Processing UMI Datasets at High Accuracy and Efficiency with the Sentieon ctDNA Analysis Pipeline

Hu, Jinnan; Jiang, Cai; Huang, Yu S.; Chen, Haodong; Feng, Hanying; Freed, Donald; Yan, Qingzhi; Fan, Rui; Su, Zhencheng; Chen, Weizhi

doi:10.1101/2022.06.03.494742

Cited by 4 publications

(4 citation statements)

References 28 publications

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“…Raw reads were trimmed with Fastp with high‐quality standards (at least 30% of bases have quality above Q30) 21 . UMIs were then extracted from both ends of reads and aligned to hg19 reference genome using Sentieon UMI pipeline 27 . Reads belonging to the same UMI family group were merged into a consensus read with base quality adjusted.…”

Section: Methodsmentioning

confidence: 99%

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Evaluating personalized circulating tumor DNA detection for early‐stage lung cancer

Huang,

Kai,

Wang

et al. 2023

Cancer Medicine

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Circulating tumor DNA (ctDNA) has been widely used as a minimally invasive biomarker in clinical routine. However, a number of factors such as panel design, sample quality, patients' disease stages are known to influence ctDNA detection sensitivity. In this study, we systematically evaluated common factors associated with the variability of ctDNA detection in plasma and investigated ctDNA abundance in bronchoalveolar lavage (BAL). Whole exome profiling was conducted on 61 tumor tissue samples to identify tumor‐specific variants, which were then used to design personalized assay MarRyDa® for ctDNA detection. DNA extracted from BAL fluid and plasma were genotyped using MarRyDa® platform. Our analysis showed that histological subtypes and disease stages had significant differences in ctDNA detection rate. Furthermore, we found that DNA purified from BAL supernatants contains the highest levels of ctDNA compared with BAL precipitates and plasma; therefore, utilizing BAL supernatants for tumor detection might provide additional benefits. Finally, we demonstrated that tumor cellularity played significant roles in the design of personalized ctDNA panel which eventually impacts ctDNA detection sensitivity. We suggest setting a flexible criteria for sample quality control and utilization of BAL might benefit more patients in clinics.

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Section: Methodsmentioning

confidence: 99%

“… 21 UMIs were then extracted from both ends of reads and aligned to hg19 reference genome using Sentieon UMI pipeline. 27 Reads belonging to the same UMI family group were merged into a consensus read with base quality adjusted. Quality control was performed after reads alignment.…”

Section: Methodsmentioning

confidence: 99%

Evaluating personalized circulating tumor DNA detection for early‐stage lung cancer

Huang,

Kai,

Wang

et al. 2023

Cancer Medicine

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“…On the other hand, some pipelines opt for separate consensus generation and variant calling tools, offering more flexibility and easier adaptation to new data types. Popular consensus generation tools include “Fgbio” 14 , “Picard” 15 , “Gencore” 16 , and Sentieon’s UMI analyzing pipeline 17 . Fgbio is typically applied to datasets with UMIs, Picard serves as a traditional deduplication tool, selecting reads with the best quality score as group representation.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Accuracy and Efficiency in Analyzing Non-UMI Liquid Biopsy Datasets Using the Sentieon ctDNA Pipeline

Niu,

Hu,

Chen

et al. 2024

Preprint

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Sequencing clinical liquid biopsy, especially circulating tumor DNA (ctDNA), provides a valuable method for identifying low allele frequency tumor variants, opening novel clinical applications, particularly in treatment selection for late-stage cancer patients. Despite advancements, challenges in assay development persist, primarily due to limited sample volumes and insufficiency of reads supporting low allele frequency variants. The allele frequencies of clinically significant variants often hover close to the threshold of errors introduced by PCR and sequencing processes. Therefore, more sophisticated analysis methods are crucial to further reduce base error rates, enabling accurate discrimination between background errors and genuine somatic variants. While several ctDNA analysis pipelines have been published and adopted, there is room for improvement in terms of accuracy and run efficiency. In this study, we introduce Sentieon's innovative consensus-based ctDNA pipeline - a rapid and precise solution for calling small somatic variants from non-UMI ctDNA sequencing data. The pipeline comprises four core modules: alignment, consensus generation, variant calling, and variant filtering. Through benchmarking with in-vitro and real clinical datasets, we observed that the Sentieon ctDNA pipeline exhibits higher accuracy compared to alternative methods.

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“…Wells et al combined experimental procedures with bioinformatics analysis to reduce the number of PCR/sequencing artifacts upon integration site identification (Wells et al, 2020). Lastly, a recent work also makes use of UMI-tag to achieve to quantify small somatic variant calling from ctDNA sequencing data (Hu et al, 2022). Still, there is to date no systematic comparative evaluation of a UMI-based system against fragment-based methods for abundance quantification in the context of insertion site retrieval using a set of controlled “real-world” scenarios.…”

Section: Introductionmentioning

confidence: 99%

IS-Seq: a bioinformatics pipeline for integration sites analysis with comprehensive abundance quantification methods

Yan

Baricordi

Nguyen

et al. 2023

Preprint

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Integration site (IS) analysis is a fundamental analytical platform for evaluating the safety and efficacy of viral vector based preclinical and clinical Gene Therapy (GT). A handful of groups have developed standardized bioinformatics pipelines to process IS sequencing data, to generate reports, and/or to perform comparative studies across different GT trials. Keeping up with the technological advances in the field of IS analysis, different computational pipelines have been published over the past decade. These pipelines focus on identifying integration sites (IS) from single-read sequencing or paired-end sequencing data either using read-based or using sonication fragment-based methods, but there is a lack of a bioinformatics tool that automatically includes unique molecular identifiers (UMI) for IS abundance estimations and allows comparing multiple quantification methods in one integrated pipeline. Here we present IS-seq a bioinformatics pipeline that can process data from paired-end sequencing of both old restriction sites-based IS collection methods and new sonication-based IS retrieval systems while allowing the selection of different abundance estimation methods, including read-based, Fragment-based and UMI-based systems. We validated the performance of IS-Seq testing it against the most widely used analytical workflow available in the literature (INSPIIRED) and using different scenarios. Lastly, by performing a comprehensive wet-lab assessment of our IS-Seq pipeline we could show that in clinically relevant scenarios, UMI quantification provides better accuracy than the currently most widely used sonication fragment counts as a method for IS abundance estimation.

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Processing UMI Datasets at High Accuracy and Efficiency with the Sentieon ctDNA Analysis Pipeline

Cited by 4 publications

References 28 publications

Evaluating personalized circulating tumor DNA detection for early‐stage lung cancer

Evaluating personalized circulating tumor DNA detection for early‐stage lung cancer

Optimizing Accuracy and Efficiency in Analyzing Non-UMI Liquid Biopsy Datasets Using the Sentieon ctDNA Pipeline

IS-Seq: a bioinformatics pipeline for integration sites analysis with comprehensive abundance quantification methods

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