scholarly journals A Canadian guideline on the use of next-generation sequencing in oncology

2019 ◽  
Vol 26 (2) ◽  
Author(s):  
S. Yip ◽  
A. Christofides ◽  
S. Banerji ◽  
M. R. Downes ◽  
I. Izevbaye ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Best Practices ◽  
Sample Selection ◽  
Molecular Profile ◽  
Next Generation ◽  
Canadian Guideline ◽  
Molecular Tests ◽  
Management Guidance ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Rapid advancements in next-generation sequencing (ngs) technology have created an unprecedented opportunity to decipher the molecular profile of tumours to more effectively prevent, diagnose, and treat cancer. Oncologists now have the option to order molecular tests that can guide treatment decisions. However, to date, most oncologists have received limited training in genomics, and they are now faced with the challenge of understanding how such tests and their interpretation align with patient management. Guidance on how to effectively use ngs technology is therefore needed to aid oncologists in applying the results of genomic tests. The Canadian guideline presented here describes best practices and unmet needs related to ngs-based testing for somatic variants in oncology, including clinical application, assay and sample selection, bioinformatics and interpretation of reports performed by laboratories, patient communication, and clinical trials.

scholarly journals Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities

2020 ◽  
Author(s):  
Matteo Chiara ◽  
Anna Maria D’Erchia ◽  
Carmela Gissi ◽  
Caterina Manzari ◽  
Antonio Parisi ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genomic Sequence ◽  
Molecular Diagnostic ◽  
Next Generation ◽  
Sequencing Data ◽  
Related Data ◽  
Molecular Tests ◽  
Methodological Approaches ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Abstract Various next generation sequencing (NGS) based strategies have been successfully used in the recent past for tracing origins and understanding the evolution of infectious agents, investigating the spread and transmission chains of outbreaks, as well as facilitating the development of effective and rapid molecular diagnostic tests and contributing to the hunt for treatments and vaccines. The ongoing COVID-19 pandemic poses one of the greatest global threats in modern history and has already caused severe social and economic costs. The development of efficient and rapid sequencing methods to reconstruct the genomic sequence of SARS-CoV-2, the etiological agent of COVID-19, has been fundamental for the design of diagnostic molecular tests and to devise effective measures and strategies to mitigate the diffusion of the pandemic. Diverse approaches and sequencing methods can, as testified by the number of available sequences, be applied to SARS-CoV-2 genomes. However, each technology and sequencing approach has its own advantages and limitations. In the current review, we will provide a brief, but hopefully comprehensive, account of currently available platforms and methodological approaches for the sequencing of SARS-CoV-2 genomes. We also present an outline of current repositories and databases that provide access to SARS-CoV-2 genomic data and associated metadata. Finally, we offer general advice and guidelines for the appropriate sharing and deposition of SARS-CoV-2 data and metadata, and suggest that more efficient and standardized integration of current and future SARS-CoV-2-related data would greatly facilitate the struggle against this new pathogen. We hope that our ‘vademecum’ for the production and handling of SARS-CoV-2-related sequencing data, will contribute to this objective.

scholarly journals NGSeasy: a next generation sequencing pipeline in Docker containers

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 997 ◽  
Author(s):  
Amos A Folarin ◽  
Richard JB Dobson ◽  
Stephen J Newhouse
Keyword(s):  
Next Generation Sequencing ◽  
Best Practices ◽  
Best Practice ◽  
Building Blocks ◽  
Reproducible Research ◽  
Next Generation ◽  
New Paradigm ◽  
Concept Evaluation ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Motivation: Bioinformatic pipelines often use large numbers of components and deploying them incurs substantial configuration and maintenance burden that remains a significant barrier to reproducible research. Our aim is to define a new paradigm and best practices for developing, distributing and running pipelines encapsulated in Docker containers (lightweight virtualization), with a focus on next generation sequencing (NGS) workflows. This approach provides several advantages, namely: efficiency, portability, versioning and reproducibility. Using the NGSeasy pipeline, a user can quickly deploy any pipeline version in any environment (e.g. operating systems, workstations, clusters, clouds). While this might also be achieved with a virtual machine (VM); VMs lack portability, have substantial overhead (disk, CPU, RAM), and require allocated resources to be provisioned statically – Docker, to a large extent, solves these issues.Results: We demonstrate best practices for packaging and execution of a multicomponent pipeline for NGS using a set of container building blocks which are versioned, modular and reusable. We present a basic ”proof of concept” evaluation of a next generation sequencing pipeline in Docker containers, capable of producing meaningful results, that are comparable with public and ”best practice” workflows, with little to no impact on standard computing performance.Availability: Both versioned Dockerfiles and container images for each component are published on GitHub and Docker Hub, respectively. The pipeline and containers can be pulled from Docker Hub and executed on any environment capable of running the Docker platform with minimum hardware requirements for running an NGS pipeline.

Initial Next-Generation Sequencing (NGS) Results of Alport Syndrome

2019 ◽  
Author(s):  
Altuğ Koç ◽  
Elçin Bora ◽  
Tayfun Cinleti ◽  
Gizem Yıldız ◽  
Meral Torun Bayram ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Alport Syndrome ◽  
Next Generation ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

The applications of next-generation sequencing (NGS) in drug development for cancer therapy

2020 ◽  
Vol 16 ◽  
Author(s):  
Pelin Telkoparan-Akillilar ◽  
Dilek Cevik
Keyword(s):  
Next Generation Sequencing ◽  
Drug Discovery ◽  
Cancer Therapy ◽  
Target Identification ◽  
Rapid Development ◽  
Next Generation ◽  
Biomedical Sciences ◽  
Dna And Rna ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Background: Numerous sequencing techniques have been progressed since the 1960s with the rapid development of molecular biology studies focusing on DNA and RNA. Methods: a great number of articles, book chapters, websites are reviewed, and the studies covering NGS history, technology and applications to cancer therapy are included in the present article. Results: High throughput next-generation sequencing (NGS) technologies offer many advantages over classical Sanger sequencing with decreasing cost per base and increasing sequencing efficiency. NGS technologies are combined with bioinformatics software to sequence genomes to be used in diagnostics, transcriptomics, epidemiologic and clinical trials in biomedical sciences. The NGS technology has also been successfully used in drug discovery for the treatment of different cancer types. Conclusion: This review focuses on current and potential applications of NGS in various stages of drug discovery process, from target identification through to personalized medicine.

scholarly journals Next-Generation Sequencing in Tumor Diagnosis and Treatment

Diagnostics ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 962
Author(s):  
Dario de Biase ◽  
Matteo Fassan ◽  
Umberto Malapelle
Keyword(s):  
Next Generation Sequencing ◽  
Tumor Diagnosis ◽  
Diagnosis And Treatment ◽  
Next Generation ◽  
Multiple Genes ◽  
Next Generation Sequencing Ngs ◽  
Very High ◽  
Generation Sequencing ◽  
High Depth

Next-Generation Sequencing (NGS) allows for the sequencing of multiple genes at a very high depth of coverage [...]

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