4.8 Article

HUSCH: an integrated single-cell transcriptome atlas for human tissue gene expression visualization and analyses

Journal

NUCLEIC ACIDS RESEARCH
Volume 51, Issue D1, Pages D1029-D1037

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkac1001

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Understanding gene expression patterns across different human cell types is crucial for investigating mechanisms of cell type differentiation and disease occurrence and progression. HUSCH is a large-scale database that integrates high-quality single-cell transcriptomic datasets from different tissues, providing comprehensive visualization and analysis of gene expression.
Understanding gene expression patterns across different human cell types is crucial for investigating mechanisms of cell type differentiation, disease occurrence and progression. The recent development of single-cell RNA-seq (scRNA-seq) technologies significantly boosted the characterization of cell type heterogeneities in different human tissues. However, the huge number of datasets in the public domain also posed challenges in data integration and reuse. We present Human Universal Single Cell Hub (HUSCH, ), an atlas-scale curated database that integrates single-cell transcriptomic profiles of nearly 3 million cells from 185 high-quality human scRNA-seq datasets from 45 different tissues. All the data in HUSCH were uniformly processed and annotated with a standard workflow. In the single dataset module, HUSCH provides interactive gene expression visualization, differentially expressed genes, functional analyses, transcription regulators and cell-cell interaction analyses for each cell type cluster. Besides, HUSCH integrated different datasets in the single tissue module and performs data integration, batch correction, and cell type harmonization. This allows a comprehensive visualization and analysis of gene expression within each tissue based on single-cell datasets from multiple sources and platforms. HUSCH is a flexible and comprehensive data portal that enables searching, visualizing, analyzing, and downloading single-cell gene expression for the human tissue atlas.

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