Author

Suluxan Mohanraj

University Health Network

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 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:scRNA-seq· 3 Approach:statistical model· 2 Research Focus:batch correction / integration· 1 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Trevor J. PughiD· 3 shared Danielle C. CroucheriD· 2 shared J. Javier Díaz-MejíaiD· 2 shared Laura M. RichardsiD· 2 shared Alaina Mahalanabis· 1 shared Alaine Naidas· 1 shared Arash NabbiiD· 1 shared Arun K RamaniiD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersBioinformatics

Trevor J. PughORCID

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3 papers

Recent·Most cited

Immunogenomic profiling of circulating T cells in pediatric cancer patients during standard-of-care

Arash Nabbi, Yiyue Jiang, Osvaldo Espin‐Garcia, Suluxan Mohanraj, Stephanie Pedersen, Johanna Regala, Lauren M. Vernau, Jessica Perazzelli, David Maxwell Barrett, Trevor J. Pugh

The paper assesses T-cell dynamics in pediatric cancer patients during treatment, finding that immune checkpoint proteins and T-cell subsets change with therapy, and introduces a Dynamic Immunogenomic Score to predict relapse risk.

bioRxiv · Jan 10, 2025 · PreprintCancer Biology

A comparison of data integration methods for single-cell RNA sequencing of cancer samples

Laura M. Richards, Mazdak Riverin, Suluxan Mohanraj, Shamini Ayyadhury, Danielle C. Croucher, J. Javier Díaz-Mejía, Fiona J. Coutinho, Peter B. Dirks, Trevor J. Pugh

This study compares five data integration methods for single-cell RNA sequencing of cancer samples, finding STACAS and fastMNN most effective in correcting batch effects while preserving biological variability.

bioRxiv · Aug 4, 2021 · PreprintBioinformatics

CReSCENT: CanceR Single Cell ExpressioN Toolkit

Suluxan Mohanraj, J. Javier Díaz-Mejía, Martin D. Pham, Hillary Elrick, Mia Husić, Shaikh Rashid, Ping Luo, Prabnur Bal, Kevin Lu, Samarth Siddharth Patel, Alaina Mahalanabis, Alaine Naidas, Erik Christensen, Danielle C. Croucher, Laura M. Richards, , Trevor J. Pugh

CReSCENT provides a web-based toolkit for analyzing scRNA-seq data in cancer research, offering preconfigured pipelines and user-editable workflows for non-experts.

Nucleic Acids Research · May 13, 2020Peer-reviewedBioinformatics