Filter, Plot and Explore Single-cell RNA-seq Data


StepAnnotation
Step 1: Input dataset
select at runtime
Step 2: Inspect AnnData
Output dataset 'output' from step 1
Key-indexed observations annotation (obs)
Step 3: Scanpy FilterCells
Output dataset 'output' from step 1
AnnData format hdf5
AnnData format
Empty.
Parameters to select cells to keeps
Parameters to select cells to keep 1
log1p_n_genes_by_counts
5.7
20.0
Categories to select cells to keep (unless negate is checked)s
Subsets to select cells to keeps
False
False
Step 4: Plot
Output dataset 'output' from step 1
png
Generic: Scatter plot along observations or variables axes, using 'pl.scatter'
Using coordinates
log1p_total_counts
log1p_n_genes_by_counts
pct_counts_mito
No
False
True
Empty.
Plot attributes:
Components
2d
right margin
Not available.
normal
Default
Default
True
Not available.
Empty.
Advanced Options:
False
Step 5: Plot
Output dataset 'output' from step 1
png
Generic: Scatter plot along observations or variables axes, using 'pl.scatter'
Using coordinates
log1p_n_genes_by_counts
pct_counts_mito
Empty.
No
False
True
Empty.
Plot attributes:
Components
2d
right margin
Not available.
normal
Default
Default
True
Not available.
Empty.
Advanced Options:
False
Step 6: Plot
Output dataset 'output' from step 1
png
Generic: Violin plot, using 'pl.violin'
Subset of variables in 'adata.var_names' or fields of '.obs'
log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito
genotype
False
False
Violin plot attributes:
Yes
Yes
1.0
No
width: each violin will have the same width
Empty.
Not available.
Parameters for seaborn.violinplot:
scott
Nothing selected.
0.0
AliceBlue
0.75
Advanced Options:
False
Step 7: Plot
Output dataset 'output' from step 1
png
Generic: Violin plot, using 'pl.violin'
Subset of variables in 'adata.var_names' or fields of '.obs'
log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito
batch
False
False
Violin plot attributes:
Yes
Yes
1.0
No
width: each violin will have the same width
Empty.
Not available.
Parameters for seaborn.violinplot:
scott
Nothing selected.
0.0
AliceBlue
0.75
Advanced Options:
False
Step 8: Inspect AnnData
Output dataset 'output' from step 1
Key-indexed annotation of variables/features (var)
Step 9: Plot
Output dataset 'output' from step 1
png
Generic: Scatter plot along observations or variables axes, using 'pl.scatter'
Using coordinates
log1p_total_counts
pct_counts_mito
Empty.
No
False
True
Empty.
Plot attributes:
Components
2d
right margin
Not available.
normal
Default
Default
True
Not available.
Empty.
Advanced Options:
False
Step 10: Inspect AnnData
Output dataset 'output' from step 1
General information about the object
Step 11: Plot
Output dataset 'output' from step 1
png
Generic: Violin plot, using 'pl.violin'
Subset of variables in 'adata.var_names' or fields of '.obs'
log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito
sex
False
False
Violin plot attributes:
Yes
Yes
1.0
No
width: each violin will have the same width
Empty.
Not available.
Parameters for seaborn.violinplot:
scott
Nothing selected.
0.0
AliceBlue
0.75
Advanced Options:
False
Step 12: Plot
Output dataset 'output_h5ad' from step 3
png
Generic: Violin plot, using 'pl.violin'
Subset of variables in 'adata.var_names' or fields of '.obs'
log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito
genotype
False
False
Violin plot attributes:
Yes
Yes
1.0
No
width: each violin will have the same width
Empty.
Not available.
Parameters for seaborn.violinplot:
scott
Nothing selected.
0.0
AliceBlue
0.75
Advanced Options:
False
Step 13: Scanpy FilterCells
Output dataset 'output_h5ad' from step 3
AnnData format hdf5
AnnData format
Empty.
Parameters to select cells to keeps
Parameters to select cells to keep 1
log1p_total_counts
6.3
20.0
Categories to select cells to keep (unless negate is checked)s
Subsets to select cells to keeps
False
False
Step 14: Inspect AnnData
Output dataset 'output_h5ad' from step 3
General information about the object
Step 15: Inspect AnnData
Output dataset 'output_h5ad' from step 13
General information about the object
Step 16: Scanpy FilterCells
Output dataset 'output_h5ad' from step 13
AnnData format hdf5
AnnData format
Empty.
Parameters to select cells to keeps
Parameters to select cells to keep 1
pct_counts_mito
0.0
4.5
Categories to select cells to keep (unless negate is checked)s
Subsets to select cells to keeps
False
False
Step 17: Plot
Output dataset 'output_h5ad' from step 13
png
Generic: Violin plot, using 'pl.violin'
Subset of variables in 'adata.var_names' or fields of '.obs'
log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito
genotype
False
False
Violin plot attributes:
Yes
Yes
1.0
No
width: each violin will have the same width
Empty.
Not available.
Parameters for seaborn.violinplot:
scott
Nothing selected.
0.0
AliceBlue
0.75
Advanced Options:
False
Step 18: Inspect AnnData
Output dataset 'output_h5ad' from step 16
General information about the object
Step 19: Scanpy FilterGenes
Output dataset 'output_h5ad' from step 16
AnnData format hdf5
AnnData format
Parameters to select genes to keeps
Parameters to select genes to keep 1
n_cells
3.0
1000000000.0
Categories to select genes to keep (unless negate is checked)s
Subsets to select genes to keeps
False
False
Step 20: Plot
Output dataset 'output_h5ad' from step 16
png
Generic: Violin plot, using 'pl.violin'
Subset of variables in 'adata.var_names' or fields of '.obs'
log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito
genotype
False
False
Violin plot attributes:
Yes
Yes
1.0
No
width: each violin will have the same width
Empty.
Not available.
Parameters for seaborn.violinplot:
scott
Nothing selected.
0.0
AliceBlue
0.75
Advanced Options:
False
Step 21: Inspect AnnData
Output dataset 'output_h5ad' from step 19
General information about the object
Step 22: Scanpy NormaliseData
Output dataset 'output_h5ad' from step 19
AnnData format hdf5
AnnData format
False
True
Step 23: Scanpy FindVariableGenes
Output dataset 'output_h5ad' from step 22
AnnData format hdf5
AnnData format
Seurat
0.0125
3.0
0.5
50.0
2000
0.3
20
False
Empty.
Step 24: Scanpy ScaleData
Output dataset 'output_h5ad' from step 23
AnnData format hdf5
AnnData format
True
10.0
Step 25: Scanpy RunPCA
Output dataset 'output_h5ad' from step 24
AnnData format hdf5
AnnData format
50
False
True
Nothing selected.
0
Nothing selected.
Step 26: Plot
Output dataset 'output_h5ad' from step 25
png
PCA: Scatter plot in PCA coordinates, using 'pl.pca_variance_ratio'
50
False
Advanced Options:
False
Step 27: Scanpy ComputeGraph
Output dataset 'output_h5ad' from step 25
AnnData format hdf5
AnnData format
False
Empty.
15
select at runtime
X_pca, use PCs
20
True
UMAP
Euclidean
0
Step 28: Scanpy RunTSNE
Output dataset 'output_h5ad' from step 27
AnnData format hdf5
AnnData format
True
Automatically chosen based on problem size
False
Empty.
30.0
select at runtime
12.0
1000.0
False
Not available.
Not available.
0
Step 29: Scanpy RunUMAP
Output dataset 'output_h5ad' from step 28
AnnData format hdf5
AnnData format
True
neighbors
Empty.
True
Step 30: Scanpy FindCluster
Output dataset 'output_h5ad' from step 29
AnnData format hdf5
AnnData format
True
Louvain
False
neighbors
Empty.
Empty.
0.6
select at runtime
Empty.
False
0
True
Step 31: Scanpy FindMarkers
Output dataset 'output_h5ad' from step 30
AnnData format hdf5
AnnData format
True
50
louvain
select at runtime
False
Empty.
t-test with over-estimated variance
True
False
Empty.
rest
0.25
0.5
2.0
False
False
Step 32: Scanpy FindMarkers
Output dataset 'output_h5ad' from step 30
AnnData format hdf5
AnnData format
True
50
genotype
select at runtime
False
Empty.
t-test with over-estimated variance
True
False
Empty.
rest
0.25
0.5
2.0
False
False
Step 33: Scanpy PlotEmbed
Output dataset 'output_h5ad' from step 31
AnnData format hdf5
tsne
louvain,sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts
Empty.
Symbol
True
Empty.
Empty.
Right margin
15
Not available.
False
0.1
Empty.
False
Empty.
2D
Empty.
4,4
80
10
False
Step 34: Scanpy PlotEmbed
Output dataset 'output_h5ad' from step 31
AnnData format hdf5
umap
louvain,sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts
Empty.
Symbol
True
Empty.
Empty.
Right margin
15
Not available.
False
0.1
Empty.
False
Empty.
2D
Empty.
4,4
80
10
False
Step 35: Manipulate AnnData
Output dataset 'output_h5ad' from step 31
Rename categories of annotation
louvain
DP-M1,DP-M2,T-mat,DN,DP-M3,DP-L,DP-M4,RBC,Macrophages
Step 36: Scanpy PlotEmbed
Output dataset 'output_h5ad' from step 31
AnnData format hdf5
pca
louvain,sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts
Empty.
Symbol
True
Empty.
Empty.
Right margin
15
Not available.
False
0.1
Empty.
False
Empty.
2D
Empty.
4,4
80
10
False
Step 37: Inspect AnnData
Output dataset 'output_h5ad' from step 31
Key-indexed annotation of variables/features (var)
Step 38: AnnData Operations
Output dataset 'output_h5ad' from step 31
AnnData format
False
Change field names in AnnData observations
index
Flag genes that start with these names
50
True
Keys from obs to copies
Keys from obs to copy 1
louvain
Output dataset 'anndata' from step 35
False
False
False
Step 39: Join two Datasets
Output dataset 'output_tsv' from step 31
4
Output dataset 'var' from step 37
2
Yes
Yes
No
Yes
Step 40: Join two Datasets
Output dataset 'output_tsv' from step 32
4
Output dataset 'var' from step 37
2
Yes
Yes
No
Yes
Step 41: AnnData Operations
Output dataset 'output_h5ad' from step 38
AnnData format
False
Change field names in AnnData observations
Change field names in AnnData observations 1
louvain_0
cell_type
False
index
Flag genes that start with these names
50
False
False
False
False
Step 42: Cut
c1,c2,c3,c4,c11,c5,c6,c7,c8
Tab
Output dataset 'out_file1' from step 39
Step 43: Cut
c1,c2,c3,c4,c11,c5,c6,c7,c8
Tab
Output dataset 'out_file1' from step 40
Step 44: Scanpy PlotEmbed
Output dataset 'output_h5ad' from step 41
AnnData format hdf5
umap
cell_type,sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts
Empty.
Symbol
True
Empty.
Empty.
Right margin
15
Not available.
False
0.1
Empty.
False
Empty.
2D
Empty.
4,4
80
10
False