scTyper

"scTyper" is an R-based package designed for analyzing and cell typing single-cell RNA sequencing (scRNA-seq) data. Addressing the challenge of accurately identifying cell types within complex tissue samples, scTyper offers an integrated solution that leverages a curated database of cell type markers and advanced analytical methods to enhance the precision and reliability of cell typing in scRNA-seq datasets.

Key Features and Functionalities:

- Curated Database of Cell Type Markers (scTyper.db): scTyper includes scTyper.db, a database containing 213 cell marker sets collected from the literature. This resource covers many cell types, including malignant cells, cancer-associated fibroblasts, and tumor-infiltrating T cells, providing a valuable reference for cell typing.

- Customized Methods for Estimating Marker Expression: The package implements three customized methods for estimating the expression of cell-type markers:

- Nearest Template Prediction (NTP)
- Gene Set Enrichment Analysis (GSEA)
- Average Expression Values

These methods offer flexibility in analyzing scRNA-seq data, allowing users to choose the approach that best fits their research needs.

- DNA Copy Number Inference (inferCNV): An improved modification of the inferCNV method is integrated into scTyper, specifically tailored for typing malignant cells based on DNA copy number variations. This feature enhances the package's utility in cancer research.

- Compatibility with Preprocessing Pipelines: scTyper supports data preprocessing pipelines by Cell Ranger from 10X Genomics and the Seurat package, facilitating seamless integration with existing workflows.

- Summary Reporting System: A summary reporting system is implemented within scTyper, enabling users to perform reproducible analyses efficiently. This system provides a structured overview of the analysis results, aiding in the interpretation and communication of findings.