Analyte Imaging Data Preparation for Low-Volume Color Storage
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Solution Overview
Problem
Existing methods for identifying nucleic acid sequences and analytes using multiple coloring rounds generate large data volumes that require significant computing effort and memory, leading to high acquisition and maintenance costs, and limit sample throughput due to SSD hard drive limitations and inefficient data processing.
Innovation Solution
A method that involves using markers specific for certain analytes, detecting images with a camera, and assessing data points for candidate information, eliminating non-relevant color information, and combining neighboring pixels to reduce data volume, utilizing machine learning models for efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all color information from multiple coloring rounds is stored for analysis, then complete analyte identification is achieved, but data storage requirements and processing time increase significantly
Solution Approach 1:
The patent extracts and stores only the color information from data points that are identified as containing markers (colored signals), while discarding color information from data points without markers. This selective extraction significantly reduces the total data volume while preserving all necessary information for analyte identification, directly resolving the contradiction between complete analysis and data management.
Solution Approach 2:
The patent segments the image data into individual data points (pixels or pixel groups) and processes them independently to determine whether they contain markers. By segmenting and filtering at the data point level before storage, the system reduces overall data volume while maintaining the integrity of relevant analytical information.
2Speed
If SSD hard drives are used to store large data volumes, then rapid data access is enabled, but the limited number of write cycles is quickly reached
Solution Approach 1:
By extracting and storing only the color information from data points containing markers rather than storing all image data, the patent dramatically reduces the total data volume written to SSD drives. This reduction extends the operational lifespan of the storage system by spreading write cycles over a longer period, while maintaining rapid access speeds for the reduced dataset.
3Measurement precision
If large data volumes are processed, then complete color information analysis is achieved, but computing effort and processing time increase significantly
Solution Approach 1:
The patent performs preliminary assessment of each data point to determine whether it contains markers before storing and processing color information. This preliminary filtering action eliminates unnecessary processing of background and non-marker regions, significantly reducing total computing effort and processing time while maintaining complete analysis of relevant analyte information.
Solution Approach 2:
By extracting only the color information from marker-containing data points for subsequent processing, the patent reduces the volume of data requiring computational analysis. This extraction before processing step maintains analytical completeness for relevant data while dramatically reducing processing time and computational resources required.
4Loss of information
If all pixels are processed individually, then complete color information is captured, but data volume and processing complexity increase
Solution Approach 1:
The patent merges adjacent pixels into data points (groups of pixels representing the same location) to reduce the total number of individual processing units. This merging maintains color information completeness for analyte identification while reducing data volume and processing complexity through the reduced number of data points that require evaluation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Significantly reduces data storage requirements, allowing for rapid and efficient processing of color information, minimizing memory capacity and write cycles, while maintaining high sample throughput.
Implementation Method 1
The markers are made up of oligonucleotides and dyes coupled thereto, which are generally fluorescent dyes
Data Source
AI summary
A method for preparing data for identifying analytes in a sample, in which in an experiment one or more analytes are colored with markers in multiple coloring rounds, the markers in each case being specific for a certain set of analytes, detecting the multiple markers using a camera, which for each coloring round generates at least one image containing multiple pixels and color values assigned thereto, the image including colored signals and uncolored signals, wherein a colored signal is a pixel having a color value that originates from a marker, and an uncolored signal is a pixel having a color value that is not based on a marker, and storing the color information of the particular coloring rounds for evaluating the color information.