| Type: | Package |
| Title: | A Pipeline to Process Single Cell RNAseq Data |
| Version: | 0.1.1.1 |
| Maintainer: | Yonghe Xia <xiayh17@gmail.com> |
| 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. |
| License: | AGPL (≥ 3) |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.2 |
| Depends: | R (≥ 2.10) |
| Imports: | Seurat, ggplot2, stringr, clustree, magrittr, Matrix, dplyr, patchwork |
| Suggests: | DBI |
| NeedsCompilation: | no |
| Packaged: | 2025-03-08 07:02:38 UTC; hornik |
| Author: | Jianming Zeng [aut], Yonghe Xia [ctb, cre], Biotrainee group [cph, fnd] |
| Repository: | CRAN |
| Date/Publication: | 2025-03-08 08:58:55 UTC |
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
Arguments
lhs |
A value or the magrittr placeholder. |
rhs |
A function call using the magrittr semantics. |
Value
The result of calling 'rhs(lhs)'.
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)