| 1. |
- Xiao, Wenming, et al.
(författare)
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Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing
- 2021
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Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1141-1150
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Tidskriftsartikel (refereegranskat)abstract
- Recommendations are given on optimal read coverage and selection of calling algorithm to maximize the reproducibility of cancer mutation detection in whole-genome or whole-exome sequencing. Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.
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| 2. |
- Fang, Li Tai, et al.
(författare)
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Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
- 2021
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Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1151-1160
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Tidskriftsartikel (refereegranskat)abstract
- Tumor-normal paired DNA samples from a breast cancer cell line and a matched lymphoblastoid cell line enable calibration of clinical sequencing pipelines and benchmarking 'tumor-only' or 'matched tumor-normal' analyses. The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.
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| 3. |
- Foox, Jonathan, et al.
(författare)
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The SEQC2 epigenomics quality control (EpiQC) study
- 2021
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Ingår i: Genome Biology. - : BioMed Central (BMC). - 1465-6906 .- 1474-760X. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundCytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA’s Epigenomics Quality Control Group.ResultsEach sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms.ConclusionsThe data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.
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| 4. |
- Liu, Biyu, et al.
(författare)
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A min–max solution to optimise planned lead time in a remanufacturing system
- 2019
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Ingår i: International Transactions in Operational Research. - : John Wiley & Sons. - 0969-6016 .- 1475-3995. ; 26:2, s. 485-506
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Tidskriftsartikel (refereegranskat)abstract
- Determining a rational planned lead time (PLT) is a critical and difficult problem in production planning, especially for a remanufacturing system. This paper considers an optimisation problem of the PLT in a make-to-order remanufacturing system to coordinate disassembly–remanufacturing–reassembly and to improve performance. This optimisation model is designed to determine the PLT that minimises the inventory holding and shortage costs. Given the unknown distribution of remanufacturing time but with known first and second moments, this model is solved by a min–max approach, which can capture distributions with the same first and second moments. How the PLT and total cost are affected by yield rate with different first and second moments, unit holding cost, unit shortage cost and purchasing lead time are also investigated through numerical examples in this paper. The results of this study are shown to be consistent with practice and can be a support to decision-making in production planning and scheduling for remanufacturing.
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| 5. |
- Liu, Biyu, et al.
(författare)
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Effects of carbon emission regulations on remanufacturing decisions with limited information of demand distribution
- 2015
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Ingår i: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; 53:2, s. 532-548
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Tidskriftsartikel (refereegranskat)abstract
- Policy-makers are developing regulation policies to drive down carbon emissions from industries. Independent remanufacturers (IRs), which remanufacture recycled products/components/parts, must manage and evaluate economic costs generated by the production under future carbon emission regulations. We present three optimisation models to determine the remanufacturing quantity that maximises the total profits under three common carbon emission regulation policies: (a) mandatory carbon emissions capacity, (b) carbon tax and (c) cap and trade. These models include sales revenue, remanufacturing cost, disposal cost, inventory holding cost, shortage cost and carbon emission cost. The max–min approach is used to solve the models, which assume limited information on demand distribution. We investigate how the three regulation policies affect remanufacturing decision-making for IRs and we also solve some numerical examples where we vary the magnitudes of incentives, penalties and stringency of constraints to provide implications to policy-makers. The results indicate that remanufacturers should aim to improve yield rate to maximise the profit irrespective of the implemented carbon emissions policy. Policy-makers should prefer the carbon tax policy, if any of the other two policies must be performed, a remanufacturing discount such as a higher carbon emission cap or lower penalty should be implemented to better promote the development of remanufacturers.
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| 6. |
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| 7. |
- Mansouri, Kamel, et al.
(författare)
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CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity
- 2020
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Ingår i: Journal of Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 128:2, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast (TM) metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast (TM)/Tox21 HTS in vitro assays.RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of similar to 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment.
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| 8. |
- Ren, Luyao, et al.
(författare)
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Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance
- 2023
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Ingår i: Genome Biology. - : BioMed Central (BMC). - 1465-6906 .- 1474-760X. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome.RESULTS: We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data.CONCLUSIONS: The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.
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