Transcriptome Compression Ratio Analysis Without Normalization
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Solution Overview
Problem
Existing methods for analyzing transcriptome data require normalization, which can be cumbersome and may obscure underlying biological information.
Innovation Solution
Analyze sequence data by calculating the compression ratio without normalization, using variables such as cultivation time, substance administration, and environment, and create a graph with the compression ratio as a second axis to analyze biological information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If normalization is performed on transcriptome data, then data comparability is improved, but analysis complexity and information loss increase
Solution Approach 1:
The invention extracts and utilizes the compression ratio as a standalone feature to represent biological state information, eliminating the need for normalization operations. By taking out the compression ratio from the data processing pipeline, the system achieves data comparability without performing complex normalization steps.
Solution Approach 2:
The invention creates a simplified representation of transcriptome data through compression, where the compression ratio serves as a copy that captures essential biological information. This compressed representation allows for direct comparison without requiring the full normalized data processing pipeline.
2Measurement precision
If normalization is performed on transcriptome data, then data comparability is improved, but underlying biological information may be obscured
Solution Approach 1:
The invention converts the potential harm of data variability into a benefit by using compression ratios to highlight meaningful patterns. Instead of normalizing away differences, the system uses compression ratios to emphasize biological state differences, turning what could be seen as noise into useful diagnostic information.
Solution Approach 2:
The invention changes the parameter of interest from normalized expression values to compression ratios. This parameter transformation allows the system to preserve biological information while achieving comparability, as compression ratios naturally reflect biological state differences without requiring normalization operations.
3Ease of operation
If compression ratio is calculated without normalization, then analysis simplicity is improved, but data comparability may be compromised
Solution Approach 1:
The compression ratio calculation is self-service in that it automatically adapts to the input data without requiring external normalization parameters or operations. The compression algorithm inherently handles data comparability through its own optimization processes, eliminating the need for separate normalization steps.
Solution Approach 2:
The compression ratio serves multiple functions simultaneously: it provides data comparability, captures biological information, and simplifies analysis. This multi-functional approach eliminates the need for separate normalization and analysis steps, making the system both simple and precise.
Data Source
AI summary
[Problem] To provide a method for analyzing a target organism, which can analyze data from a compression ratio without normalization, and a method for acquiring a graph from which various types of biological information can be analyzed. [Solution] A method for analyzing a target organism, comprising compression ratio fluctuation examination step of obtaining a compression ratio of sequence data on the target organism for each variable related to the target organism, wherein the compression ratio fluctuation examination step includes: a sequence data acquisition step of obtaining a plurality of pieces of sequence data based on the target organism for each of the variables; and a compression ratio calculation step of compressing the plurality of pieces of sequence data to obtain a data compression ratio.