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LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution.

Gianluca Ascolani1, Fabrizio Angaroni2, Davide Maspero2

  • 1Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy. gianluca.ascolani@unimib.it.

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|March 18, 2023
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Summary
This summary is machine-generated.

The LACE 2.0 framework aids in reconstructing cancer evolution by analyzing single-cell sequencing data. It enhances tumor evolutionary history analysis and drug impact assessment using improved computational methods.

Keywords:
Clonal analysisInterfaceLongitudinalShinySingle cell

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Area of Science:

  • Computational biology
  • Cancer research
  • Genomics

Background:

  • Longitudinal single-cell sequencing is crucial for studying cancer evolution in patient-derived models.
  • Robust computational tools are essential for analyzing mutational profiles from single-cell data.
  • Understanding tumor evolution aids in characterizing therapeutic impacts.

Purpose of the Study:

  • To introduce LACE 2.0, an enhanced framework for Longitudinal Analysis of Cancer Evolution.
  • To improve the reconstruction of tumor evolutionary histories from single-cell sequencing data.
  • To facilitate the assessment of therapeutic strategies' impact on cancer progression.

Main Methods:

  • LACE 2.0 incorporates improved data management for variant calling data preprocessing.
  • A reworked inference engine enhances the accuracy of clonal tree reconstruction.
  • Direct integration with public databases streamlines data analysis.

Main Results:

  • LACE 2.0 offers enhanced functionalities for inferring longitudinal clonal trees.
  • The framework provides improved data preprocessing and a more robust inference engine.
  • Connectivity to public databases facilitates comprehensive analysis.

Conclusions:

  • LACE 2.0 is accessible via an interactive Shiny R graphical interface.
  • Users can filter mutations, set inferential parameters, and visualize results.
  • The software is available for download at github.com/BIMIB-DISCo/LACE.