Python API

The Python API enables maximum flexibility using crema.

Read PSMs easily using the read_tide() or read_mztab() functions for files in the Tide tab-delimited format or mzTab format, respectively. Alternatively, more generic tab delimited files can be read using the read_txt().

Once read, a collection of PSMs is stored in a PsmDataset object. Calling the assign_confidence() function will calculate confidence estimates for the respective psm data using the specified confidence estimate method.

This will produce a confidence object that stores the calculated confidence estimates via false discovery rates (FDR) and q-values. Results stored in a confidence object can be exported by calling the to_txt() function.

Functions

Primary Functions

assign_confidence

Assign confidence estimates to a collection of peptide-spectrum matches.

Parsers

`read_tide`	Read peptide-spectrum matches (PSMs) from Tide tab-delimited files.
`read_msamanda`	Read peptide-spectrum matches (PSMs) from MSAmanda tab-delimited files.
`read_msfragger`	Read peptide-spectrum matches (PSMs) from MSFragger pepXML files.
`read_msgf`	Read peptide-spectrum matches (PSMs) from MSGF+ tab-delimited files.
`read_pepxml`	Read peptide-spectrum matches (PSMs) from pepXML files.
`read_mztab`	Read peptide-spectrum matches (PSMs) from mzTab files.
`read_txt`	Read peptide-spectrum matches (PSMs) from delimited text files.

Writers

to_txt

Save confidence estimates to delimited text files.

Dataset

PsmDataset

Store a collection of peptide-spectrum matches (PSMs).

Confidence

Confidence

Estimate statistical confidence estimates for a collection of PSMs.