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PreDigs: A Database of Context-specific Cell Type Markers and Precise Cell Subtypes for Digestive Cell Annotation.

Jiayue Meng1, Mengyao Han2, Yuwei Huang1

  • 1National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.

Genomics, Proteomics & Bioinformatics
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Summary

PreDigs is a new database featuring 124 single-cell RNA sequencing datasets for digestive system research. It aids in identifying tumor-specific cell types and improving our understanding of gastrointestinal cancer heterogeneity.

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Cell type markerData integrationDatabaseGastrointestinal tumorSingle-cell RNA sequencing

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Area of Science:

  • Single-cell RNA sequencing
  • Genomics
  • Bioinformatics

Background:

  • Gastrointestinal tumor research benefits from understanding cellular composition.
  • Tumor heterogeneity impacts disease progression and treatment.
  • Challenges include integrating large datasets and standardizing cell identification.

Purpose of the Study:

  • To develop PreDigs, a user-friendly database of predicted cell signatures in the digestive system.
  • To provide a comprehensive resource of single-cell RNA sequencing data for gastrointestinal research.
  • To offer tools for cell type identification and annotation.

Main Methods:

  • Curated 124 single-cell RNA sequencing datasets (over 3.4 million cells).
  • Applied unsupervised clustering for cell identification and naming.
  • Constructed a cell ontology tree with 142 cell types across eight hierarchical levels.
  • Calculated context-specific cell-type markers (Cell Markers, Subtype Markers, TPN Markers).

Main Results:

  • Identified distinct cell subpopulations exclusive to tumors.
  • Discovered tumor-specific endothelial cells.
  • PreDigs database is available for download.
  • Online cell annotation tools are provided for flexible cell classification.

Conclusions:

  • PreDigs enhances the study of gastrointestinal tumor cellular composition and heterogeneity.
  • The database and tools facilitate deeper insights into disease mechanisms and treatment responses.
  • Facilitates identification of novel tumor-specific cell types.