Genomic Data Visualization via Linked Chromosomal Maps
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Solution Overview
Problem
Current genomic analysis techniques, such as array CGH, struggle to accurately represent in vivo chromosomal structures in cancer cells, missing structural lesions like derivative and marker chromosomes, and cannot determine the orientation and relative positions of copy number variations, which are crucial for understanding genomic instability in cancer.
Innovation Solution
A computer-implemented method that integrates genomic array data and cytogenetic data to create dynamically linked chromosomal and cytogenetic maps, allowing users to correlate copy number changes with structural alterations by synchronizing positional indicators across both maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If array CGH is used to measure copy number variations, then copy number changes can be detected, but the orientation and relative positions of each copy cannot be determined
Solution Approach 1:
The patent combines array CGH data with cytogenetic data (karyotyping, FISH) into an integrated analysis system. This merging allows the system to leverage the quantitative copy number precision of array CGH while simultaneously capturing the structural orientation and positional information from cytogenetic methods, thereby resolving the information loss limitation of array CGH alone.
Solution Approach 2:
The patent introduces a reference genome assembly as an intermediary framework that maps and integrates data from both array CGH and cytogenetic sources. This reference framework serves as a mediator that reconciles the different data types, allowing orientation and position information to be inferred by comparing experimental data against the known reference structure.
2Ease of operation
If aCGH data is plotted across normal reference chromosomes, then copy number changes can be visualized, but in vivo chromosomal structures in cancer cells are not represented
Solution Approach 1:
The patent applies local quality by allowing different representation methods for different chromosomal regions. Normal reference chromosome plots are used for regions with standard architecture, while cytogenetic data and alternative visualizations are employed for regions with structural abnormalities, ensuring each region is represented according to its actual in vivo structure.
Solution Approach 2:
The patent implements dynamic visualization that can switch between normal reference chromosome views and aberrant chromosome structures based on the detected abnormalities. The system adaptively reconfigures the display to show derivative chromosomes, translocations, and other structural lesions in their actual structural context rather than forcing them into normal reference frameworks.
3Measurement precision
If standard cytogenetic assays are used to identify balanced translocations and marker chromosomes, then structural lesions can be detected, but copy number changes and their integration with array data become difficult
Solution Approach 1:
The patent creates a universal analysis platform that can handle multiple data types (array CGH, karyotyping, FISH) and multiple analysis functions (copy number detection, structural lesion identification, integration) within a single integrated system. This multi-functional approach eliminates the need for separate analysis pipelines for different data types, reducing the overall complexity despite the diverse inputs.
Data Source
AI summary
A computer-implemented method for viewing experimental data is provided. In certain embodiments the method comprises: a) inputting genomic array data and cytogenetic data into a computer memory; and b) producing a graphical user interface comprising: i) a chromosomal map of the genomic array data comprising a first positional indicator that indicates a position on the chromosomal map; and ii) a cytogenetic map of the cytogenetic data comprising a second positional indicator that indicates a position on the cytogenetic map.