IsoCor: isotope correction for high-resolution MS labeling experiments

Author:

Millard Pierre1ORCID,Delépine Baudoin1ORCID,Guionnet Matthieu12ORCID,Heuillet Maud12ORCID,Bellvert Floriant12ORCID,Létisse Fabien1ORCID

Affiliation:

1. LISBP, Université de Toulouse, CNRS, INRA, INSA, Toulouse 31077, France

2. MetaToul-MetaboHUB, National Infrastructure of Metabolomics and Fluxomics, Toulouse, France

Abstract

Abstract Summary Mass spectrometry (MS) is widely used for isotopic studies of metabolism and other (bio)chemical processes. Quantitative applications in systems and synthetic biology require to correct the raw MS data for the contribution of naturally occurring isotopes. Several tools are available to correct low-resolution MS data, and recent developments made substantial improvements by introducing resolution-dependent correction methods, hence opening the way to the correction of high-resolution MS (HRMS) data. Nevertheless, current HRMS correction methods partly fail to determine which isotopic species are resolved from the tracer isotopologues and should thus be corrected. We present an updated version of our isotope correction software (IsoCor) with a novel correction algorithm which ensures to accurately exploit any chemical species with any isotopic tracer, at any MS resolution. IsoCor v2 also includes a novel graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. Availability and implementation IsoCor v2 is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/IsoCor/ and https://isocor.readthedocs.io/.

Funder

French National Research Agency

ENZINVIVO

European Union

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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