PHLOWER

PHLOWER infers complex, multi-branching cell differentiation trajectories from single-cell multimodal data by leveraging the harmonic component of the Hodge decomposition on simplicial complexes.

Key Features:

• Hodge Laplacian decomposition: PHLOWER decomposes the Hodge Laplacian to infer trajectory embeddings from flows of cell differentiation.
• Simplicial complex representation: PHLOWER uses simplicial complexes to generate natural representations of cell differentiation that facilitate estimation of underlying differentiation trees.
• Transcription factor identification: PHLOWER identifies transcription factors regulating off-target cells in kidney organoids.

Scientific Applications:

• Complex tree inference: PHLOWER enables inference of complex branching differentiation trees from single-cell multimodal data.
• Kidney organoid analysis: PHLOWER analyzes kidney organoid multimodal and spatial single-cell data to identify transcriptional regulators.

Methodology:

PHLOWER applies the harmonic component of the Hodge decomposition on simplicial complexes to infer trajectory embeddings from single-cell multimodal data, which facilitates estimation of underlying differentiation trees.