scloop
Pre-alpha

scloop

Single-cell loop analysis

scloop finds statistically significant loops in single-cell RNA-seq data. It bootstraps the cells, matches loops across bootstrap samples by image homology and topological equivalence, and assigns each loop a confidence score. Loops can also be matched across datasets.

About scloop
$ pip install scloop
import scloop as scl

# Preprocess AnnData
scl.pp.prepare_adata(adata, downsample=True, n_downsample=500)
# Identify statistically significant loops
scl.tl.find_loops(adata)
# Trajectories, gene trends, and features of each loop
scl.tl.analyze_loops(adata)
# Match loops across datasets
scl.tl.match_loops([adata1, adata2])
Analysis overview
Analysis overview · Loops, trajectories, and matching on one dataset.
Loop landscape
Loop landscape · Loop landscape over the embedding.
Loop rank
Loop rank · Loops ranked by bootstrap confidence.

About

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Framework

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Benchmark

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