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cFinder: definition and quantification of multiple haplotypes in a mixed sample.

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cFinder software automatically detects and quantifies multiple haplotypes in next-generation sequencing data. This tool precisely characterizes sample composition, aiding in diagnosis and therapy decisions for various infections and oncological issues.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) enables genetic analysis of mixed samples.
  • Accurate identification and quantification of multiple haplotypes are crucial for diagnosis and treatment decisions in oncology, infectious diseases, and more.
  • Current software methods for haplotype analysis are often manual, complex, and inefficient.

Purpose of the Study:

  • To develop an automated tool for the detection and quantification of multiple haplotypes within a single sample.
  • To provide precise characterization of sample composition, including variant connections, read counts, and relative occurrence.

Main Methods:

  • Development of a novel software tool named cFinder.
  • Utilized BCR-ABL1 samples with known multiple clones for testing.
  • Simulated NGS reads using GemSIM with multiple haplotypes to assess detection accuracy.

Main Results:

  • cFinder successfully identified all known clones and their abundances in BCR-ABL1 samples, refining existing results.
  • Simulated data showed highly linear detection performance (R² = 0.96).
  • The software reports haplotype-variant connections, read counts, and percentages.

Conclusions:

  • cFinder is an efficient algorithm runnable on standard desktop computers.
  • The tool supports paired-end information and is compatible with various NGS technologies and alignment strategies.
  • cFinder empowers researchers to designate multiple haplotypes and their contribution to a sample without extensive bioinformatics expertise.