UMI-tools: Modelling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

By Tom S. Smith, Andreas Heger, Ian M. Sudbery. bioRxiv, 2016

1,542 citations recorded by the source corpus.

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughout sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalised. In particular, sequencing errors in the UMI sequence are often ignored, or else resolved in an ad-hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single cell RNA-Seq datasets. Reproducibility between iCLIP replicates and single cell RNA-Seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package (https://github.com/CGATOxford/UMI-tools).

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0bb5b7afb729814693eeff9beabf08344b65ed90

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Citations in the corpus

zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs (2017, positive): “Lastly, the HEK dataset was used with UMI-tools [25] in (1) "unique" and (2) "directional adjacency" mode with edit distance set to 1.”
Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations (2018, background): “Both problems can be mitigated with careful design and strategies for tolerating errors in barcodes 63–65 .”
Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin (2020, methodology): “UMI-Tools (Smith et al., 2017) was used to collapse UMIs of aligned reads that were within 1nt mismatch of another UMI.”
PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data (2019, methodology): “If the single-cell protocol used UMIs, we performed UMI deduplication using UMI-tools (13) v.0.5.3 (parameters: “–no-sort-output –method unique –gene-tag=XT –per-gene –per-cell”).”