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Benchmarking DNA barcode decoding strategies under high error rates
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DOI：10.1186/s12859-026-06540-x.png)
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Abstract
En 中文
DNA barcoding enables multiplexed identification of biomolecules in pooled sequencing experiments, with broad applications including spatial transcriptomics. Photolithographic synthesis of high-density barcode arrays achieves library sizes exceeding $$10^5$$ unique sequences but introduces error rates of 10–20% per nucleotide through substitutions, insertions, and deletions. Classical error-correcting codes cannot scale to such library sizes while maintaining robust error correction under these conditions. We benchmarked three computational barcode decoding approaches—Columba (FM-index-based lossless alignment), QUIK (k-mer filtering with GPU acceleration), and RandomBarcodes (trimer-based triage with GPU parallelization)—across simulated and empirical datasets. Simulations spanned barcode lengths of 28–36 nt, library sizes of 21,000–85,000 barcodes, and error rates of 9–32%. Real sequencing data were generated from photolithographically synthesized arrays at three printing density levels. Under medium error rates (~23%), QUIK achieved the highest recall (87–89%) while maintaining precision $$>99.5\%$$, outperforming RandomBarcodes (recall 56%, precision $$>99.8\%$$) and Columba (recall 35%, precision 98–100%). QUIK demonstrated superior scalability, processing 59,620 reads/second on a single GPU compared to RandomBarcodes (68 reads/second) and Columba (1550 reads/second with 8 CPU threads). Barcode length strongly influenced accuracy: 34-nt barcodes enabled 75% recall at 99.97% precision with QUIK, compared to 60% recall with 32-nt barcodes. On real data from a 42,000-spot subarray with 36-nt barcodes, QUIK managed a 57% assignment rate with perfect precision, versus 52% (Columba, precision 99.96) and 50% (RandomBarcodes, precision 99.82). QUIK provides the optimal balance of speed, accuracy, and scalability for high-density spatial transcriptomics applications under realistic synthesis error conditions. Barcode lengths $$\ge 34$$ nt are recommended for applications requiring $$>75\%$$ read recovery at $$>99.9\%$$ precision.
Keywords:
Barcode calling
High-throughput sequencing
Benchmarking
Error correction
Demultiplexing
Photolithography
Spatial transcriptomics
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