Sequencing Data Compression Using Frequency-Domain Key Frames
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Solution Overview
Problem
High amounts of data generated by ion-sensitive field effect transistors (ISFETs) for chemical and biological reactions require efficient compression techniques to reduce memory consumption while maintaining data quality, as existing methods fail to effectively capture biological/chemical events while reducing noise.
Innovation Solution
The method involves converting time-based waveform data from ISFETs into frequency-domain spectrums, generating a key frame, calculating differences between individual spectrums and the key frame, and encoding these differences for compression, allowing for efficient storage and reconstruction of sequencing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If compression techniques are applied to reduce data storage requirements, then memory consumption is reduced, but data quality may deteriorate
Solution Approach 1:
The patent segments the waveform data into multiple frequency components through Fourier transformation. By dividing the data into frequency bins and processing each segment separately, the system can apply compression selectively to different frequency ranges while preserving the most informative components, thus reducing storage requirements while maintaining data quality.
Solution Approach 2:
The patent extracts and removes the DC component (zero-frequency component) from the waveform data before compression. This extraction eliminates redundant information that does not contribute to detecting chemical events, reducing the data volume that needs to be stored while preserving the essential dynamic information contained in the AC components.
Solution Approach 3:
The patent transforms the data from the time domain to the frequency domain by changing the representation parameters. This parameter transformation allows the system to identify and retain only the most significant frequency components that contain information about chemical events, compressing less important components while maintaining overall data quality.
2Measurement precision
If noise reduction is applied to improve data quality, then signal clarity is improved, but loss of information may occur
Solution Approach 1:
The patent applies different processing quality levels to different frequency components. By identifying which frequency bins contain significant signal information versus noise, the system can apply aggressive noise reduction to noise-dominated components while preserving the quality of signal-rich components, thus improving overall data quality without excessive information loss.
Solution Approach 2:
The patent applies noise reduction selectively to specific frequency ranges rather than uniformly across all frequencies. By applying noise filtering only where necessary (in frequency regions dominated by noise rather than signal), the system improves data quality in those regions while minimizing information loss in signal-rich regions.
Data Source
AI summary
Methods, systems, and computer-readable media are disclosed for compression of sequencing data. One method includes receiving waveform data associated with a chemical event occurring on a sensor array, the waveform data including a plurality of time-based waveforms of a corresponding plurality of locations of the sensor array; converting, by at least one processor, each time-based waveform of the waveform data into a frequency-domain spectrum; generating, by the at least one processor, a key frame based on a plurality of the frequency-domain spectrums; calculating, by the at least one processor, for each of the frequency-domain spectrums, a difference between the frequency-domain spectrum and the key frame; and encoding, by the at least one processor, each calculated difference between the frequency-domain spectrum and the key frame.