Jialin Liu

Jialin Liu

Postdoctoral Research Fellow at HHMI & University of Michigan

Posts by Collection

portfolio

CytoSignal Permalink

A machine-learning model for detecting the locations and dynamics of cell-cell signaling at cellular resolution from spatial transcriptomic data.

Published in Nature Genetics (2025).

CytoSimplex Permalink

A tool for quantifying and visualizing current cell fate commitment and future cell potential on a simplex.

Published in Bioinformatics (2025).

LIGER Permalink

A machine-learning model for integrating and analyzing multiple single-cell multi-omic datasets, supporting RNA-seq, ATAC-seq, methylation, and spatial modalities.

Published in Nature Protocols (2020).

TopoVelo Permalink

A deep-learning model for jointly modeling temporal gene expression and spatial cellular dynamics from spatial transcriptomic data.

Published in Nature Biotechnology (2025).

publications

Jointly Defining Cell Types from Multiple Single-Cell Datasets Using LIGER

Published in Nature Protocols, 2020

A comprehensive protocol for using LIGER to jointly define cell types from multiple single-cell datasets through integrative non-negative matrix factorization.

Recommended citation: Liu J*, Gao C*, Sodicoff J, Kozareva V, Macosko EZ, Welch JD. (2020). "Jointly Defining Cell Types from Multiple Single-Cell Datasets Using LIGER." Nature Protocols, 15.11, pp. 3632-3662.
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Iterative Single-Cell Multi-Omic Integration Using Online Learning

Published in Nature Biotechnology, 2021

An online learning approach for iterative integration of single-cell multi-omic datasets using non-negative matrix factorization.

Recommended citation: Gao C, Liu J, Kriebel AR, Preissl S, Luo C, Castanon R, Sandoval J, Rivkin A, Nery JR, Behrens MM, Ecker JR, Ren B, Welch JD. (2021). "Iterative Single-Cell Multi-Omic Integration Using Online Learning." Nature Biotechnology, 39.8, pp. 1000-1007.
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G-CSF Secreted by Mutant IDH1 Glioma Stem Cells Abolishes Myeloid Cell Immunosuppression and Enhances the Efficacy of Immunotherapy

Published in Science Advances, 2021

G-CSF secreted by mutant IDH1 glioma stem cells abolishes myeloid cell immunosuppression and enhances immunotherapy efficacy.

Recommended citation: Alghamri MS, McClellan BL, Avvari RP, Thalla R, Carney S, Hartlage CS, Haase S, Ventosa M, Taher A, Kamran N, Zhang L, Faisal SM, Nunnez FJ, Garcia-Fabiani MB, Al-Holou WN, Orringer D, Hervey-Jumper S, Heth J, Patil PG, Eddy K, Merajver SD, Ulintz PJ, Welch JD, Gao C, Liu J, Nunez G, Hambardzumyan D, Lowenstein PR, Castro MG. (2021). "G-CSF Secreted by Mutant IDH1 Glioma Stem Cells Abolishes Myeloid Cell Immunosuppression." Science Advances, 7.40, eabh3243.
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Bone Marrow Endosteal Stem Cells Dictate Active Osteogenesis and Aggressive Tumorigenesis

Published in Nature Communications, 2023

Identification of bone marrow endosteal stem cells and their role in osteogenesis and tumorigenesis via single-cell multi-omic integrative analysis.

Recommended citation: Matsushita Y*, Liu J*, Chu AKY, Tsutsumi-Arai C, Nagata M, Arai Y, Ono W, Yamamoto K, Saunders TL, Welch JD, Ono N. (2023). "Bone Marrow Endosteal Stem Cells Dictate Active Osteogenesis and Aggressive Tumorigenesis." Nature Communications, 14.1, p. 2383.
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Mapping Cell Fate Transition in Space and Time

Published in RECOMB 2024, 2024

Conference paper on topological velocity inference for mapping cell fate transitions in space and time.

Recommended citation: Gu Y*, Liu J*, Li C, Welch JD. (2024). "Mapping Cell Fate Transition in Space and Time." 28th International Conference on Research in Computational Molecular Biology (RECOMB), 2024.
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CytoSignal Detects Locations and Dynamics of Ligand-Receptor Signaling at Cellular Resolution from Spatial Transcriptomic Data

Published in Nature Genetics (accepted, 2026), 2024

A machine-learning method for detecting the locations and dynamics of ligand-receptor signaling at cellular resolution from spatial transcriptomic data.

Recommended citation: Liu J, Manabe H, Qian W, Wang Y, Gu Y, Chu AKY, Gadhvi G, Song Y, Ono N, Welch JD. (2026). "CytoSignal Detects Locations and Dynamics of Ligand-Receptor Signaling at Cellular Resolution from Spatial Transcriptomic Data." Nature Genetics (accepted).
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Topological Velocity Inference from Spatial Transcriptomic Data Maps Cell Fate Transition in Space and Time

Published in Nature Biotechnology, 2025

A deep-learning method for jointly modeling temporal gene expression and spatial cellular dynamics from spatial transcriptomic data.

Recommended citation: Gu Y*, Liu J*, Lee HK, Li C, Lu L, Moline J, Guan R, Welch JD. (2025). "Topological Velocity Inference from Spatial Transcriptomic Data Maps Cell Fate Transition in Space and Time." Nature Biotechnology, 1-12.
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Techniques and Analytic Workflow for Spatial Transcriptomics and Its Application to Allergy and Inflammation

Published in Journal of Allergy and Clinical Immunology, 2025

A review of techniques and analytic workflows for spatial transcriptomics applied to allergy and inflammation research.

Recommended citation: Zhang H, Patrick MT, Zhao J, Zhai X, Liu J, Li Z, Gu Y, Welch J, Zhou X, Modlin RL, Tsoi LC, Gudjonsson JE. (2025). "Techniques and Analytic Workflow for Spatial Transcriptomics and Its Application to Allergy and Inflammation." Journal of Allergy and Clinical Immunology, 155.3, pp. 678-687.
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talks

teaching

MCDB 421 — Single-Cell Data Integration

Guest Lecture, University of Michigan, Department of Molecular, Cellular, and Developmental Biology, 2025

Guest lecture on single-cell data integration covering:

  • Why single-cell genomics: bulk vs. single-cell resolution
  • Single-cell data modalities (scRNA-seq, snATAC-seq, snmC-seq, 10X multiome)
  • Challenges with variation and batch effects in sequencing
  • Data integration methods (LIGER, Seurat anchors, Harmony)
  • Applications to multi-modal single-cell analysis