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SpaTalk package consists of five types of functions, namely the Datasets
, Preprocessing
, Main
, Visulization
, Demo-data
.
Please refer to the tutorial vignette with demo data processing steps. Detailed functions see the document
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geneinfo
Gene symbols of Human and Mouse updated on June 30, 2021 for revising count matrix -
lrpairs
Ligand-receptor pairs of Humanand Mouse containing 3398 human and 2033 mouse pairs -
pathways
KEGG pathways and Reactomes of Human and Mouse for intra-cellular genes and transcription factors
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rev_gene()
Revise gene symbols -
generate_spot()
Generate pseudo spot st_data with single-cell st_data -
createSpaTalk()
Create SpaTalk object using spatial transcriptomics data
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dec_celltype()
Identify the cellular composition with non-negative regression -
find_lr_path()
Find downstream targets and transcriptional factors for receptors -
dec_cci()
Identify the cell-cell communications -
dec_cci_all()
Identify the all cell-cell communications -
get_lr_path()
Get LR and downstream pathways -
set_expected_cell()
Set the expected cell for each spot.
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plot_st_pie_generate()
Plot scatterpie for data generated fromgenerate_spot()
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plot_st_pie()
Plot scatterpie for spot-based ST dataSpaTalk
object
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_pie.png)
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plot_st_gene()
Point plot with spatial distribution of a gene
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_gene_spot.png)
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plot_st_gene()
Point plot with spatial distribution of a gene
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_gene_cell.png)
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plot_st_celltype()
Ponit plot with spatial distribution of a single predicted cell type
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_celltype.png)
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plot_st_celltype_density()
Plot spatial density of a single predicted cell type
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_celltype_density.png)
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plot_st_celltype_density()
Plot spatial density of a single predicted cell type
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_celltype_raster.png)
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plot_st_celltype_percent()
Ponit plot with spatial distribution of a single predicted cell type percent
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_celltype_percent.png)
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plot_st_celltype_all()
Ponit plot with spatial distribution of all predicted cell types
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/st_celltype_all.png)
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plot_st_cor_heatmap()
Heatpmap of correlation between marker gene expression and cell type percent
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/cor_heatmap.png)
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plot_ccdist()
Point plot with spatial distribution of celltype_sender and celltype_receiver -
plot_cci_lrpairs(type = "sig")
Heatmap with LR pairs of celltype_sender and celltype_receiver
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/plot_cci_lrpairs.png)
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plot_cci_lrpairs(type = "number")
Heatmap with the number of spatial LRI pairs of celltype_sender and celltype_receiver
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/plot_cci_lrpairs_num.png)
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plot_lrpair()
Point plot with LR pair from celltype_sender to celltype_receiver
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/plot_lrpair.png)
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plot_lrpair_vln()
Violin plot spatial distance of LR pair between senders and receivers and between all cell-cell pairs
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/plot_lrpair_vln.png)
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plot_lr_path()
Plot network with LR and downstream pathways
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/plot_lr_path.png)
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plot_path2gene()
River plot of significantly activated pathways and related downstream genes of receptors
![](https://github.com/ZJUFanLab/SpaTalk/raw/main/img/plot_path2gene.png)
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demo_st_data()
demo spot-based ST data -
demo_st_meta()
demo spot-based ST meta -
demo_st_sc_data()
demo single-cell ST data -
demo_st_sc_meta()
demo single-cell ST meta -
demo_sc_data()
demo scRNA-seq data -
demo_geneinfo()
demo geneinfo -
demo_lrpairs()
demo lrpairs -
demo_pathways()
demo pathways -
demo_dec_result()
demo dec_result