How Error Correction Affects PCR Deduplication: A Survey Based on UMI Datasets of Short Reads

Abstract Next-Generation Sequencing (NGS) data is widely utilised for various downstream applications in bioinformatics, and numerous techniques have been developed for PCR-deduplication and error-correction to eliminate bias and errors introduced during the sequencing. This study first-time provides a joint overview of recent advances in PCR-deduplication and error-correction on short reads. In particular, we utilise UMI-based PCR-deduplication strategies and sequencing data to assess the performance of the solely-computational PCR-deduplication approaches and investigate how error correction affects the performance of PCR-deduplication. Our survey and comparative analysis reveal that the deduplicated reads generated by the solely-computational PCR-deduplication and error-correction methods exhibit substantial differences and divergence from the sets of reads obtained by the UMI-based deduplication methods. The existing solely-computational PCR-deduplication and error-correction tools can eliminate some errors but still leave hundreds of thousands of erroneous reads uncorrected. All the error-correction approaches raise thousands or more new sequences after correction which do not have any benefit to the PCR-deduplication process. Upon these discoveries, we offer practical suggestions to enhance the existing computational approaches for improving the quality of short-read sequencing data.