3D Grid Classification for Horizontally Transferred Gene Detection
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Solution Overview
Problem
Current methods for detecting horizontally transferred genes in microbial genomes lack sensitivity and efficiency, particularly in identifying subtle variations in oligonucleotide composition and mapping genomic regions independently, leading to suboptimal detection of compositionally distinct regions.
Innovation Solution
A computer-implemented method that transforms genomic fragments into three-dimensional space using reference points, classifies grids as majority, minority, or mixed based on quartile values and genome-specific thresholds, and assesses distance ratios to identify horizontally transferred genes with associated confidence values, enabling more sensitive and efficient detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods compare oligonucleotide compositions of specific sub regions with overall genome compositions, then the detection process is simple, but the detection sensitivity is low
Solution Approach 1:
The patent transforms genomic fragments into three-dimensional space using oligonucleotide composition features as dimensions. This dimensional transformation allows for more nuanced comparison and detection of HGT regions by visualizing compositionality in 3D space rather than simple linear comparison, thereby improving detection sensitivity while maintaining computational feasibility through geometric operations.
Solution Approach 2:
The patent divides the genome into multiple non-overlapping genomic fragments and processes each fragment independently through the 3D transformation and grid classification pipeline. This segmentation enables localized detection of HGT regions with high sensitivity while the modular approach keeps the overall method manageable despite the increased analytical depth.
2Measurement precision
If recent methods heuristically capture oligonucleotide compositional diversity, then detection sensitivity is improved, but computational complexity increases
Solution Approach 1:
The patent changes the parameter space by transforming genomic fragments into 3D coordinates based on oligonucleotide composition frequencies. This parameter transformation converts complex compositional analysis into geometric operations in 3D space, improving detection sensitivity while reducing computational burden through efficient spatial operations and grid-based classification.
Solution Approach 2:
The patent introduces 3D space coordinates as an intermediary representation between raw oligonucleotide composition data and HGT detection results. This intermediary transformation layer simplifies the detection process by converting compositional complexity into spatial relationships that can be efficiently analyzed through grid classification and distance calculations.
3Measurement precision
If genomic regions are mapped independently, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the genome into non-overlapping fragments and processes each fragment independently through the 3D transformation and grid classification pipeline. This independent processing improves detection accuracy for each region while the parallelizable nature of fragment-based processing allows for efficient computation that mitigates the time cost.
Solution Approach 2:
The patent performs preliminary transformation of all genomic fragments into 3D space and pre-classifies them into grids before conducting HGT detection. This preliminary organization of data into structured 3D grids enables faster subsequent analysis and reduces processing time during the actual detection phase while maintaining independent mapping accuracy.
Data Source
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AI summary
Method(s) and system(s) for identifying horizontally transferred genes are described herein. The method includes defining a cuboid in a three dimensional space, wherein the cuboid includes fragment points corresponding to the genomic fragments belonging to a plurality of sequenced microbial genomes, and dividing the cuboid into a plurality of grids. The method further includes selecting one or more grids corresponding to a selected genome and classifying each of the selected grids as one of majority, minority, and mixed grids, based on number of fragment points corresponding to the selected genome in each of the selected grids. Further, at least one genomic fragment from the minority and the mixed grids is identified as the horizontally transferred gene based on a distance ratio assessment.