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Updated: Sep 19, 2026

Isolation and Transcriptome Analysis of Plant Cell Types
Published on: April 7, 2023
iPscDB: a comprehensive platform for plant single-cell transcriptomic data integration and analysis
Peng Lu1,2,3, Jingjing Jin1,2, Jiemeng Tao1,2
1China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China.
Abstract:
The rapid advancement of single-cell technologies has significantly enhanced our ability to investigate cellular heterogeneity within plant tissues. However, deciphering these intricate cellular landscapes requires processing high-dimensional gene expression matrices and integrating diverse datasets to enable accurate marker selection, cell identification, and other complex computational operations. These processes typically require broad programming expertise, posing a challenge for researchers with a limited computational background. To address this, we present integrated Plant single-cell Database (iPscDB), an integrated and multifunctional platform that facilitates the integration and analysis of plant single-cell data. iPscDB combines 4 688 428 cells and 288 139 curated cell markers derived from 946 experiments across 38 plant species. Wherever raw data were available, datasets were reprocessed through a single uniform pipeline, and both integration quality and automated cell-type annotation were benchmarked quantitatively. The platform introduces a Marker Confidence Level scheme that grades each cell-type marker by the strength and independence of its supporting evidence (from manually curated classic markers to database-derived associations), allowing users to judge marker reliability directly. The platform also provides a user-friendly online analysis pipeline and modules capable of processing raw FASTQ files or Cell Ranger-processed files. Users can configure parameters via an intuitive interface and utilize an integrated image editor to customize visualization outputs. Additionally, iPscDB supports various analyses, including cross-species gene expression, electronic Single-Cell Pictograph, and developmental trajectory. By streamlining the complex workflows of single-cell transcriptomics, iPscDB offers a practical and accessible resource for researchers with diverse technical backgrounds. iPscDB is accessible at https://www.tobaccodb.org/ipscdb/homePage.
