ArticleBMC bioinformatics2016
Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Extracting, filtering and simulating cellular barcodes using CellBarcode tools.Nature computational science · 2024Article
- Clonal barcoding with qPCR detection enables live cell functional analyses for cancer research.Nature communications · 2022Article
- ngsComposer: an automated pipeline for empirically based NGS data quality filtering.Briefings in bioinformatics · 2021Article
- Lineage barcoding in mice with homing CRISPR.Nature protocols · 2021Article
- A committed tissue-resident memory T cell precursor within the circulating CD8+ effector T cell pool.The Journal of experimental medicine · 2020Article
- Targeting enhancer switching overcomes non-genetic drug resistance in acute myeloid leukaemia.Nature communications · 2019Article
- Systematic evaluation of error rates and causes in short samples in next-generation sequencing.Scientific reports · 2018Article
- Heritable tumor cell division rate heterogeneity induces clonal dominance.PLoS computational biology · 2018Article
- Limitations and challenges of genetic barcode quantification.Scientific reports · 2017Article
- Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow.Nucleic acids research · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNext generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags.
resultsHere, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences.
conclusionsApplication of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.
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