MASI enables fast model-free standardization and integration of single-cell transcriptomics data.

ABSTRACT: Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods, in terms of integration, annotation, and speed. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological condi

SUBMITTER: Xu Y 

PROVIDER: S-EPMC10144903 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature