ReviewBriefings in bioinformatics2021
Computational methods for the integrative analysis of single-cell data.
Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.
- An integrated single cell and spatial transcriptomic map of human white adipose tissue.Nature communications · 2023Pooled it
- Tracing the molecular route to progression in miRNA-biogenesis-defective thyroid lesions.JCI insight · 2026Article
- Single-Cell Multi-Omics in Type 2 Diabetes Mellitus: Revealing Cellular Heterogeneity and Mechanistic Insights.International journal of molecular sciences · 2025Review
- Article
- PriorCCI: Interpretable Deep Learning Framework for Identifying Key Ligand-Receptor Interactions Between Specific Cell Types from Single-Cell Transcriptomes.International journal of molecular sciences · 2025Article
- A comparison of integration methods for single-cell RNA sequencing data and ATAC sequencing data.Quantitative biology (Beijing, China) · 2025Review
- SCITUNA: single-cell data integration tool using network alignment.BMC bioinformatics · 2025Article
- Single-Cell Sequencing: Genomic and Transcriptomic Approaches in Cancer Cell Biology.International journal of molecular sciences · 2025Review
- Benchmarking cross-species single-cell RNA-seq data integration methods: towards a cell type tree of life.Nucleic acids research · 2025Article
- scFocus: Detecting branching probabilities in single-cell data with SAC.Computational and structural biotechnology journal · 2025Article
- The tumor microenvironment across four dimensions: assessing space and time in cancer biology.Frontiers in immunology · 2025Review
- scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning.Briefings in bioinformatics · 2024Article
- Visualizing scRNA-Seq data at population scale with GloScope.Genome biology · 2024Article
- Visualizing scRNA-Seq Data at Population Scale with GloScope.bioRxiv : the preprint server for biology · 2024Article
- scPerturb: harmonized single-cell perturbation data.Nature methods · 2024Article
- Stabilized mosaic single-cell data integration using unshared features.Nature biotechnology · 2024Article
- Advancing immunotherapy for melanoma: the critical role of single-cell analysis in identifying predictive biomarkers.Frontiers in immunology · 2024Review
- scMuffin: an R package to disentangle solid tumor heterogeneity by single-cell gene expression analysis.BMC bioinformatics · 2023Article
- Review
- Applications of multi-omics analysis in human diseases.MedComm · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in single-cell technologies are providing exciting opportunities for dissecting tissue heterogeneity and investigating cell identity, fate and function. This is a pristine, exploding field that is flooding biologists with a new wave of data, each with its own specificities in terms of complexity and information content. The integrative analysis of genomic data, collected at different molecular layers from diverse cell populations, holds promise to address the full-scale complexity of biological systems. However, the combination of different single-cell genomic signals is computationally challenging, as these data are intrinsically heterogeneous for experimental, technical and biological reasons. Here, we describe the computational methods for the integrative analysis of single-cell genomic data, with a focus on the integration of single-cell RNA sequencing datasets and on the joint analysis of multimodal signals from individual cells.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.