Poly Pipeline: A Polyvalent Spatial Transcriptomics Workflow Validated Across Polyploid and Diploid Organisms
Spatial transcriptomics (ST) has emerged as a transformative approach for visualizing tissue landscapes, yet it faces significant challenges regarding data standardization, sparsity, and the analysis of complex genomes, particularly polyploid plants. To address these limitations, we introduce Poly Pipeline, a robust and universal bioinformatic workflow designed to streamline analysis across…
Spatial transcriptomics, a cutting-edge method for visualizing tissue landscapes, has encountered obstacles related to data standardization, sparsity, and the analysis of complex genomes, particularly in polyploid plants. To tackle these issues, researchers have developed Poly Pipeline, a versatile bioinformatic workflow. This new tool simplifies the analysis process across a wide range of plant and animal genomes.
The Poly Pipeline incorporates a comprehensive converter for different file formats, clustering algorithms, and hdWGCNA co-expression networks. This combination ensures that even low-expressed duplicated genes maintain their original expression signatures. The workflow was tested on datasets from wheat, rice, Arabidopsis, and mouse, showcasing its wide-ranging applicability in identifying relevant clusters. The results demonstrated the pipeline's effectiveness in analyzing diverse organisms and data types.
Poly Pipeline offers a unified and reproducible framework that addresses a crucial gap in genomic analysis, especially concerning genomic redundancy related to polyploidy. By adhering to FAIR data principles, the tool promotes accessibility, interoperability, and reusability of data for the entire scientific community.
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