DCLEAR

DCLEAR reconstructs single-cell lineage trees from CRISPR-edited barcodes to infer cellular ancestry and developmental trajectories.

Key Features:

• Distance Matrix Estimation: Two novel methods estimate distance matrices from observed edited barcodes and report improved relationships compared with Hamming distance.
• Tree Reconstruction from Distance Matrices: Algorithms reconstruct lineage trees from the estimated distance matrices.
• Input Data: Operates on observed edited barcodes from individual cells produced by CRISPR-based gene editing.
• Implementation: Provided as an R package implementation.

Scientific Applications:

• Developmental Biology: Enables reconstruction of cellular lineages to study developmental trajectories and cell fate decisions.
• Cancer Research: Facilitates inference of clonal relationships and tumor cell lineage dynamics.
• Regenerative Medicine: Supports analysis of differentiation and proliferation patterns relevant to tissue regeneration.

Methodology:

Estimates distance matrices between single-cell CRISPR-edited barcodes using two novel methods and then reconstructs lineage trees from those distance matrices using tree reconstruction algorithms.