Author

Valeh Valiollah Pour Amiri

University of California, BerkeleyORCID 0000-0002-2008-5297Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Research Focus:dimensionality reduction· 2 Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1

Frequent Co-Authors

Aaron StreetsiD· 2 shared Adam GayosoiD· 2 shared Nir YosefiD· 2 shared Achille NazaretiD· 1 shared Aditi GnanasekariD· 1 shared Brooke E. HowittiD· 1 shared Can ErgeniD· 1 shared Carlos N. Talavera-LópeziD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Aaron StreetsORCID

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Author profile →

3 papers

Recent·Most cited

scAmp analyzes focal gene amplifications at single-cell resolution

Matthew G. Jones, Natasha E. Weiser, King L. Hung, Xiaowei Yan, Sangya Agarwal, Jens Luebeck, Aditi Gnanasekar, Brooke E. Howitt, Ellis J. Curtis, Kevin Yu, John C. Rose, Katerina Kraft, Valeh Valiollah Pour Amiri, Leena Satpathy, Vineet Bafna, , Howard Y. Chang

scAmp detects and analyzes ecDNA at single-cell resolution, showing its impact on chromatin accessibility in cancer cells.

bioRxiv · Feb 15, 2026 · PreprintCancer Biology

Scvi-hub: an actionable repository for model-driven single cell analysis

Can Ergen, Valeh Valiollah Pour Amiri, Martin Kim, Ori Kronfeld, Aaron Streets, Adam Gayoso, Nir Yosef

Scvi-hub provides a platform for sharing and analyzing single-cell omics datasets using pre-trained models, enabling efficient tasks like visualization and annotation with reduced computational demands.

Nature Methods · Sep 1, 2025Peer-reviewedBioinformatics

scvi-tools: a library for deep probabilistic analysis of single-cell omics data

Adam Gayoso, Romain Lopez, Galen K. Xing, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong, Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, Yining Liu, Jules Samaran, Gabriel Misrachi, Achille Nazaret, Oscar Clivio, , Nir Yosef

scvi-tools provides a Python package for probabilistic analysis of single-cell omics data, offering standardized interfaces and extensible tools for various analysis tasks.

Nature Biotechnology · Feb 1, 2022Peer-reviewedBioinformatics