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Open research questions in Single-cell and spatial transcriptomics

1,178 gap statements mined from Single-cell and spatial transcriptomics papers in our 7.9M-paper local library, which holds 6,149 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • The lack of a prospectively validated liver simulator that can predict responses to untested genetic, chemical, inflammatory, or metabolic interventions. The need for a framework for evaluating and improving AI Virtual Cell models for the liver. The limitation of current single-cell and spatial atlases in predicting liver behavior.

    Toward AI Virtual Cells for Hepatology: Representation, Generation, Dynamics, and Intervention in Single-Cell Models · 2026 · DOI

  • Extracting biological insight from multimodal datasets remains technically demanding. The paper mentions the challenge of downsampling in the CellChat module, which can destabilize the inferred pathway ranking.

    SingleRepExplorer: a unified interactive platform for integrated single-cell transcriptomic and immune repertoire analysis · 2026 · DOI

  • The limitation of traditional flow cytometry techniques, such as the need for labeling. The challenge of developing label-free flow cytometry technologies.

    Recent Developments (After 2020) in Flow Cytometry Worldwide and Within China · 2025 · DOI

  • Established methods such as XGBoost, Seurat reference mapping, and scANVI have limitations in terms of noise tolerance and scalability.

    Robust Single-Cell RNA-Seq Analysis Using Hyperdimensional Computing: Enhanced Clustering and Classification Methods · 2025 · DOI

  • Pediatric and neonatal development and disease have been largely understudied compared to their adult counterparts.

    Impact of the single cell revolution on neonatology research · 2026 · DOI

  • Single-cell atlases have enabled the prediction of human cell-cell communication (CCC) networks in cancer, but whether predicted communication networks have clinical significance is not well understood.

    Survival-associated cellular communication networks in human solid cancers · 2026 · DOI

  • Tumours comprise heterogeneous phenotypic states, but how these states are reorganized during malignant progression and therapeutic adaptation remains poorly understood.

    Phenotype-cloud reorganization shapes cancer progression and therapeutic adaptation · 2026 · DOI

  • Although generative models have revolutionized many fields, including genomics, building a scalable dataset compatible with artificial intelligence (AI) is essential yet underexplored.

    GENOAR: Global Engine for Navigating the Omnicell space via Agent-based Research · 2026 · DOI

  • Combining these measurements helped distinguish candidates with similar RNA evidence and assess their functional relevance and expression in normal tissues, although therapeutic selectivity remains to be established.

    General Purpose AI for Public Data Analysis and Experimental Hypothesis Generation · 2026 · DOI

  • Phenoscapes remain a comparatively new and underexplored representation and existing static phenoscapes position experimental conditions relative to one another without specifying trajectories that describe how a cellular population moves from one condition to another.

    GeoSinkhorn Flow: Geometry-Aware Flow Matching for Perturbation-Conditioned Dynamics in Single cell Data Phenoscapes · 2026 · DOI

  • Senescence is a cellular phenomenon that may contribute to aging, but how it presents in the human hippocampus remains unclear.

    Dissecting cellular and molecular networks of aging and senescence in the human hippocampus · 2026 · DOI

  • However, reliable uncertainty estimates are essential for identifying potentially inaccurate predictions, and it remains unclear whether existing methods provide useful information about prediction reliability.

    Probabilistic uncertainty in virtual spatial transcriptomics from histology is largely redundant with the predicted mean · 2026 · DOI

  • Thus, accurate detection of immune cells with distinct functional signatures was enabled, permitting more unique and understudied populations to be quantified, including T regulatory 1 (Tr1) and cytotoxic type 2 (Tc2) T cell subsets.

    Superior Intracellular Detection of Cytokines, Transcription Factors, and Phosphoproteins by CyTOF Compared With Fluorescent Cytometry · 2026 · DOI

  • Fluorescent reporter viruses permit this process to be followed at single-cell resolution, but whether secondary infected cells retain detectable signatures associated with their plaque of origin remains unclear.

    Single‐Cell Reporter Dynamics During the First Two Rounds of Rhinovirus Plaque Growth · 2026 · DOI

  • Cancer-associated fibroblasts (CAFs) are major contributors to extracellular matrix (ECM) remodeling in breast cancer (BRCA), but the transcriptional programs underlying pathological CAF remodeling remain incompletely understood.

    Integrative single-cell and spatial analyses implicate ECM2 in pathological CAF remodeling in breast cancer · 2026 · DOI

  • N-cadherin + ( CDH2) glandular epithelial progenitors and SUSD2 + mesenchymal stem cells (MSCs) and their niches have been identified, but their signaling interactions remain unknown.

    Molecular signature of human endometrial stem/progenitor cells at the single-cell level · 2026 · DOI

  • Intestinal epithelial cells rely on a complex array of stromal signals to determine their fate and function along the crypt-villus axis, but the precise cellular sources and combinations of signals at each position remain poorly defined.

    Single-Cell Transcriptome Profiles of Foxl1-Lineage Cells Along the Intestinal Crypt–Villus Axis · 2026 · DOI

  • Introduction The spatial organization of epithelial states relative to stromal and myeloid cells in gastric cancer remains incompletely understood.

    Spatial association of an AKR1C3-positive epithelial state with ACTA2-positive stromal cells and SPP1-positive macrophages in gastric cancer · 2026 · DOI

  • Although the transcriptional landscape of the tumor microenvironment (TME) in AM has been characterized, the heterogeneity of malignant cells and underlying molecular features remain to be fully delineated.

    Integrative Single‐Cell and Bulk Transcriptomic Analysis Defines a Molecular Stratification Strategy Based on Intra‐Tumoral Heterogeneity in Acral Melanoma · 2026 · DOI

  • Limited scalability of manual workflows for high-throughput processing. Accurate taxonomic assignment and quality assessment of co-assembled genomes.

    CoSAG-nf: A Scalable Nextflow Pipeline for Co-assembly, Optimization, and Interactive Visualization of High-Throughput Single-Cell Genomes · 2026 · DOI

  • Liver evaluation should hold out donors, disease contexts, perturbations, or platforms and compare predictions with independent spatial measurements, - Evaluating metabolic function in MASLD and MASH requires more than transcriptomic…

    Toward AI Virtual Cells for Hepatology: Representation, Generation, Dynamics, and Intervention in Single-Cell Models · 2026 · DOI

  • Further development of CoSAG-nf to improve its performance, - Investigation of the application of CoSAG-nf to other types of sequencing data, - Comparison of CoSAG-nf with other existing…

    CoSAG-nf: A Scalable Nextflow Pipeline for Co-assembly, Optimization, and Interactive Visualization of High-Throughput Single-Cell Genomes · 2026 · DOI

  • Insufficient understanding of the dynamic mechanisms governing immune cell subset transitions. Inadequate knowledge of the intricate regulatory networks underlying metabolism-immune crosstalk.

    Single-cell sequencing reveals immune networks and metabolic reprogramming in gynecological malignancies · 2026 · DOI

  • The analysis of multimodal datasets remains a substantial barrier for experimental immunologists, - The module downsamples any condition exceeding a user-set cell cap, - The dataset contains only paired scRNA-seq, TCR, and BCR contig…

    SingleRepExplorer: a unified interactive platform for integrated single-cell transcriptomic and immune repertoire analysis · 2026 · DOI

  • Further research is needed to explore the potential of HDC in other high-dimensional biological datasets, - Investigating the application of HDC in proteomics, epigenomics, and transcriptomics could be a future research direction, - Personalized medicine could be an area where HDC is applied…

    Robust Single-Cell RNA-Seq Analysis Using Hyperdimensional Computing: Enhanced Clustering and Classification Methods · 2025 · DOI

Most-cited papers in Single-cell and spatial transcriptomics

Most recent work

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Open questions raised by papers listed on this page include: (1) The lack of a prospectively validated liver simulator that can predict responses to untested genetic, chemical, inflammatory, or metabolic interventions (“Toward AI Virtual Cells for Hepatology: Representation, Generation, Dynamics,…”, 2026); (2) Single-cell atlases have enabled the prediction of human cell-cell communication (CCC) networks in cancer, but whether predicted communication networks have clinical significance is not well understood (“Survival-associated cellular communication networks in human solid cancers”, 2026); (3) Tumours comprise heterogeneous phenotypic states, but how these states are reorganized during malignant progression and therapeutic adaptation remains poorly understood (“Phenotype-cloud reorganization shapes cancer progression and therapeutic…”, 2026); (4) Combining these measurements helped distinguish candidates with similar RNA evidence and assess their functional relevance and expression in normal tissues, although therapeutic selectivity remains to be established (“General Purpose AI for Public Data Analysis and Experimental Hypothesis…”, 2026); (5) Senescence is a cellular phenomenon that may contribute to aging, but how it presents in the human hippocampus remains unclear (“Dissecting cellular and molecular networks of aging and senescence in the human…”, 2026). 1,178 gap statements have been mined from Single-cell and spatial transcriptomics papers in our 7.9M-paper local library, which holds 6,149 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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