The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy
Open accessAbstract
Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput 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 formalized. 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 data sets. 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.
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Cites
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“Islam et al. (2014) previously identified the issue of sequencing errors and proposed removing UMIs whose counts fall below a threshold of 1% of the mean of all nonzero UMIs at the lo-cus, a method we refer to as percentile .”
InfluentialiCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution
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Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin
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Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer
Fu, A., Yao, B., Dong, T., Chen, Y., Yao, J., Liu, Y., Li, H., Bai, H., Liu, X., Zhang, Y., et al. (2022) · Cell · doi:10.1016/j.cell.2022.02.027 · Cited by 981
Metadata
- Authors
- Smith, T., Heger, A., & Sudbery, I.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2017-01-18
- Volume
- 27
- Issue
- 3
- Pages
- 491-499
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- OpenAlex
- W2952109315
- Cited by
- 2,143
- References
- 10
- Type
- posted content
- Language
- en
- Open access
- bronze
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