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deTELpy: Python package for high-throughput detection of amino acid substitutions in mass spectrometry datasets.

Authors :
Landerer, Cedric
Scheremetjew, Maxim
Moon, HongKee
Hersemann, Lena
Toth-Petroczy, Agnes
Source :
Bioinformatics. Jul2024, Vol. 40 Issue 7, p1-5. 5p.
Publication Year :
2024

Abstract

Motivation Errors in the processing of genetic information during protein synthesis can lead to phenotypic mutations, such as amino acid substitutions, e.g. by transcription or translation errors. While genetic mutations can be readily identified using DNA sequencing, and mutations due to transcription errors by RNA sequencing, translation errors can only be identified proteome-wide using mass spectrometry. Results Here, we provide a Python package implementation of a high-throughput pipeline to detect amino acid substitutions in mass spectrometry datasets. Our tools enable users to process hundreds of mass spectrometry datasets in batch mode to detect amino acid substitutions and calculate codon-specific and site-specific translation error rates. deTELpy will facilitate the systematic understanding of amino acid misincorporation rates (translation error rates), and the inference of error models across organisms and under stress conditions, such as drug treatment or disease conditions. Availability and implementation deTELpy is implemented in Python 3 and is freely available with detailed documentation and practical examples at https://git.mpi-cbg.de/tothpetroczylab/detelpy and https://pypi.org/project/deTELpy/ and can be easily installed via pip install deTELpy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13674803
Volume :
40
Issue :
7
Database :
Academic Search Index
Journal :
Bioinformatics
Publication Type :
Academic Journal
Accession number :
178887786
Full Text :
https://doi.org/10.1093/bioinformatics/btae424