ArticleCurrent protocols2022
Analyzing Spatial Transcriptomics Data Using Giotto.
Article in Current protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
18 citing papers in PubMed.
- A 3D spatial proteomic map of the human pancreatic islet microenvironment.Research square · 2026Article
- Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Article
- Mapping safety in space: the emerging role of spatial transcriptomics in safe drug development.Frontiers in toxicology · 2026Review
- Why "Where" Matters as Much as "How Much": Single-Cell and Spatial Transcriptomics in Plants.International journal of molecular sciences · 2025Review
- Giotto Suite: a multiscale and technology-agnostic spatial multiomics analysis ecosystem.Nature methods · 2025Article
- Cancer-associated fibroblasts shape the formation of budding cancer cells at the invasive front of human colorectal cancer.Communications biology · 2025Article
- Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser.Cell genomics · 2025Article
- Cell-specific priors rescue differential gene expression in spatial spot-based technologies.Briefings in bioinformatics · 2024Article
- An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology.Briefings in bioinformatics · 2024Article
- Spotless, a reproducible pipeline for benchmarking cell type deconvolution in spatial transcriptomics.eLife · 2024Article
- Signals that control MAIT cell function in healthy and inflamed human tissues.Immunological reviews · 2024Review
- Semi-automated approaches for interrogating spatial heterogeneity of tissue samples.Scientific reports · 2024Article
- Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA).Molecular systems biology · 2024Article
- RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data.Frontiers in genetics · 2024Article
- Broad H3K4me3 Domain Is Associated with Spatial Coherence during Mammalian Embryonic Development.bioRxiv : the preprint server for biology · 2023Article
- Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem.bioRxiv : the preprint server for biology · 2023Article
- Best practices for single-cell analysis across modalities.Nature reviews. Genetics · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Spatial transcriptomic technologies have been developed rapidly in recent years. The addition of spatial context to expression data holds the potential to revolutionize many fields in biology. However, the lack of computational tools remains a bottleneck that is preventing the broader utilization of these technologies. Recently, we have developed Giotto as a comprehensive, generally applicable, and user-friendly toolbox for spatial transcriptomic data analysis and visualization. Giotto implements a rich set of algorithms to enable robust spatial data analysis. To help users get familiar with the Giotto environment and apply it effectively in analyzing new datasets, we will describe the detailed protocols for applying Giotto without any advanced programming skills. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Getting Giotto set up for use Basic Protocol 2: Pre-processing Basic Protocol 3: Clustering and cell-type identification Basic Protocol 4: Cell-type enrichment and deconvolution analyses Basic Protocol 5: Spatial structure analysis tools Basic Protocol 6: Spatial domain detection by using a hidden Markov random field model Support Protocol 1: Spatial proximity-associated cell-cell interactions Support Protocol 2: Assembly of a registered 3D Giotto object from 2D slices.
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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.