An error correction strategy for image reconstruction by DNA sequencing microscopy

Abstract

By pairing adjacent molecules in situ and then mapping these pairs, DNA microscopy could substantially reduce the workload in spatial omics methods by directly inferring geometry from sequencing data alone. However, experimental artifacts can lead to errors in the adjacency data, which distort the spatial reconstruction. Here we describe a method to correct two such errors: spurious crosslinks formed between any two nodes, and fused nodes that are formed out of multiple molecules. We build on the principle that spatially close molecules should be connected and show that these errors violate this principle, allowing for their detection and correction. Our method corrects errors in simulated data, even in the presence of up to 20% errors, and proves to be more efficient at removing errors from experimental data than a read count filter. Integrating this method in DNA microscopy will substantially improve the accuracy of spatial reconstructions with lower data loss.