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Azimuth Annotation Specifications

Process Details

  • Name: Azimuth Annotation
  • Process UUID: f93134kp86ix315h9t2g3gig5ur986
  • Process Group: Annotation

Overview

This process performs automated cell type annotation using the Azimuth reference mapping framework. It takes single-cell RNA-seq data and maps it against reference datasets to predict cell types and states. The process is particularly useful for annotating newly generated single-cell datasets by leveraging high-quality reference atlases.

This process is implemented in Bash, which invokes an R script for reference-based cell type annotation using Azimuth.

Key Functionality

  • Reference-based Annotation: Maps query single-cell data to curated reference datasets for automated cell type identification
  • Transfer Learning: Utilizes pre-trained models and reference indices to predict cell types and cellular states
  • Quality Assessment: Provides confidence scores and mapping quality metrics for annotation predictions

Input/Output Specification

Inputs

Required Inputs

  • RDS File (Set)

    • Description: Collection of R data objects containing single-cell expression data
    • Format: RDS

  • RDS File

    • Description: Single R data object with preprocessed single-cell RNA-seq data
    • Format: RDS

  • Input File TSV

    • Description: Tab-separated values file containing metadata or additional data parameters
    • Format: TSV

Outputs

  • RDS File
    • Description: Annotated single-cell dataset with predicted cell types, confidence scores, and mapping metrics
    • Format: RDS

References & Resources

  • Tool Documentation: Contact the team for details on azimuth_annotation.R
  • Related Papers: Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573-3587.e29 (2021). https://doi.org/10.1016/j.cell.2021.04.048