Probabilistic Adapter Trimming for Faster Sequencing Analysis
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Solution Overview
Problem
Existing adapter trimming methods in next-generation sequencing are inefficient, inaccurate, and computationally costly, often requiring hours to process and failing to reliably distinguish between adapter sequences and actual sequencing data, especially when dealing with indels and unbalanced nucleotide diversity.
Innovation Solution
The method employs random matching and probability distribution, such as binomial distribution, to determine adapter positions directly from sequencing reads in binary format, reducing computational complexity and time by eliminating the need for additional indel processing and alignment in standard formats, and utilizing FPGA and dedicated processors for real-time processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional adapter trimming methods are used, then adapter sequences can be identified, but computational time increases to hours and processing efficiency decreases
Solution Approach 1:
The patent replaces traditional mechanical alignment and indel processing systems with a probability-based computational model. By using binomial distribution to calculate adapter presence probabilities directly from sequencing reads in binary format, the system eliminates the need for time-consuming alignment algorithms and indel correction processes, reducing computation time from hours to minutes while maintaining trimming accuracy.
Solution Approach 2:
The patent changes the fundamental parameters of adapter detection from sequence alignment-based metrics to probability distribution-based metrics. By modeling adapter presence using binomial distribution with parameters derived from nucleotide diversity and read composition, the system transforms the computational approach from exhaustive search to probabilistic estimation, significantly reducing processing time.
2Measurement precision
If traditional alignment methods are used, then adapter positions can be determined, but device complexity and processing requirements increase
Solution Approach 1:
The patent extracts and removes the complex alignment and indel processing steps from the adapter detection workflow. By directly calculating adapter presence probabilities from sequencing reads using probability distributions, the system separates and eliminates unnecessary computational complexity while retaining the essential function of accurate adapter position determination.
Solution Approach 2:
The patent substitutes complex mechanical alignment algorithms with a probabilistic model that operates directly on sequencing read data in binary format. This replacement reduces device complexity by eliminating the need for sophisticated alignment software and processing pipelines while maintaining determination accuracy.
3Reliability
If comprehensive indel processing is performed, then sequencing accuracy improves, but computational time and processing cost increase
Solution Approach 1:
The patent performs preliminary action by calculating adapter presence probabilities before traditional indel processing would be applied. By using probability distributions to predict adapter positions and trim adapters in advance, the system prepares sequencing data for downstream analysis without requiring subsequent complex indel correction processes, thus maintaining reliability while improving throughput.
Solution Approach 2:
The patent skips the time-consuming indel processing step by directly addressing adapter contamination through probability-based detection and trimming. The system rushes through the processing pipeline by eliminating unnecessary intermediate steps and focusing computation only on the essential adapter detection task, thereby maintaining data reliability with higher productivity.
Data Source
AI summary
Provided herein are system, apparatus, method, and/or computer program product embodiments, and/or combinations and sub-combinations thereof which enables adapter trimming and/or adapter determination during sequencing data analysis. Based on a plurality of match scores, one or more sequence alignments are selected. Each of the plurality of match scores may be based on a first number of matched bases and a second number of total bases. First and second consensus positions are generated from the one or more sequencing alignments. A trimming position is determined based on the first and second consensus positions and a first and second consensus match score.