A python package for creating entrapment databases.
overview
pytrapment allows the convenient creation of entrapment databases for proteomic mass spectrometry analysis. Entrapment databases are build by sampling for each protein in the host fasta file an fitting entrapment protein.
pytrapment performs the following steps to minimize the differences between the host and entrapment database.
- remove all entrapment proteins that share a peptide with the host (replace I with L amino acids)
- compute the amino acid composition for each protein in the host and entrapment database
- for each host protein find the nearest neighbor (Euclidean distance) in the composition space
- perform some quality control metrics on the peptides
- save the entrapment fasta file (host + entrapment proteins)
Installation
pytrapment is available on pypi and can be installed via pip install pytrapment
Usage
To use pytrapment, simply call the main program via a command line:
pytrapment -i host.fasta -t trap.fasta -o entrapment_db
Make sure to have the correct paths to the fasta files. The out dir will contain the entrapment fasta and two qc plots for peptide and protein features. The repository contains example files which can be used as follows:
pytrapment -i sample_data/host.fasta -t sample_data/trap.fasta -o sample_data/
The results (qc_plot.png and entrapment_data.fasta) can also be found in the sample_data folder.
Contributors
- Sven Giese
Metadata
Release files for pytrapment 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pytrapment-1.0.1.tar.gz | 24.2 kB | Details |
Release files / pytrapment-1.0.1.tar.gz
| Download URL | pytrapment-1.0.1.tar.gz |
|---|---|
| Size | 24.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6b4c74835d1113c070474ff319a4f0fec9656d197d421abf13724fc4bdc469fd
|
|
BLAKE2b-256 checksum How to use checksums |
3d7aa3e18bbe12751c13c865c0f213389556452d18f12d93d07fca86d55d3498
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.3
|