cortado is a Python package that implements various methods to estimate false discovery rates (FDR) in extreme-scale mass spectrometry proteomics experiments. cortado is focused on gathering and reducing datasets to enable applying efficient implementations to estimate FDR. An additional focus is supporting peptide-centric searching through the "mixture-maximum" (MixMax) approach, which also supports spectrum-centric searches.
Cortado is designed to be easy-to-use and flexible. Currently the following modes are supported:
- Global PSM FDR
- Global peptide or precursor FDR
- MixMax q-value estimation
- Protein scoring by rolling up PSM scores
- Protein q-value estimation
Installation
cortado requires Python 3.8+ and can be installed with pip:
pip install cortado-ms
Basic Usage
Using cortado requires that you collect a dataset of PSMs, which can easily be
accomplished with the
wheely-mammoth library, which is
installed when you install cortado-ms:
>>> from wheely.mammoth.parsers import read_encyclopedia_features
>>> ds = read_encyclopedia_features("data/*.features.txt")
You can then compute q-values using the assign_confidence function:
>>> from cortado import assign_confidence
>>> conf = assign_confidence(ds, "primary", desc=False)
>>> print(f"pi0={100*conf.pi0:.2f}%")
pi0=36.74%
>>> conf.data.toPandas()[["primary", "sequence", "q-value"]]
primary sequence q-value
0 43.783160 -.LSLEGDHSTPPSAYGSVK.- 0.000000
1 41.212322 -.NGPLEVAGAAVSAGHGLPAK.- 0.000000
2 36.081665 -.IMDPNIVGSEHYDVAR.- 0.000000
3 34.730186 -.TTHYTPLAC[+57.0214635]GSNPLKR.- 0.000000
4 34.666630 -.SGPKPFSAPKPQTSPSPK.- 0.000000
.. ... ... ...
827 8.150498 -.FGVEQDRMDK.- 0.414025
828 8.065474 -.QYYYSADGSR.- 0.416572
829 8.028464 -.APHDFQFVQK.- 0.416572
830 7.946067 -.KLYEDAQMAR.- 0.417337
831 7.632076 -.LTC[+57.0214635]PC[+57.0214635]C[+57.0214635... 0.420368
[832 rows x 3 columns]
1 maintainer
Metadata
1 maintainer
Release files for cortado-ms 0.16.3
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