Exon sequencing mutation detection algorithm based on PCR matching.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Second-generation sequencing technologies have increased the detection of DNA sequence variations.
• Exon sequencing is crucial for analyzing cancer genes and identifying disease status through gene variants.
• Polymerase chain reaction (PCR) sequencing effectively captures exon sequences, including primer sequences for positional determination.

Purpose of the Study:

• To develop and present a new matching algorithm based on PCR primer sequences for accurate DNA sequence analysis.
• To improve the efficiency and accuracy of identifying DNA variations, such as single nucleotide polymorphisms (SNPs) and insertions/deletions (Indels).

Main Methods:

• A novel matching algorithm utilizing PCR primer sequences was developed.
• Sequencing data was sorted and redundant sequences were counted to minimize matching operations.
• The algorithm matches sequenced DNA with PCR primer sequences for precise localization and variation identification.

Main Results:

• The proposed algorithm effectively sequences PCR primer positions and identifies key sequence segments.
• Optimized matching reduced computational load and increased the speed of variation detection.
• Accurate DNA positional matching and rapid identification of sequence variations were achieved.

Conclusions:

• The PCR primer sequence matching method outperforms traditional approaches in matching numerous sequences and detecting more variations.
• This method demonstrates a high recall rate, enhancing the reliability of variant identification.
• The algorithm offers a more efficient and sensitive approach to analyzing DNA sequence variations in genomic studies.