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

Author:

Landerer Cedric12,Scheremetjew Maxim12,Moon HongKee12ORCID,Hersemann Lena12,Toth-Petroczy Agnes123ORCID

Affiliation:

1. Max Planck Institute of Molecular Cell Biology and Genetics , 01307 Dresden, Germany

2. Center for Systems Biology Dresden , 01307 Dresden, Germany

3. Cluster of Excellence Physics of Life, TU Dresden , 01062 Dresden, Germany

Abstract

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.

Funder

Max Planck Gesellschaft

Publisher

Oxford University Press (OUP)

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