RareQ: Cell Neighborhood Topology Directs Rare Cell Population Identification

RareQ_0.1.0.tar.gz: Source R package of RareQ algorithm for rare cell identification from single-cell data (scRNA-seq, scATAC-seq, CITE-seq) and spatial transcriptomic data (e.g. Xenuim) via neighborhood connectivity (Q)-based network propagation.

Tutorial_example.rar: Step-by-step R code for the usage of RareQ in scRNA-seq data, paired scRNA-seq and scATAC-seq data, CITE-seq (RNA and ADT) data, Xenuim spatial data.

simulation.rar: Python code and associated datasets for generating simulation datasets in the manuscript.

B_lymphoma.rar: Analysis of RareQ in a paired scRNA-seq and scATAC-seq data from human B lymphoma. Source code and data are accompanied.

bmcite.rar: Analysis of RareQ in a CITE-seq data in RNA, protein and weighted nearest neighbor (WNN)-integrated data. Source data is RDS format accompanied by R code.

Alzheimer.rar: Analysis of RareQ in snRNA-seq data from the brain of healthy and Alzheimer's Disease (AD) patients. Source code and data are accompanied.

smFISH.rar: Analysis of RareQ in a spatial transcriptomic data of mouse brain by EEL FISH platform. Source data is h5ad format accompanied by R code.

Xenium_Mouse_Brain.rar: Analysis of RareQ in a spatial transcriptomic data of the mouse brain by the Xenium platform. Source code and data are accompanied.

Xenium_Human_Kidney_RNA_Protein.rar: Analysis of RareQ in a spatial transcriptomic and protein data of mouse kidney by the Xenium platform. Source code and data are accompanied.