An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology.
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ABSTRACT:
SUBMITTER: Li J
PROVIDER: S-EPMC4827795 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MotivationThere has been rapid progress in the development of error-correcting and constrained codes for DNA storage systems in recent years. However, improving the steps for processing raw sequencing data for DNA storage has a lot of untapped potential for further progress. In particular, constraints can be used as prior information to improve the processing of DNA sequencing data. Furthermore, a workflow tailored to DNA storage codes enables fair comparisons between different approaches while leading to reproducible results.ResultsWe present RepairNatrix, a read-processing workflow for DNA storage. RepairNatrix supports preprocessing of raw sequencing data for DNA storage applications and can be used to flag and heuristically repair constraint-violating sequences to further increase the recoverability of encoded data in the presence of errors. Compared to a preprocessing strategy without repair functionality, RepairNatrix reduced the number of raw reads required for the successful, error-free decoding of the input files by a factor of 25-35 across different datasets.Availability and implementationRepairNatrix is available on Github: https://github.com/umr-ds/repairnatrix.
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Project description:Radical new possibilities of improved treatment of cancer are on offer from an advanced medical technology already demonstrating its significance: next-generation sequencing (NGS). This refined testing provides unprecedentedly precise diagnoses and permits the use of focused and highly personalized treatments. However, across regions globally, many cancer patients will continue to be denied the benefits of NGS as long as some of the yawning gaps in its implementation remain unattended. The challenges at the regional and national levels are linked because putting the solutions into effect is highly dependent on cooperation between regional- and national-level cooperation, which could be hindered by shortfalls in interpretation or understanding. The aim of the paper was to define and explore the necessary conditions for NGS and make recommendations for effective implementation based on extensive exchanges with policy makers and stakeholders. As a result, the European Alliance for Personalised Medicine (EAPM) developed a maturity framework structured around demand-side and supply-side issues to enable interested stakeholders in different countries to self-evaluate according to a common matrix. A questionnaire was designed to identify the current status of NGS implementation, and it was submitted to different experts in different institutions globally. This revealed significant variability in the different aspects of NGS uptake. Within different regions globally, to ensure those conditions are right, this can be improved by linking efforts made at the national level, where patients have needs and where care is delivered, and at the global level, where major policy initiatives in the health field are underway or in preparation, many of which offer direct or indirect pathways for building those conditions. In addition, in a period when consensus is still incomplete and catching up is needed at a political level to ensure rational allocation of resources-even within individual countries-to enable the best ways to make the necessary provisions for NGS, a key recommendation is to examine where closer links between national and regional actions could complement, support, and mutually reinforce efforts to improve the situation for patients.
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Project description:Since the first reported case of the new coronavirus infection in Wuhan, China, researchers and governments have witnessed an unseen rise in the number of cases. Thanks to the rapid work of Chinese scientists, the pathogen now called SARS-CoV-2 has been identified and its whole genome was deposited in public databases by early January 2020. The availability of the genome has allowed researchers to develop Reverse Transcription-Polymerase Chain Reaction (RT-PCR) assays, which are now the gold-standard for molecular diagnosis of the respiratory syndrome COVID19. Because of the rising number of cases and rapid spreading, the world has been facing a shortage of RT-PCR supplies, especially the ones involved in RNA extraction. This has been a major bottleneck to increase testing capacity in many countries that do not significantly manufacture these supplies, such as Brazil. Additionally, RT-qPCR scalability is highly dependent on equipment that usually performs testing of 96 samples at a time. In this work, we describe a cost-effective molecular NGS-based test for diagnosis of COVID19, which uses a single-step RNA extraction and presents high scalability and accuracy when compared to the gold-standard RT-qPCR. A single run of the NGS-based test using the Illumina NextSeq 550 mid-end sequencing equipment is able to multiplex 1,536 patient's samples, providing individual semi-qualitative results (detected, not detected). Detected results are provided with fragments per million (FPM) values, which was demonstrated to correlate with RT-qPCR Cycle Threshold (CT) values. Besides, usage of the high-end Illumina Novaseq platform may yield diagnostic for up to 6144 samples in a single run. Performance results when compared with RT-qPCR show general accuracy of 96%, and 98% when only samples with CT values (gene N) lower than 30 are considered. We have also developed an online platform, termed VarsVID, to help test executors to easily scale testing numbers. Sample registering, wet-lab worksheets generation, sample sheet for sequencing and results' display are all features provided by VarsVID. Altogether, these results will contribute to control COVID19 pandemics.
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Project description:The study of sex determination and sex chromosome organization in nonmodel species has long been technically challenging, but new sequencing methodologies now enable precise and high-throughput identification of sex-specific genomic sequences. In particular, restriction site-associated DNA sequencing (RAD-Seq) is being extensively applied to explore sex determination systems in many plant and animal species. However, software specifically designed to search for and visualize sex-biased markers using RAD-Seq data is lacking. Here, we present RADSex, a computational analysis workflow designed to study the genetic basis of sex determination using RAD-Seq data. RADSex is simple to use, requires few computational resources, makes no prior assumptions about the type of sex-determination system or structure of the sex locus, and offers convenient visualization through a dedicated R package. To demonstrate the functionality of RADSex, we re-analysed a published data set of Japanese medaka, Oryzias latipes, where we uncovered a previously unknown Y chromosome polymorphism. We then used RADSex to analyse new RAD-Seq data sets from 15 fish species spanning multiple taxonomic orders. We identified the sex determination system and sex-specific markers in six of these species, five of which had no known sex-markers prior to this study. We show that RADSex greatly facilitates the study of sex determination systems in nonmodel species thanks to its speed of analyses, low resource usage, ease of application and visualization options. Furthermore, our analysis of new data sets from 15 species provides new insights on sex determination in fish.
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Project description:BACKGROUND:Next generation sequencing (NGS) is becoming widely used among diagnostics and research laboratories, and nowadays it is applied to a variety of disciplines, including veterinary virology. The NGS workflow comprises several steps, namely sample processing, library preparation, sequencing and primary/secondary/tertiary bioinformatics (BI) analyses. The latter is constituted by a complex process extremely difficult to standardize, due to the variety of tools and metrics available. Thus, it is of the utmost importance to assess the comparability of results obtained through different methods and in different laboratories. To achieve this goal, we have organized a proficiency test focused on the bioinformatics components for the generation of complete genome sequences of salmonid rhabdoviruses. METHODS:Three partners, that performed virus sequencing using different commercial library preparation kits and NGS platforms, gathered together and shared with each other 75 raw datasets which were analyzed separately by the participants to produce a consensus sequence according to their own bioinformatics pipeline. Results were then compared to highlight discrepancies, and a subset of inconsistencies were investigated more in detail. RESULTS:In total, we observed 526 discrepancies, of which 39.5% were located at genome termini, 14.1% at intergenic regions and 46.4% at coding regions. Among these, 10 SNPs and 99 indels caused changes in the protein products. Overall reproducibility was 99.94%. Based on the analysis of a subset of inconsistencies investigated more in-depth, manual curation appeared the most critical step affecting sequence comparability, suggesting that the harmonization of this phase is crucial to obtain comparable results. The analysis of a calibrator sample allowed assessing BI accuracy, being 99.983%. CONCLUSIONS:We demonstrated the applicability and the usefulness of BI proficiency testing to assure the quality of NGS data, and recommend a wider implementation of such exercises to guarantee sequence data uniformity among different virology laboratories.
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Project description:Nanopore sequencing, also known as single-molecule real-time sequencing, is a third/fourth generation sequencing technology that enables deciphering single DNA/RNA molecules without the polymerase chain reaction. Although nanopore sequencing has made significant progress in scientific research and clinical practice, its application has been limited compared with next-generation sequencing (NGS) due to specific design principle and data characteristics, especially in hotspot mutation detection. Therefore, we developed Nano2NGS-Muta as a data analysis framework for hotspot mutation detection based on long reads from nanopore sequencing. Nano2NGS-Muta is characterized by applying nanopore sequencing data to NGS-liked data analysis pipelines. Long reads can be converted into short reads and then processed through existing NGS analysis pipelines in combination with statistical methods for hotspot mutation detection. Nano2NGS-Muta not only effectively avoids false positive/negative results caused by non-random errors and unexpected insertions-deletions (indels) of nanopore sequencing data, improves the detection accuracy of hotspot mutations compared to conventional nanopore sequencing data analysis algorithms but also breaks the barriers of data analysis methods between short-read sequencing and long-read sequencing. We hope Nano2NGS-Muta can serves as a reference method for nanopore sequencing data and promotes higher application scope of nanopore sequencing technology in scientific research and clinical practice.
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