Author

Noemi Di Nanni

Novartis Institutes for BioMedical ResearchORCID 0000-0002-6399-321XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 3 Approach:statistical model· 3 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

Ada Sula· 1 shared Alejandro ReyesiD· 1 shared Alessandra MezzelaniiD· 1 shared Alice ChiodiiD· 1 shared Antoine de WeckiD· 1 shared Audrey KauffmanniD· 1 shared Cinzia CocolaiD· 1 shared Daniel J. Ho· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBioinformatics

Ada Sula

Mutual co-authors in cluster

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3 papers

Recent·Most cited

scMuffin: an R package for disentangling solid tumor heterogeneity from single-cell expression data

Valentina Nale, Alice Chiodi, Noemi Di Nanni, Ingrid Cifola, Marco Moscatelli, Cinzia Cocola, Matteo Gnocchi, Eleonora Piscitelli, Ada Sula, Ileana Zucchi, Rolland A. Reinbold, Luciano Milanesi, Alessandra Mezzelani, Paride Pelucchi, Ettore Mosca

scMuffin is an R package that analyzes single-cell expression data to identify tumor heterogeneity, cell identities, and genomic aberrations in solid tumors.

BMC Bioinformatics · Nov 27, 2023Peer-reviewedBioinformatics

TRAWLING: a Transcriptome Reference AWare of spLIciNG events.

Noemi Di Nanni, Alejandro Reyes, Daniel J. Ho, Robert J. Ihry, Audrey Kauffmann, Eric Y. Durand, Antoine de Weck

TRAWLING simplifies aberrant splicing detection by providing a splicing-aware transcriptome reference, improving RNAseq analysis across multiple datasets.

bioRxiv · Dec 3, 2021 · PreprintBioinformatics

Inferring copy number variation from gene expression data: methods, comparisons, and applications to oncology

Joseph Boen, Joel P. Wagner, Noemi Di Nanni

This work infers copy number variations from scRNA-seq data using three methods, compares them statistically, and applies the results to analyze tumor cell subpopulations and heterogeneity.

bioRxiv · Oct 18, 2021 · PreprintBioinformatics