Author

Daniel M. Bader

Technical University of MunichORCID 0000-0003-1875-6044Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:database / resource· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Christian MertesiD· 2 shared Holger ProkischiD· 2 shared Julien GagneuriD· 2 shared Agnė Matusevičiūtė· 1 shared Agnès RötigiD· 1 shared Alice Donati· 1 shared Anne LombèsiD· 1 shared Arcangela IusoiD· 1 shared

Activity by Year

2017-2018 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersBioinformatics

Christian MertesORCID

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2 papers

Recent·Most cited

OUTRIDER: A statistical method for detecting aberrantly expressed genes in RNA sequencing data

Felix Brechtmann, Christian Mertes, Agnė Matusevičiūtė, Vicente A. Yépez, Žiga Avsec, Maximilian Herzog, Daniel M. Bader, Holger Prokisch, Julien Gagneur

OUTRIDER detects aberrantly expressed genes in RNA-seq data by modeling co-variation and using significance-based thresholds to identify outliers.

The American Journal of Human Genetics · Nov 29, 2018Peer-reviewedBioinformatics

Genetic diagnosis of Mendelian disorders via RNA sequencing

Laura Sophie Kremer, Daniel M. Bader, Christian Mertes, Robert Kopajtich, Garwin Pichler, Arcangela Iuso, Tobias B. Haack, Elisabeth Graf, Thomas Schwarzmayr, Caterina Terrile, Eliška Koňaříková, Birgit M. Repp, Gabi Kastenmüller, Jerzy Adamski, Peter Lichtner, , Holger Prokisch

This study uses RNA sequencing to identify genetic diagnoses in mitochondrial disease patients by detecting aberrant gene expression and splicing events.

Nature Communications · Jun 12, 2017Peer-reviewedGenetics