Getting started
Installation
Reference
Dashboard
delete workspace
export workspace
import workspace
new workspace
Upload
external sources
scanpy dataset
upload file
Preprocess
annotate hb
annotate mito
annotate ribo
batch effect removal
cell cycle scoring
downsample data
filter cells
filter genes
filter highest expr genes
filter highly variable genes
measure gene counts
normalize counts
pca
recipes
regress out
remove genes
run doubletdetection
run scrublet
scale to unit variance
subsample data
Integrate
bbknn
concat
ingest
quick map
scanorama integrate
scanvi integrate
scvi integrate
scvi integrate graphs
scvi metrics
umap
Create CiteSeq model
init model
Create Solo model
init model
Create linear vae
init model
Cluster plots
autoencoder cluster plot
neighbourhood graph
pca graph
tsne graph
variance ratio graph
Differential gene expression
add embeddings
do umap
rank genes groups
show top ranked genes
stat tests
upload marker genes
visualize
Trajectory inference
diffusion pseudotime
draw graph
paga clustering
Spatial transcriptomics
centrality score
co occurance score
interaction matrix
neighbourhood enrichment
ripley score
spatial scatter
Plotly 3D
plot chart
Sidebar
add experiment
download adata
export script
gene format
notes
show preview
species
Tutorials
Clustering
1. Setting up workspace
2. Preprocessing
3. Training an autoencoder
4. Cluster plots
5. Differential Gene Expression
Trajectory Inference
Spatial transcriptomics
Nuwa
tutorials
trajectory_inference
README.md
Trajectory Inference
2024,
Nuwa
Revision
25b3bfb
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Software
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MIT License
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