and summarization. Can optionally take an additional global protein quantification experiment for protein-level correction of PTM changes. Can take either label free or tandem mass tag (TMT) labeled data.
dataProcessPTM(
data,
ptm_label_type,
protein_label_type,
MBimpute_ptm = FALSE,
MBimpute_protein = TRUE,
use_log_file = TRUE,
append = FALSE,
verbose = TRUE,
log_file_path = NULL,
...
)
data |
Name of the output of MSstatsPTM converter function or peptide-level quantified data from other tools. It should be a list containing one or two data tables, named PTM and PROTEIN for modified and unmodified datasets. The list must at least contain the PTM dataset, however the PROTEIN dataset is optional. |
ptm_label_type |
Indicator of labeling type for PTM dataset. Must be one of
|
protein_label_type |
Indicator of labeling type for PROTEIN dataset. Must be
one of |
MBimpute_ptm |
Missing value imputation on the feature-level for the PTM dataset. TRUE (default) imputes missing values by Accelated failure model. FALSE uses minimum value to impute the missing value for each peptide precursor ion. |
MBimpute_protein |
Missing value imputation on the feature-level for the PROTEIN dataset. TRUE (default) imputes missing values by Accelated failure model. FALSE uses minimum value to impute the missing value for each peptide precursor ion. |
... |
Additional parameters passed to either the
dataProcess function from |
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