Approximate any single cell data set, saving >99% of memory and runtime.
Project description
scquill
Approximate any single cell data set, saving >99% of memory and runtime.
Approximating a single cell data set
import scquill
q = scquill.Compressor(
filename='myscdata.h5ad',
output_filename='myapprox.h5',
celltype_column="cell_annotation",
)
q()
Exploring an approximation
To load an approximation:
import scquill
app = scquill.ApproxAnnData(
filename='myapprox.h5',
)
To show a neighborhood plot:
scquill.pl.neighborhoodplot(app, ['gene1', 'gene2', 'gene3'])
To show embeddings of cell neighborhoods, similar to single-cell UMAPs:
scquill.pl.embedding(app, ['gene1', 'gene2', 'gene3'])
MORE TO COME
Authors
Fabio Zanini @fabilab
Project details
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