A preliminary Quality Control (QC) for next generation sequencing (NGS) library evaluation turns out to be a very useful tool for a rapid detection of BRCA1/2 deleterious mutations

2014 ◽  
Vol 437 ◽  
pp. 72-77 ◽  
Author(s):  
Paola Concolino ◽  
Alessandra Costella ◽  
Angelo Minucci ◽  
Giovanni Luca Scaglione ◽  
Concetta Santonocito ◽  
...  
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Rapid Detection ◽  
Deleterious Mutations ◽  
Next Generation ◽  
Library Evaluation ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

scholarly journals Demystification of RNAseq Quality Control

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Dragana Dudić ◽  
Bojana Banović Đeri ◽  
Vesna Pajić ◽  
Gordana Pavlović-Lažetić
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Rna Sequencing ◽  
Next Generation ◽  
Comprehensive Guidance ◽  
Dna And Rna ◽  
Control Evaluation ◽  
Downstream Analysis ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Next Generation Sequencing (NGS) analysis has become a widely used method for studying the structure of DNA and RNA, but complexity of the procedure leads to obtaining error-prone datasets which need to be cleansed in order to avoid misinterpretation of data. We address the usage and proper interpretations of characteristic metrics for RNA sequencing (RNAseq) quality control, implemented in and reported by FastQC, and provide a comprehensive guidance for their assessment in the context of total RNAseq quality control of Illumina raw reads. Additionally, we give recommendations how to adequately perform the quality control preprocessing step of raw total RNAseq Illumina reads according to the obtained results of the quality control evaluation step; the aim is to provide the best dataset to downstream analysis, rather than to get better FastQC results. We also tested effects of different preprocessing approaches to the downstream analysis and recommended the most suitable approach.

scholarly journals Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context

2019 ◽  
Vol 47 (21) ◽  
pp. e135-e135
Author(s):  
Maxim Ivanov ◽  
Mikhail Ivanov ◽  
Artem Kasianov ◽  
Ekaterina Rozhavskaya ◽  
Sergey Musienko ◽  
...  
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Performance Measure ◽  
Next Generation ◽  
Coverage Depth ◽  
Clinical Context ◽  
Context Availability ◽  
Control Metric ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Abstract As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnostic sensitivity of given NGS dataset. Here we present case studies of the use of EphaGen in context of BRCA1/2 and CFTR sequencing in a series of 14 runs across 43 blood samples and 504 publically available NGS datasets. EphaGen is superior to conventional bioinformatics metrics such as coverage depth and coverage uniformity. We recommend using this software as a QC step in NGS studies in the clinical context. Availability: https://github.com/m4merg/EphaGen or https://hub.docker.com/r/m4merg/ephagen.

scholarly journals Next-Generation Sequencing (NGS) in COVID-19: A Tool for SARS-CoV-2 Diagnosis, Monitoring New Strains and Phylodynamic Modeling in Molecular Epidemiology

2021 ◽  
Vol 43 (2) ◽  
pp. 845-867
Author(s):  
Goldin John ◽  
Nikhil Shri Sahajpal ◽  
Ashis K. Mondal ◽  
Sudha Ananth ◽  
Colin Williams ◽  
...  
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Real World ◽  
Next Generation ◽  
Comprehensive Review ◽  
Current Testing ◽  
Phylogenetic Evolution ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

This review discusses the current testing methodologies for COVID-19 diagnosis and explores next-generation sequencing (NGS) technology for the detection of SARS-CoV-2 and monitoring phylogenetic evolution in the current COVID-19 pandemic. The review addresses the development, fundamentals, assay quality control and bioinformatics processing of the NGS data. This article provides a comprehensive review of the obstacles and opportunities facing the application of NGS technologies for the diagnosis, surveillance, and study of SARS-CoV-2 and other infectious diseases. Further, we have contemplated the opportunities and challenges inherent in the adoption of NGS technology as a diagnostic test with real-world examples of its utility in the fight against COVID-19.

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.

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