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BFAST: joint dimension reduction and spatial clustering with Bayesian factor analysis for zero-inflated spatial

Yang Xu1,2, Dian Lv1,2, Xuanxuan Zou1,2

  • 1BGI-Research, 313, Gaoteng Avenue, Jiulongpo, Chongqing 400039, China.

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We developed Bayesian Factor Analysis for zero-inflated Spatial Transcriptomics data (BFAST), a new method for spatial clustering. BFAST improves gene expression analysis by reducing noise and enhancing clustering accuracy in spatial transcriptomics data.

Keywords:
Bayesian factor analysisdimension reductionspatial Transcriptomicsspatial clusteringzero-inflated

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Spatially resolved transcriptomics (ST) technologies enable gene expression profiling with spatial context.
  • Understanding cellular heterogeneity and tissue microenvironments is crucial for biological research.
  • Existing spatial clustering algorithms struggle with high noise and dropout events in ST data.

Purpose of the Study:

  • To develop a novel method for dimension reduction and spatial clustering of spatial transcriptomics data.
  • To address challenges posed by noise and dropout events in ST data analysis.
  • To improve the accuracy and precision of spatial clustering for biological insights.

Main Methods:

  • Developed Bayesian Factor Analysis for zero-inflated Spatial Transcriptomics data (BFAST).
  • Jointly performed dimension reduction and spatial clustering.
  • Benchmarked BFAST against existing methods using simulation and real ST datasets.

Main Results:

  • BFAST demonstrated exceptional performance on simulation and real spatial transcriptomics datasets.
  • The method effectively extracts more biologically informative low-dimensional features.
  • BFAST significantly enhances the accuracy and precision of spatial clustering compared to traditional approaches.

Conclusions:

  • BFAST offers a robust solution for spatial clustering of noisy ST data.
  • The method improves the characterization of cellular phenotype heterogeneity and tissue microenvironments.
  • BFAST advances downstream analysis in spatial transcriptomics research.