Author

Brianna Xu

University of British Columbia

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Research Focus:database / resource· 2 Organism:human· 2 Organism:mouse· 2 Assay:scRNA-seq· 2 Approach:benchmark study· 1

Frequent Co-Authors

Paul PavlidisiD· 3 shared Sanja RogićiD· 2 shared Xinrui Xiang Yu· 2 shared Alexander M. MoriniD· 1 shared Alexandra N. Millett· 1 shared Anna Xiao· 1 shared Burak Ogan MancarciiD· 1 shared Carlton Yan· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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3 shared papersBioinformatics

Paul PavlidisORCID

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Author profile →

3 papers

Recent·Most cited

Persistent hindrances to data re-use in single-cell genomics

Sanja Rogić, Xinrui Xiang Yu, Brianna Xu, Alexandra N. Millett, Salva Sherif, Guillaume Poirier‐Morency, Rachel S. Schwartz, Paul Pavlidis

The paper assesses challenges in reusing scRNA-seq data from GEO, finding that only ~40% provide usable processed data and <10% include cell-type annotations.

Scientific Data · Jun 24, 2026Peer-reviewedGenomics

Evaluation of analysis modes for RNA coexpression in single-cell and bulk tissue

Eric Ching-Pan Chu, Nairuz Elazzabi, Jules Garreau, Brianna Xu, Xinrui Xiang Yu, Alexander M. Morin, Paul Pavlidis

This study evaluates coexpression analysis methods in single-cell and bulk data, finding that xCell provides more replicable and biologically interpretable results than other modes.

bioRxiv · Jun 19, 2026 · PreprintBioinformatics

Application of large language models to the annotation of cell lines and mouse strains in genomics data

Sanja Rogić, Burak Ogan Mancarci, Brianna Xu, Anna Xiao, Carlton Yan, Paul Pavlidis

This paper evaluates using GPT-4o to annotate mouse strains and cell lines in genomics data, achieving 77% and 59% accuracy, and identifies manual curation errors.

Database · Jan 1, 2026Peer-reviewedBioinformatics