scDNA: Single Cell DNA analysis software toolkit for subclonality discovery and assessment.

Area of Science:

• Genomics
• Cancer Biology
• Computational Biology

Background:

• Single-cell multi-omics technologies enable detailed analysis of genotype-immunophenotype relationships and clonal evolution in cancer.
• Understanding subclonal dynamics and genetic drivers is crucial for cancer progression insights.
• Accessible computational tools are needed to process and analyze the growing volume of single-cell data.

Purpose of the Study:

• To introduce the scDNA package, a user-friendly computational tool for single-cell DNA analysis.
• To provide rapid analysis of single-cell molecular profiling data.
• To facilitate sample quality control, subclonal architecture determination, and mutation trajectory analysis.

Main Methods:

• Development of the scDNA package for single-cell DNA analysis.
• Implementation of functionalities for quality control, demultiplexing, copy number variation analysis, and mutation ordering.
• Vignette-based demonstration using hematopoiesis datasets.

Main Results:

• The scDNA package offers rapid analysis of single-cell molecular profiling.
• It provides diagnostic summaries, subclonal architecture, and mutation trajectory analysis.
• Demonstrated utility in hematopoiesis datasets, showcasing its application in understanding clonal evolution.

Conclusions:

• The scDNA package is a modular and user-friendly framework for single-cell DNA analysis.
• It supports various downstream analyses and integrates with existing software pipelines.
• Facilitates deeper insights into genotype-immunophenotype relationships and cancer progression.