scCompare: a web app for single-cell RNA sequencing dataset comparisons across multiple auto-immune diseases

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Abstract

Motivation Single-cell RNA sequencing (scRNA-seq) datasets have been widely used to identify the cell types and marker genes with pivotal roles in driving pathogenesis and progression of auto-immune diseases. Comparative analysis of different cell types or diseases across multiple scRNA-seq datasets can reveal the homogeneous and heterogeneous pathogenesis, and a comprehensive web-based comparison tool that could streamline this process is not yet available. Results We introduce scCompare, a web-based platform for scRNA-seq comparisons in autoimmune diseases. scCompare includes 2,125 differential gene lists from 100 scRNA-seq datasets in 22 auto-immune diseases and a query system supporting 170 standardized keywords from four attributes (disease, cell type, tissue, and treatment). scCompare also provides three modules enabling several comparative analysis and visualization options. geneQuery supports comparisons of queried genes across differential gene lists identified from multiple scRNA-seq datasets. DEGEnricher performs cell-type-specific enrichment analysis across studies based on a user-input gene list. DEGCompare allows interactive comparisons of multiple differential gene lists of many studies and performs pathway enrichment analyses. Using two case studies as examples, we demonstrated that scCompare represents a unique platform for biologists to identify, compare and validate the pathogenesis at the single-cell levels among auto-immune diseases. Availability and implementation scCompare is freely available at https://sccompare.shinyapps.io/main/ . The source code is available at https://github.com/abbviegrc/scCompare .
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Abstract

Motivation Single-cell RNA sequencing (scRNA-seq) datasets have been widely used to identify the cell types and marker genes with pivotal roles in driving pathogenesis and progression of auto-immune diseases. Comparative analysis of different cell types or diseases across multiple scRNA-seq datasets can reveal the homogeneous and heterogeneous pathogenesis, and a comprehensive web-based comparison tool that could streamline this process is not yet available.

Results

We introduce scCompare, a web-based platform for scRNA-seq comparisons in autoimmune diseases. scCompare includes 2,125 differential gene lists from 100 scRNA-seq datasets in 22 auto-immune diseases and a query system supporting 170 standardized keywords from four attributes (disease, cell type, tissue, and treatment). scCompare also provides three modules enabling several comparative analysis and visualization options. geneQuery supports comparisons of queried genes across differential gene lists identified from multiple scRNA-seq datasets. DEGEnricher performs cell-type-specific enrichment analysis across studies based on a user-input gene list. DEGCompare allows interactive comparisons of multiple differential gene lists of many studies and performs pathway enrichment analyses. Using two case studies as examples, we demonstrated that scCompare represents a unique platform for biologists to identify, compare and validate the pathogenesis at the single-cell levels among auto-immune diseases. Availability and implementation scCompare is freely available at https://sccompare.shinyapps.io/main/. The source code is available at https://github.com/abbviegrc/scCompare. Competing Interest Statement All authors are employees/contractors of AbbVie. The design, study conduct, and financial support for this research were provided by AbbVie. AbbVie participated in the interpretation of data, review, and approval of the publication. Footnotes Disclosures JW, DC, and PS are employees of AbbVie. SY and MP are contractors for AbbVie. The design, study conduct, and financial support for this research were provided by AbbVie. AbbVie participated in the interpretation of data, review, and approval of the publication.

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last seen: 2026-05-20T01:45:00.602351+00:00