Author

Réka Tóth

German Cancer Research CenterORCID 0000-0002-6096-1052Unclaimed ORCID profile · follow to get notified of new preprints

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Signature Assays, Organisms & Methods

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Assay:DNA methylation· 4 Approach:statistical model· 4 Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:deconvolution· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Petr V. NazaroviD· 3 shared Christoph PlassiD· 2 shared Pavlo LutsikiD· 2 shared Aikaterini Spantidaki· 1 shared Alain J. van GooliD· 1 shared Anaïs OudiniD· 1 shared Andreas SchereriD· 1 shared Ann‐Christin HauiD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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3 shared papersBioinformatics

Petr V. NazarovORCID

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Author profile →

4 papers

Recent·Most cited

Integrative multi-omics combined with functional pharmacological profiling in patient-derived organoids identifies personalized therapeutic vulnerabilities of adult high-grade gliomas

Luca Ermini, Anuja Lipsa, Ann‐Christin Hau, Iryna Krokhmal, Bakhtiyor Nosirov, Réka Tóth, Eliane Klein, Anaïs Oudin, Linsey Houben, Sabrina Fritah, Christel C. Herold‐Mende, Katrin B. M. Frauenknecht, Michel Guy André Mittelbronn, Guy Berchem, Frank Hertel, , Anna Golebiewska

This study integrates multi-omics and functional drug screening in patient-derived organoids to identify personalized therapeutic vulnerabilities in adult high-grade gliomas, finding distinct drug responses in IDH1 mutant and MYCN-amplified tumors.

bioRxiv · Sep 9, 2025 · PreprintCancer Biology

Comprehensive multi-omics profiling of a healthy human cohort

Casper de Visser, Anna Niehues, Lukáš Najdekr, Réka Tóth, Petr V. Nazarov, Jana Vrbková, Jarmila Stanková, Sara Ekberg, Elisa Conde, Bishwa R. Ghimire, Bhagwan Yadav, Pirkko Mattila, Maija Puhka, Val F. Lanza, Jolein Gloerich, , Peter A.C. ’t Hoen

The paper presents a comprehensive multi-omics dataset of healthy individuals, revealing sex and age influences and providing reference ranges for omics features.

bioRxiv · Nov 7, 2024 · PreprintBioinformatics

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

Yunhee Jeong, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Réka Tóth, Marlene Ganslmeier, Kersten Breuer, Christoph Plass, Pavlo Lutsik

This study benchmarks six sequencing-based and two array-based cell-type deconvolution methods for bulk DNA methylomes, identifying the best-performing method and factors affecting performance.

Briefings in Bioinformatics · Jul 6, 2022Peer-reviewedBioinformatics

Reference-free deconvolution of complex DNA methylation data - a systematic protocol

Michael Scherer, Petr V. Nazarov, Réka Tóth, Shashwat Sahay, Tony Kaoma, Valentin J. Maurer, Nikita Vedeneev, Christoph Plass, Thomas Lengauer, Jörn Walter, Pavlo Lutsik

This paper introduces a reference-free deconvolution protocol for DNA methylomes to identify hidden cell populations in complex samples, applied to lung cancer data from TCGA.

Nature Protocols · Sep 25, 2020Peer-reviewedBioinformatics