CIMICE

CIMICE builds a Cancer Progression Markov Chain (CPMC) to model tumor subtypes evolution from single-cell DNA mutational data.

Key Features:

• Mutational Matrix Input: Accepts a boolean matrix representing altered genes in a collection of samples.
• Single-Cell DNA Data Optimization: Specifically written to use the peculiarities of single-cell DNA analysis data for CPMC construction.
• Tumor Phylogenetics Modeling: Constructs a Markov Chain to represent cancer progression and tumor subtypes evolution.

Scientific Applications:

• Cancer Evolution Inference: Models the evolutionary relationships and progression of tumor subtypes using single-cell genomic data.
• Single-Cell DNA Analysis: Processes mutational profiles from single-cell DNA sequencing to reconstruct cancer phylogenies.

Methodology:

CIMICE constructs a Cancer Progression Markov Chain from a boolean mutational matrix representing altered genes across samples obtained by single-cell DNA analysis techniques.