Package 'scRNAstat'

Title: A Pipeline to Process Single Cell RNAseq Data
Description: 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.
Authors: Jianming Zeng [aut], Yonghe Xia [ctb, cre], Biotrainee group [cph, fnd]
Maintainer: Yonghe Xia <[email protected]>
License: AGPL (>= 3)
Version: 0.1.1
Built: 2024-11-16 05:22:41 UTC
Source: https://github.com/cran/scRNAstat

Help Index


Small 'AJ064' Seurat Data After Processed

Description

An object of class Seurat

Usage

AJ064_small_last_sce

Format

An object of class Seurat with 627 rows and 800 columns.


Small 'AJ064' Seurat Data Set

Description

An object of class Seurat

Usage

AJ064_small_sce

Format

An object of class Seurat with 713 rows and 1000 columns.


basic_filter

Description

filter the genes which show expression less than 3 cells. filter the cells which percent_mito < 25 & percent_ribo > 3 & percent_hb < 10 filter the cells which nFeature_RNA > 300 & nFeature_RNA < 8000

Usage

basic_filter(sce)

Arguments

sce

An object of class Seurat

Value

sce.all.filt An object of class Seurat

Examples

basic_filter(AJ064_small_sce)

Basic Find Markers

Description

To find de 'novo' markers by 'FindAllMarkers' from Seurat with default setting.

Usage

basic_find_markers(sce, group = "seurat_clusters", dir = ".")

Arguments

sce

An object of class Seurat

group

default:seurat_clusters, you can change it to celltype

dir

path for saving results

Value

sce.markers a data.frame of markers.

Examples

basic_find_markers(AJ064_small_last_sce,dir=tempdir())

Basic Markers

Description

Basic Markers

Usage

basic_markers(sce, org = "human", group = "orig.ident", dir = ".")

Arguments

sce

An object of class Seurat

org

human or mouse, default: human

group

default:'orig.ident', you can change it to 'seurat_clusters' or 'celltype'

dir

the path for saving the figures by 'DotPlot' with known famous markers.

Value

a list of figures by 'DotPlot'

Examples

basic_markers(AJ064_small_last_sce,dir=tempdir())

Basic Quality Control

Description

add 'percent_mito','percent_ribo','percent_hb' to the Seurat class. And draw 'VlnPlot' for these 'qc' values.

Usage

basic_qc(sce, org = "human", group = "orig.ident", dir = ".")

Arguments

sce

An object of class Seurat

org

human or mouse, default: human

group

default:'orig.ident',you can change it to 'seurat_clusters' or 'celltype'

dir

the path for saving the figures by 'DotPlot' with known famous markers.

Value

list(p1,p2,p3,sce), the last one in the new 'sce'.

Examples

basic_qc(AJ064_small_sce,dir= tempdir())

Basic Workflow

Description

the workflow from Seurat, including: 'NormalizeData','FindVariableFeatures','ScaleData', 'RunPCA','RunTSNE','RunUMAP','FindNeighbors','FindClusters(sce, resolution = seq(0.1,1,by=0.1))' we use 'clustree' to check the different resolution for 'FindClusters'.

Usage

basic_workflow(sce, dir = ".")

Arguments

sce

An object of class Seurat

dir

the path for saving the figures by 'DotPlot' with known famous markers.

Value

list(p1,p2,p3,sce), the last one in the new sce with PCA,tSNE,UMAP information.

Examples

## Not run: 
basic_workflow(AJ064_small_sce,dir=tempdir())

## End(Not run)