DETECTING MUTATIONS AND PLOIDY IN CHROMOSOMAL SEGMENTS

Smart overview of the Invention

The invention introduces advanced methods, systems, and computer-readable mediums designed to detect the ploidy of chromosomal segments and single nucleotide variants. These tools offer significant applications in identifying cancer and chromosomal abnormalities in a fetus. The technology leverages allele frequency data and high-throughput nucleic acid sequencing to enhance the accuracy of detecting such genetic variations.

Background

Copy number variation (CNV) is a key contributor to genomic structural variation, involving duplications and deletions of sequences. These variations are linked to various conditions, including complex genetic diseases and cancer. CNVs are categorized into two types: common copy number polymorphisms (CNPs) and rare, large CNVs. The latter are often associated with neurocognitive diseases and can significantly affect gene copy numbers in cancer cells, influencing disease susceptibility and progression.

Methodology

The invention provides a method to determine chromosomal ploidy by analyzing allele frequency data at polymorphic loci. The process involves generating phased allelic information, calculating individual and joint probabilities for different ploidy states, and selecting the best fit model for chromosomal ploidy. This method utilizes nucleic acid sequence data, correcting for errors such as allele amplification efficiency bias and contamination to ensure accuracy.

System Components

The system comprises an input processor for receiving allele frequency data, a modeler for generating phased allelic information and probabilities, and a hypothesis manager for selecting the best fit ploidy model. The modeler corrects errors in allele frequency data and considers linkage between loci to refine probability calculations. This system can be integrated with nucleic acid sequencing technologies to enhance ploidy detection.

Applications

This invention's methods and systems can significantly improve the early detection of cancer and prenatal chromosomal abnormalities, potentially reducing the need for invasive procedures. By providing more precise diagnosis capabilities, the technology can aid in better disease management and treatment planning, thereby improving patient outcomes and reducing treatment-related side effects.