FalseAmpHunter: A Bioinformatics Pipeline for Detecting and Characterizing False Amplicons in PCR

Polymerase chain reaction (PCR) is a widely used molecular biology technique; however, it remains highly susceptible to non-specific primer binding, particularly in genomic regions with extensive sequence similarity. Such off-target amplification can generate false amplicons that are difficult to detect using conventional quality control methods and may lead to erroneous downstream interpretation. Here, we present FalseAmpHunter, a pipeline designed to detect, assemble, and characterize false amplicons from paired-end next-generation sequencing (NGS) data generated from PCR amplification. FalseAmpHunter reconstructs candidate amplicons, maps them genome-wide, evaluates primer-binding orientation, and distinguishes true target amplification from paralog-driven off-target products and sequencing artifacts. We validated FalseAmpHunter using a synthetic dataset derived from in silico PCR of paralogous olfactory receptor (OR) genes. The pipeline successfully identified both the intended target amplicon and false amplicons originating from paralogous loci, while excluding a random decoy control. FalseAmpHunter provides a systematic and transparent solution for investigating false PCR amplification events and is applicable to assay development, primer validation, and troubleshooting of targeted sequencing experiments. By transforming raw sequencing data into interpretable genomic evidence, it enhances confidence in PCR-based analyses, particularly in paralog-rich genomic contexts. The pipeline is accessible online at: https://github.com/xoaib4/FalseAmpHunter.