SCIntRuler: Integration of Single-Cell RNA-seq Datasets

Source: R/SCIntRuler-package.R

The SCIntRuler package addresses the challenges of integrating multiple single-cell RNA-seq (scRNA-seq) datasets. It provides tools to enhance analytical robustness by augmenting sample sizes and reducing batch discrepancies. Developed using the Seurat framework, SCIntRuler includes both existing and novel workflows for single-cell analysis.

Value

This is the main page for SCIntRuler package.

Why SCIntRuler? Integrating scRNA-seq datasets can be complex due to various factors such as batch effects and sample diversity. SCIntRuler provides a statistical metric to aid in crucial decisions regarding dataset integration, ensuring more robust and accurate analyses.

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Features

  • Informed Decision Making: Helps researchers decide on the necessity of data integration and the most suitable method.

  • Flexibility: Suitable for various scenarios, accommodating different levels of data heterogeneity.

  • Robustness: Enhances analytical robustness in joint analyses of merged or integrated scRNA-seq datasets.

  • User-Friendly: Streamlines decision-making processes, simplifying the complexities involved in scRNA-seq data integration.

Getting Started

Refer to the "Getting Started with SCIntRuler" article in the package vignettes for detailed user instructions.

Author

Yue Lyu