ArticlePlant communications2023
scPlant: A versatile framework for single-cell transcriptomic data analysis in plants.
Article in Plant communications, 2023. 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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Who cites it
18 citing papers in PubMed.
- DESIGN: a framework for generative AI-enabled crop molecular design-driven breeding.Science China. Life sciences · 2026Review
- scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation.Journal of advanced research · 2026Article
- Advances in single-cell and spatial multi-omics for plant development and stress responses.Plant diversity · 2026Review
- Integrating single-cell omic techniques to resolve the spatio-temporal complexity of arbuscular mycorrhizal symbiosis.Journal of experimental botany · 2026Review
- Cell-type-specific gating of gene regulatory modules as a hallmark of early immune responses in Arabidopsis leaves.The New phytologist · 2026Article
- Decoding plant physiology through systems biology: Integrative multi-omics and computational perspectives for next-generation crop design.Plant communications · 2026Review
- Comprehensive insights into the development of arabidopsis trichomes by single-nucleus RNA-seq.BMC plant biology · 2026Article
- MINI-EX Version 2: Cell-Type-Specific Gene Regulatory Network Inference Using an Integrative Single-Cell Transcriptomics Approach.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Pangenomics and single-cell transcriptomics uncover the genetic basis of continuous bearing trait in grapevine.Horticulture research · 2025Article
- Single-Cell Transcriptome Reveals the Cellular Response to PEG-Induced Stress in Wheat Leaves.Journal of agricultural and food chemistry · 2025Article
- Hierarchical Regulatory Networks Reveal Conserved Drivers of Plant Drought Response at the Cell-Type Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Orthologous marker groups reveal broad cell identity conservation across plant single-cell transcriptomes.Nature communications · 2025Article
- Single-cell RNA sequencing reveals cellular diversity and gene expression dynamics in maize root development.Frontiers in plant science · 2025Article
- Direct RNA sequencing in plants: Practical applications and future perspectives.Plant communications · 2024Review
- A single-cell transcriptome atlas reveals the trajectory of early cell fate transition during callus induction in Arabidopsis.Plant communications · 2024Article
- Multiome in the Same Cell Reveals the Impact of Osmotic Stress on Arabidopsis Root Tip Development at Single-Cell Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis.Plant communications · 2024Article
- scPlantDB: a comprehensive database for exploring cell types and markers of plant cell atlases.Nucleic acids research · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth, development, and responses to external stimuli. However, single-cell transcriptomic data analysis in plants is not trivial, given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies. Here, we present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input data provided by users. The scPlant pipeline is implemented with numerous functions for diverse analytical tasks, ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution, trajectory inference, cross-species data integration, and cell-type-specific gene regulatory network construction. In addition, a variety of visualization tools are bundled in a built-in Shiny application, enabling exploration of single-cell transcriptomic data on the fly.
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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.