ArticleBMC bioinformatics2019
Barcode identification for single cell genomics.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Fast barcode calling based onPNAS nexus · 2026Article
- Comparative Evaluation of Antibody-Oligonucleotide Conjugation Strategies for Multiplexed Imaging Applications.Laboratory investigation; a journal of technical methods and pathology · 2026Article
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- Single cell RNA-seq: a novel tool to unravel virus-host interplay.Virusdisease · 2024Review
- Single-Cell RNA Sequencing of Bone Marrow Mesenchymal Stem Cells from the Elderly People.International journal of stem cells · 2022Article
- Sequencing the origins of life.BBA advances · 2022Review
- Single-Cell Transcriptome Profiling Simulation Reveals the Impact of Sequencing Parameters and Algorithms on Clustering.Life (Basel, Switzerland) · 2021Article
- Single-Cell Transcriptome Analysis as a Promising Tool to Study Pluripotent Stem Cell Reprogramming.International journal of molecular sciences · 2021Review
- Efficient CRISPR/Cas9 mediated Pooled-sgRNAs assembly accelerates targeting multiple genes related to male sterility in cotton.Plant methods · 2021Article
- Low-complexity and highly robust barcodes for error-rich single molecular sequencing.3 Biotech · 2021Article
- Mapping regulators of cell fate determination: Approaches and challenges.APL bioengineering · 2020Review
- Diversity in biology: definitions, quantification and models.Physical biology · 2020Article
- Rodent models for psychiatric disorders: problems and promises.Laboratory animal research · 2020Review
- Alevin efficiently estimates accurate gene abundances from dscRNA-seq data.Genome biology · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSingle-cell sequencing experiments use short DNA barcode 'tags' to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes.
resultsHere we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Our approach is based on the observation that circularizing a barcode sequence can yield error-free k-mers even when the size of k is large relative to the length of the barcode sequence, a regime which is typical single-cell barcoding applications. This allows for assignment of reads to consensus fingerprints constructed from k-mers.
conclusionWe show that for single-cell RNA-Seq circularization improves the recovery of accurate single-cell transcriptome estimates, especially when there are a high number of errors per read. This approach is robust to the type of error (mismatch, insertion, deletion), as well as to the relative abundances of the cells. Sircel, a software package that implements this approach is described and publically available.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.