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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Related Experiment Video

Updated: Jun 26, 2025

Lineage Tracing and Clonal Analysis in Developing Cerebral Cortex Using Mosaic Analysis with Double Markers MADM
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Scuphr: A probabilistic framework for cell lineage tree reconstruction.

Hazal Koptagel1,2, Seong-Hwan Jun3, Joanna Hård4

  • 1School of EECS, KTH Royal Institute of Technology, Stockholm, Sweden.

Plos Computational Biology
|May 9, 2024
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Summary
This summary is machine-generated.

Scuphr reconstructs cell lineage trees using DNA sequencing data, offering faster and more accurate analysis. This method addresses common challenges in single-cell sequencing for developmental and cancer research.

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Area of Science:

  • Genomics
  • Computational Biology
  • Developmental Biology

Background:

  • Cell lineage tree reconstruction is crucial for understanding development, differentiation, and cancer.
  • Single-cell sequencing technologies offer high-resolution insights into cellular processes.
  • Existing methods face challenges with noise and accuracy in complex biological systems.

Purpose of the Study:

  • To introduce Scuphr, a novel computational method for cell lineage tree reconstruction.
  • To utilize both bulk and single-cell DNA sequencing data for improved accuracy.
  • To address and incorporate common errors in single-cell DNA sequencing data.

Main Methods:

  • Scuphr employs a distance-based approach to infer relationships between cells.
  • It utilizes the neighbor-joining algorithm for phylogenetic tree reconstruction.
  • The method incorporates handling of allelic dropouts and amplification errors inherent in single-cell DNA sequencing.

Main Results:

  • Scuphr demonstrates faster analysis compared to state-of-the-art methods due to its parallel design.
  • The method achieves higher accuracy in reconstructing cell lineage trees.
  • Robustness was validated using diverse synthetic datasets and a biological dataset of 18 cells.

Conclusions:

  • Scuphr provides an efficient and accurate solution for cell lineage tree reconstruction.
  • The method is robust and capable of handling technical challenges in single-cell DNA sequencing.
  • Scuphr advances the analysis of cellular development and disease progression using genomic data.