Author

Stefanie Peschel

Helmholtz MunichORCID 0000-0002-7936-7627Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metagenomics· 4 Approach:statistical model· 4 Research Focus:benchmarking· 2 Research Focus:software / tool· 2 Organism:bacteria (other)· 1 Approach:benchmark study· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Christian L. MülleriD· 4 shared Anne‐Laure BoulesteixiD· 2 shared Aki Samuli HavulinnaiD· 1 shared Ana Rita BrochadoiD· 1 shared Annamaria ZannoniiD· 1 shared Artur SannikoviD· 1 shared Aura RauloiD· 1 shared Benjamín ValderramaiD· 1 shared

Activity by Year

2020-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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4 shared papersBioinformatics

Christian L. MüllerORCID

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Author profile →

4 papers

Recent·Most cited

Orchestrating Microbiome Analysis with Bioconductor

Tuomas Borman, Giulio Benedetti, Geraldson Muluh, Aura Raulo, Benjamín Valderrama, Artur Sannikov, Stefanie Peschel, Yihan Liu, Rasmus Hindström, Katariina M. M. Pärnänen, Christian L. Müller, Aki Samuli Havulinna, Sudarshan Anand Shetty, Marcel Ramos, Domenick J. Braccia, , Leo Lahti

The paper introduces an open-source ecosystem for microbiome data science using Bioconductor, supporting modular workflows for analyzing complex, multi-modal datasets.

bioRxiv · Oct 29, 2025 · PreprintBioinformatics

Statistical end-to-end analysis of large-scale microbial growth data with DGrowthR

Medina Feldl, Roberto Olayo-Alarcón, Martin K. Amstalden, Annamaria Zannoni, Stefanie Peschel, Cynthia Mira Sharma, Ana Rita Brochado, Christian L. Müller

DGrowthR provides a statistical framework for analyzing large-scale microbial growth data, enabling differential growth analysis and discovery of compounds affecting bacterial growth.

bioRxiv · Mar 25, 2025 · PreprintMicrobiology

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering

Theresa Ullmann, Stefanie Peschel, Philipp Finger, Christian L. Müller, Anne‐Laure Boulesteix

This paper quantifies over-optimism in unsupervised microbiome analysis by comparing results from discovery and validation datasets across three tasks.

PLoS Computational Biology · Jan 6, 2023Peer-reviewedBioinformatics

NetCoMi: Network Construction and Comparison for Microbiome Data in R

Stefanie Peschel, Christian L. Müller, Erika von Mutius, Anne‐Laure Boulesteix, Martin Depner

NetCoMi is an R package that provides a unified workflow for constructing, analyzing, and comparing microbial association networks from high-throughput sequencing data.

Briefings in Bioinformatics · Oct 7, 2020Peer-reviewedBioinformatics