Scissor: Single-Cell Identification of Subpopulations with bulk Sample phenOtype coRrelation

Introduction

Scissor is a novel approach that utilizes the phenotypes, such as disease stage, tumor metastasis, treatment response, and survival outcomes, collected from bulk assays to identify the most highly phenotype-associated cell subpopulations from single-cell data. The workflow of Scissor is shown in the following Figure:

News

Feb, 2021: Scissor version 2.0.0 is launched.
Jun, 2020: Scissor version 1.0.0 is launched.

Installation

• Prerequisites: Scissor is developed under R (version >= 3.6.1). The Seurat package (version >= 3.2.0) is used for loading data and preprocessing.

• Latest version: The latest developmental version of Scissor can be downloaded from GitHub and installed from source by devtools::install_github('sunduanchen/Scissor')

Manual

Please see https://sunduanchen.github.io/Scissor/vignettes/Scissor_Tutorial.html for details. In the R terminal, please use the command ?Scissor to access the help documents.

Example

Our tutorial https://sunduanchen.github.io/Scissor/vignettes/Scissor_Tutorial.html provides examples of Scissor, which identified a lung cancer cell subpopulation from lung cancer single cell data, guided by the TCGA-LUAD 471 bulk RNA-seq samples and their corresponding survival information.

How to cite Scissor

Please cite the following manuscript:

Phenotype-guided subpopulation identification from single-cell sequencing data
Duanchen Sun and Zheng Xia

License

Scissor is licensed under the GNU General Public License v3.0.