TNER: a novel background error suppression method for mutation detection in circulating tumor DNA

Deng, Shibing; Lira, Maruja; Huang, Donghui; Wang, Kai; Valdez, Crystal E.; Kinong, Jennifer; Rejto, Paul A.; Bienkowska, Jadwiga; Hardwick, James S.; Xie, Tongxin

doi:10.1186/s12859-018-2428-3

Cited by 13 publications

(12 citation statements)

References 36 publications

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“…To this end, cfDNA sequencing artifacts and stochastic sequencing errors need to be suppressed 25 . Combining existing knowledge 22, 23, 25 , our error suppression approach includes tagging DNA molecules with unique molecular identifiers (UMIs) and a combination of two comparative error suppression (CES) methods: (I) deriving and excluding error-prone genomic regions in a identically processed set of cfDNA samples from a healthy control cohort and (II) judging each base call based on its modelled error-rate in an identically processed healthy control cohort considering the given tri-nucleotide context 27 (see methods for details).…”

Section: Resultsmentioning

confidence: 99%

“…Using customized scripts, all positions with a non-reference (hg19) allele frequency > 5%, likely representing germline single nucleotide polymorphisms, were set to a non-reference allele frequency of 0 in the reference cohort. Next, TNER 27 was used to compile a database of position-specific average background error rates for each position in the target region using the healthy donor controls as input. This database was used as input to TNER 27 to polish each cell-free DNA MPILEUP generated from post UMI-processing consensus reads aligned to hg19 by BWA mem 70 as described above with the polish strength parameter set to 0.05 (parameter: input.alpha = 0.05).…”

Section: Methodsmentioning

confidence: 99%

“…Next, TNER 27 was used to compile a database of position-specific average background error rates for each position in the target region using the healthy donor controls as input. This database was used as input to TNER 27 to polish each cell-free DNA MPILEUP generated from post UMI-processing consensus reads aligned to hg19 by BWA mem 70 as described above with the polish strength parameter set to 0.05 (parameter: input.alpha = 0.05). Briefly, TNER 27 uses tri-nucleotide error rates in the healthy reference cohort to suppress likely sequencing errors, thus reducing tri-nucleotide error rate profiles to suppress stochastic sequencing errors.…”

Section: Methodsmentioning

confidence: 99%

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Exhaustive circulating tumor DNA sequencing reveals the genomic landscape of Hodgkin lymphoma and facilitates ultrasensitive detection of minimal residual disease

Sobesky

Mammadova

Cirillo

et al. 2021

Preprint

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Individualizing treatment is key to improve outcome and reduce long-term side-effects in any cancer. In Hodgkin lymphoma (HL), individualization of treatment is hindered by a lack of genomic characterization and technology for sensitive, molecular response assessment. Sequencing of cell-free (cf)DNA is a powerful strategy to understand an individual cancer genome and can be used to develop assays for extremely sensitive disease monitoring. In HL, a high proportion of cfDNA is tumor-derived making it a highly relevant disease model to study the role of cfDNA sequencing in cancer. Here, we introduce our targeted cfDNA sequencing platform and present the largest genomic landscape of HL to date, which was entirely derived by cfDNA sequencing. We comprehensively genotype and assess minimal residual disease in 324 samples from 121 patients, presenting an integrated landscape of mutations and copy number variations in HL. In addition, we perform a deep analysis of mutational processes driving HL, investigate the clonal structure of HL and link several genotypes to HL phenotypes and outcome. Finally, we show that minimal residual disease assessment by repeat cfDNA sequencing as early as a week after treatment initiation is feasible and predicts overall treatment response allowing highly improved treatment guidance and relapse prediction. Our study also serves as a blueprint showcasing the utility of our platform for other cancers with similar therapeutic challenges.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Exhaustive circulating tumor DNA sequencing reveals the genomic landscape of Hodgkin lymphoma and facilitates ultrasensitive detection of minimal residual disease

Sobesky

Mammadova

Cirillo

et al. 2021

Preprint

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“…3h). This result indicated that using cfDNA data from normal healthy individuals with low-level templates as the background [20,41] is not sufficient to cover all noises in samples with high-level templates under similar sequencing coverage. Thus, we combined controls with RSDs for the following analysis.…”

Section: Characteristics Of Mutant-family-level Noisementioning

confidence: 99%

A novel virtual barcode strategy for accurate panel-wide variant calling in circulating tumor DNA

Deng

Xu³

et al. 2020

BMC Bioinformatics

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Background: Hybrid capture-based next-generation sequencing of DNA has been widely applied in the detection of circulating tumor DNA (ctDNA). Various methods have been proposed for ctDNA detection, but low-allelicfraction (AF) variants are still a great challenge. In addition, no panel-wide calling algorithm is available, which hiders the full usage of ctDNA based 'liquid biopsy'. Thus, we developed the VBCALAVD (Virtual Barcode-based Calling Algorithm for Low Allelic Variant Detection) in silico to overcome these limitations. Results: Based on the understanding of the nature of ctDNA fragmentation, a novel platform-independent virtual barcode strategy was established to eliminate random sequencing errors by clustering sequencing reads into virtual families. Stereotypical mutant-family-level background artifacts were polished by constructing AF distributions. Three additional robust fine-tuning filters were obtained to eliminate stochastic mutant-family-level noises. The performance of our algorithm was validated using cell-free DNA reference standard samples (cfDNA RSDs) and normal healthy cfDNA samples (cfDNA controls). For the RSDs with AFs of 0.1, 0.2, 0.5, 1 and 5%, the mean F1 scores were 0.43 (0.25~0.56), 0.77, 0.92, 0.926 (0.86~1.0) and 0.89 (0.75~1.0), respectively, which indicates that the proposed approach significantly outperforms the published algorithms. Among controls, no false positives were detected. Meanwhile, characteristics of mutant-family-level noise and quantitative determinants of divergence between mutant-family-level noises from controls and RSDs were clearly depicted. Conclusions: Due to its good performance in the detection of low-AF variants, our algorithm will greatly facilitate the noninvasive panel-wide detection of ctDNA in research and clinical settings. The whole pipeline is available at https://github.com/zhaodalv/VBCALAVD.

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“…This caveat has motivated several approaches for error-suppression when sequencing cfDNA, which can enhance the sensitivity of variant detection (Newman et al, 2016;Deng et al, 2018). Another approach to go beyond the variant detection limit is to monitor previously identified mutations from the tumor rather than de novo detection.…”

Section: Introductionmentioning

confidence: 99%

ctDNAtools: An R package to work with sequencing data of circulating tumor DNA

Alkodsi

Meriranta

Pasanen³

et al. 2020

Preprint

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Sequencing of cell-free DNA (cfDNA) including circulating tumor DNA (ctDNA) in minimally-invasive liquid biopsies is rapidly maturing towards clinical utility for cancer diagnostics. However, the publicly available bioinformatics tools for the specialized analysis of ctDNA sequencing data are still scarce.Here, we present the ctDNAtools R package, which provides functionalities for testing minimal residual disease (MRD) and analyzing cfDNA fragmentation. MRD detection in ctDNAtools utilizes a Monte Carlo sampling approach to test ctDNA positivity through tracking a set of pre-detected reporter mutations in follow-up samples. Additionally, ctDNAtools includes various functionalities to study cfDNA fragment size histograms, profiles and fragment ends patterns. AvailabilityThe ctDNAtools package is freely available under MIT license at https://github.com/alkodsi/ctDNAtools.

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TNER: a novel background error suppression method for mutation detection in circulating tumor DNA

Cited by 13 publications

References 36 publications

Exhaustive circulating tumor DNA sequencing reveals the genomic landscape of Hodgkin lymphoma and facilitates ultrasensitive detection of minimal residual disease

Exhaustive circulating tumor DNA sequencing reveals the genomic landscape of Hodgkin lymphoma and facilitates ultrasensitive detection of minimal residual disease

A novel virtual barcode strategy for accurate panel-wide variant calling in circulating tumor DNA

ctDNAtools: An R package to work with sequencing data of circulating tumor DNA

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