Investigating the performance of Oxford Nanopore long-read sequencing with respect to Illumina microarrays and short-read sequencing

Oxford Nanopore Technologies (ONT) long-read sequencing (LRS) has emerged as a promising tool for genomic analysis, but comprehensive comparisons with established platforms across diverse datasets remain limited. We present a multi-platform benchmark using 14 human genomes sequenced with ONT LRS, Illumina short-read sequencing (SRS), and Illumina microarrays. Our study evaluates LRS performance for various genetic variants across genomic contexts, while also examining the impact of experimental factors such as multiplexing, depth, and read length. In high-complexity regions, LRS demonstrated competitive yet slightly lower accuracy than SRS for SNV detection (F-measure: 0.954 vs. 0.968), with performance gaps narrowing in low-complexity regions. For indel detection, LRS showed robust performance for small indels (1-5bp) in high-complexity regions (F-measure: 0.869), but accuracy decreased significantly in low-complexity regions and for larger indels. LRS identified 2.86 times more structural variants than SRS, with superior detection of large-scale variations. Sequencing depth strongly influenced variant calling performance across all variant types, while multiplexing effects were minimal after controlling for depth. Our findings provide valuable insights for optimising ONT LRS applications in genomic research and clinical diagnostics.