scRNAstat: A Pipeline to Process Single Cell RNAseq Data

A pipeline that can process single or multiple Single Cell RNAseq samples primarily specializes in Clustering and Dimensionality Reduction. Meanwhile we use common cell type marker genes for T cells, B cells, Myeloid cells, Epithelial cells, and stromal cells (Fiboblast, Endothelial cells, Pericyte, Smooth muscle cells) to visualize the Seurat clusters, to facilitate labeling them by biological names. Once users named each cluster, they can evaluate the quality of them again and find the de novo marker genes also.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: Seurat, ggplot2, stringr, clustree, magrittr, Matrix, dplyr, patchwork
Published: 2021-09-22
DOI: 10.32614/CRAN.package.scRNAstat
Author: Jianming Zeng [aut], Yonghe Xia [ctb, cre], Biotrainee group [cph, fnd]
Maintainer: Yonghe Xia <xiayh17 at>
License: AGPL (≥ 3)
NeedsCompilation: no
CRAN checks: scRNAstat results


Reference manual: scRNAstat.pdf


Package source: scRNAstat_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): scRNAstat_0.1.1.tgz, r-oldrel (arm64): scRNAstat_0.1.1.tgz, r-release (x86_64): scRNAstat_0.1.1.tgz, r-oldrel (x86_64): scRNAstat_0.1.1.tgz


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