Author

Miguel Vazquez

Barcelona Supercomputing CenterPrimary ORCID profile (0000-0002-5713-1058 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Miguel VazqueziD1 paper

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Organism:human· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Assay:proteomics· 1 Research Focus:spatial domain detection· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Adam P. Butler· 1 shared Aisha Shah· 1 shared Alba Jimenez-Lupiañez· 1 shared Alex Buchanan· 1 shared Ana C. Ricardo· 1 shared Ana Mijalkovic Lazic· 1 shared André KahlesiD· 1 shared Andy CafferkeyiD· 1 shared

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2017-2026 · peak 1/yr

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10 top collaborators · 22 mutual co-author links

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1 shared paperGenomics

Adam P. Butler

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3 papers

Recent·Most cited

A Principled Statistical Framework for Analyzing Spatial Patterns in Spatially Resolved Multi-Omics

Jinpu Li, Mauminah Raina, Yiqing Wang, Shuai Zeng, Yang Yu, Xiufan Yu, Xiaojie Jin, Yuzhou Chang, Daniel Feliciano, Jonathan Himmelfarb, Ana C. Ricardo, Patrick H. Nachman, Miguel Vazquez, M. Luiza Caramori, Laura Barisoni, , Dong Xu

This paper introduces STORM, a statistical framework for analyzing spatial patterns in multi-omics data, demonstrating reliable performance in detecting spatial structures and supporting study design decisions.

bioRxiv · Aug 10, 2026 · PreprintBioinformatics

rDNAcaller: a fast and robust pipeline to call ribosomal DNA variants

Jose Miguel Ramirez, Winona Oliveros, Raquel García-Pérez, Alba Jimenez-Lupiañez, Aisha Shah, Pablo Perez-Cano, Fairlie Reese, Miguel Vazquez, Marta Melé

The paper introduces rDNAcaller, a pipeline for accurate rDNA variant detection using short-read whole-genome sequencing, achieving 94% precision and identifying 5,607 novel variant positions across human populations.

NAR Genomics and Bioinformatics · Oct 7, 2025Peer-reviewedBioinformatics

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

Christina K. Yung, Brian D. O’Connor, Sergei Yakneen, Junjun Zhang, Kyle Ellrott, Kortine Kleinheinz, Naoki Miyoshi, Keiran M. Raine, Romina Royo, Gordon Saksena, Matthias Schlesner, Solomon I. Shorser, Miguel Vazquez, Joachim Weischenfeldt, Denis Yuen, , Charles L. Short

The paper describes the PCAWG project's large-scale analysis of cancer whole genomes across multiple computing environments, producing validated consensus variants for downstream research.

bioRxiv · Jul 10, 2017 · PreprintGenomics