msmu.pp.to_peptide

Summarise PSM-level data to peptide-level data.

Usage

mdata = mm.pp.to_peptide( mdata, agg_method="median", purity_threshold=0.7, calculate_q=True, )

Parameters:

Name	Type	Description	Default
mdata	MuData	MuData object containing PSM-level data.	required
layer	str | None	Layer to use for quantification aggregation. If None, the default layer (.X) will be used. Defaults to None.	None
agg_method	Literal['median', 'mean', 'sum']	Aggregation method for quantification to use. Defaults to "median".	'median'
purity_threshold	float | None	Purity threshold for TMT data quantification aggregation (does not filter out features). If None, no filtering is applied. Defaults to 0.7.	0.7
top_n	int | None	Number of top features to consider for summarisation. If None, all features are used. Defaults to None.	None
rank_method	Literal['median_intensity', 'total_intensity', 'max_intensity', 'mean_intensity']	Method to rank features when selecting top_n. Defaults to "median_intensity".	'median_intensity'
calculate_q	bool	Whether to calculate q-values. Defaults to True.	True

Returns:

Type	Description
MuData	MuData object containing peptide-level data.