Metagenomic parasite detection trap: prevention with an Excel filter sheet based on CIGAR values

Abstract

False positive mapping in metagenomic microbial detection is an underestimated and under-explored concern. It is more critical among parasites than among bacteria and viruses in metagenomic samples. We created an Excel filter sheet to minimize false mapping for metagenomic parasites, based on ratios of the first and last values of S, H and M in the CIGAR string retrieved from Minimap2 mapping. By applying a filter of S/M < 0.3, 88% to 95% of reads ‘mapped’ to ten pathogenic reference parasite sequences were eliminated from the Oxford Nanopore Sequencing data of three macaque stool samples. CZID annotation of the remaining reads detected Entamoeba , Cyclospora , Toxoplasma and Giardia . The majority of the eliminated ‘mapped’ parasite reads were bacteria. The sensitivity of the Minimap2 – S/M < 0.3 filter is between 56.12% and 74.92% for the metagenomic data, and 86% (43/50) for 50 randomly downloaded annotated parasite sequences from NCBI. Our Excel filter sheet provides a temporary solution for false positive mapping in metagenomic parasite detection. We advocate tools that would automate read filtration for metagenomic parasite detection based on the principle reported herein, so that workers unbeknownst to this false positive trap could avoid misinformed downstream analysis and public health interventions.

The authors' abstract, as published at the source. Scientific Reports, 2026 · DOI ↗