Sequencing Template Construction via Image Spot Merging
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Solution Overview
Problem
Current methods for processing and correlating multiple images of nucleic acid molecules to accurately determine nucleotide sequences are inefficient and prone to errors, particularly in sequencing platforms where precise alignment and noise interference are challenges.
Innovation Solution
A method and device for constructing a sequencing template based on images by combining and merging overlapping spots from multiple images, utilizing image registration techniques and spot detection algorithms to create a comprehensive spot set that accurately reflects the nucleotide composition, facilitating accurate base calling and sequence identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple images of nucleic acid molecules are processed and correlated to determine nucleotide sequences, then sequencing information can be acquired, but alignment precision deteriorates and noise interference increases
Solution Approach 1:
The patent divides the sequencing template construction into multiple stages: first constructing a preliminary template from initial images, then iteratively refining it by comparing with subsequent images. This segmentation allows systematic processing of multiple images while maintaining alignment precision through staged verification.
Solution Approach 2:
The patent implements feedback mechanisms by comparing constructed templates with new images and adjusting the template accordingly. The system uses quality scores and comparison results to determine whether to accept or reject new image data, thereby maintaining alignment precision while acquiring sequencing information.
2Measurement precision
If multiple images are processed to construct sequencing template, then sequencing accuracy can be improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary template construction from initial images before processing subsequent images. This preliminary action establishes a baseline template that can be efficiently compared with new images, reducing the computational complexity of processing each individual image while maintaining overall sequencing accuracy.
Solution Approach 2:
The patent processes images in batches and uses quality scores to determine the extent of processing required for each image. Not all images need to be fully processed to the same degree, allowing the system to achieve sufficient sequencing accuracy with reduced processing time by applying partial action to lower-quality images.
3Quantity of substance
If spot detection and merging is performed across multiple images, then comprehensive nucleotide composition can be captured, but noise interference and false alignments increase
Solution Approach 1:
The patent uses quality scores generated during spot detection and merging to feedback control the process. Images or spots with low quality scores are rejected or given reduced weight, thereby reducing noise interference while maintaining comprehensive nucleotide composition coverage through selective inclusion of high-quality data.
Solution Approach 2:
The patent converts potential harmful noise and false alignments into beneficial filtering criteria by using quality scores to identify and exclude erroneous spots. The harmful effect of noise is transformed into a useful mechanism for selecting only reliable spots, thereby improving the signal-to-noise ratio in the final sequencing template.
Data Source
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AI summary
A method for constructing a sequencing template based on an image, a device, and a system. The image comprises first, second, third and fourth images of one same field of view corresponding to base base extensions of A/U, T, G, and C respectively; the first, second, third and fourth images respectively comprise images M1 and M2, images N1 and N2, images P1 and P2, and images Q1 and Q2; the method for constructing the sequencing template comprises: combining any two of the images M1, M2, N1, N2, P1, P2, Q1, and Q2 to perform bright spot matching, and enabling the images M1, N1, N2, P1, P2, Q1, and Q2 to participate in the combination for at least one time to obtain a plurality of combined images comprising first coincident bright spots (S10), two or more bright spots whose distances are less than that of a first predetermined pixel on the combined images being one first coincident bright spot; and merging the first coincident bright spots on the plurality of combined images to obtain a bright spot set corresponding to the sequencing template (S20). The method can effectively obtain the bright spot set corresponding to a nucleic acid template.