ArticleeLife2024
Spotless, a reproducible pipeline for benchmarking cell type deconvolution in spatial transcriptomics.
Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Benchmarking cell-type deconvolution in cross-platform transcriptomic data.Genome biology · 2026Article
- Image-guided spatial omics enhancement reveals hidden spatial microstructures.Bioinformatics (Oxford, England) · 2026Article
- RETROFIT: Reference-free deconvolution of cell-type mixtures in spatial transcriptomics.Nature communications · 2026Article
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- ST-LDAW: A Topic-Model and Damped Weighted Least-Squares Method for Integrative Deconvolution of Single-Cell and Spatial Transcriptomics.Interdisciplinary sciences, computational life sciences · 2026Article
- Spatiotemporal cell type deconvolution leveraging tissue structure.Research square · 2026Article
- FlashDeconv reveals resolution horizons in atlas-scale spatial transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Pan-cancer analysis of spatial transcriptomics reveals heterogeneous tumor spatial microenvironment.Cell reports. Medicine · 2026Article
- ChatSpatial: Schema-Enforced Agentic Orchestration for Reproducible and Cross-Platform Spatial Transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking cell-type-specific spatially variable gene detection methods.Briefings in bioinformatics · 2026Article
- BEASTsim-a benchmarking and analysis platform for spatial transcriptomics simulations.Briefings in bioinformatics · 2026Article
- Local Tumor Microenvironment Niches Correlate With Survival And Immunotherapy Response In Human Glioblastoma.bioRxiv : the preprint server for biology · 2026Article
- Spatiotemporal cell type deconvolution leveraging tissue structure.bioRxiv : the preprint server for biology · 2026Article
- Advances in Spatial Transcriptomics in Bone.Current osteoporosis reports · 2026Review
- Discovering paracrine regulators of cell type composition from spatial transcriptomics using SPER.Bioinformatics advances · 2026Article
- Deciphering the Tumor Microenvironment Composition Using Bulk Transcriptomics: A Guide to Recent Advances and Open Challenges.Methods in molecular biology (Clifton, N.J.) · 2026Article
- A robust workflow to benchmark deconvolution of multi-omic data.Genome biology · 2025Article
- Spatial transcriptomics deconvolution methods generalize well to spatial chromatin accessibility data.Bioinformatics (Oxford, England) · 2025Article
- Refinement strategies for Tangram for reliable single-cell to spatial mapping.Bioinformatics (Oxford, England) · 2025Article
- LETSmix: a spatially informed and learning-based domain adaptation method for cell-type deconvolution in spatial transcriptomics.Genome medicine · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Spatial transcriptomics (ST) technologies allow the profiling of the transcriptome of cells while keeping their spatial context. Since most commercial untargeted ST technologies do not yet operate at single-cell resolution, computational methods such as deconvolution are often used to infer the cell type composition of each sequenced spot. We benchmarked 11 deconvolution methods using 63 silver standards, 3 gold standards, and 2 case studies on liver and melanoma tissues. We developed a simulation engine called
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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.