摘要
The comparative analysis of single-cell RNA sequencing (scRNA-seq) datasets across various biological conditions, technology platforms and tissue types reveals crucial insights into cellular heterogeneity and tissue architecture. Recent advances in high-resolution technologies have enabled the profiling of gene expression at the single-cell level, yet inherent heterogeneities between platforms and differences in cell type composition make data integration challenging. We present the FIRM R package, which offers a streamlined workflow for the flexible integration of scRNA-seq data using a re-scaling algorithm that accounts for the effects of cell type composition. FIRM achieves accurate mixing of shared cell type identities and superior preservation of the original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis.
| 源语言 | 英语 |
|---|---|
| 期刊 | Statistical Theory and Related Fields |
| DOI | |
| 出版状态 | 已接受/待刊 - 2026 |
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