Author

Snigdha Agarwal

Chan Zuckerberg Biohub San FranciscoPrimary ORCID profile (0009-0008-7262-5022 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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

Same name, identified by ORCID

Snigdha AgarwaliD1 paper · Carnegie Mellon University

Biology Disciplines

Click to filter author papers

Bioinformatics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Organism:mouse· 2 Assay:scRNA-seq· 2 Research Focus:batch correction / integration· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:contrastive learning· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Kyle AwayaniD· 2 shared Norma F NeffiD· 2 shared Aaron M. KershneriD· 1 shared Aaron McGeeveriD· 1 shared Abhishek MurtiiD· 1 shared Aditi AgrawaliD· 1 shared Ahmad Al‐MoujahediD· 1 shared Ahmad N. NabhaniD· 1 shared

Activity by Year

2022-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Kyle AwayanORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Concordance of MERFISH Spatial Transcriptomics with Bulk and Single-cell RNA Sequencing

Jonathan Liu, Vanessa Tran, Venkata N. P. Vemuri, Ashley Byrne, Michael Borja, Yang Joon Kim, Snigdha Agarwal, Ruofan Wang, Kyle Awayan, Abhishek Murti, Aris Taychameekiatchai, Bruce Wang, George Emanuel, Jiang He, John R. Haliburton, , Norma F Neff

The paper compares MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing in mouse liver and kidney, finding MERFISH provides comparable results and robust cell type identification without needing integration with scRNA-seq atlases.

Life Science Alliance · Dec 16, 2022Peer-reviewedBioinformatics

Adversarial domain translation networks for fast and accurate integration of large-scale atlas-level single-cell datasets

Jia Zhao, Gefei Wang, Jingsi Ming, Zhixiang Lin, Yang Wang, Snigdha Agarwal, Aditi Agrawal, Ahmad Al‐Moujahed, Alina A. Alam, Megan A. Albertelli, Paul Allegakoen, Thomas H. Ambrosi, Jane Antony, Steven E. Artandi, Fabienne Aujard, , Patricia Kim Phuong Nguyen

Portal integrates large-scale single-cell datasets efficiently and accurately by preserving biological variation across samples, platforms, and species.

Nature Computational Science · May 30, 2022Peer-reviewedBioinformatics