Preprocessing: pp

Any transformation of the data matrix that is not a tool. Other than tools, preprocessing steps usually don’t return an easily interpretable annotation, but perform a basic transformation on the data matrix.

Basic Preprocessing

pp.calculate_qc_metrics	Calculate quality control metrics.
pp.filter_samples	Filter samples based on number of counts or proteins.
pp.filter_proteins	Filter proteins based on number of counts or samples.
pp.highly_variable_proteins	Identify highly variable proteins.
pp.filter_proteins_per_replicate	Filter proteins based on detection in replicates.
pp.aggregate_proteins	Aggregates protein intensities across samples using a given function.
pp.aggregate_samples	Aggregates sample expression across samples using a given function.
pp.normalize_total	Normalize expression values for each sample to sum to a constant value.
pp.drop_excess_MQ_metadata	Drop excess metadata columns from MaxQuant output.
pp.remove_contaminants	Remove contaminant proteins from the data matrix.
pp.filter_min_consecutive_fractions	Filters for proteins present in at least min_consecutive of specified consecutive fractions.

Enrichment

pp.calculate_enrichment_vs_untagged	Calculates enrichment scores and p-values by comparing tagged samples against untagged controls.
pp.calculate_enrichment_vs_all	Calculates enrichment of each sample against all other samples as the background.

Imputation

pp.impute_gaussian

Impute missing values using a Gaussian distribution.