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.

scholarly journals Mining and Development of Novel SSR Markers Using Next Generation Sequencing (NGS) Data in Plants

Molecules ◽  
2018 ◽  
Vol 23 (2) ◽  
pp. 399 ◽  
Author(s):  
Sima Taheri ◽  
Thohirah Lee Abdullah ◽  
Mohd Yusop ◽  
Mohamed Hanafi ◽  
Mahbod Sahebi ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Ssr Markers ◽  
Next Generation ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

scholarly journals ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Michael T. Wolfinger ◽  
Jörg Fallmann ◽  
Florian Eggenhofer ◽  
Fabian Amman
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Motif ◽  
Software Components ◽  
Sequencing Analysis ◽  
Next Generation ◽  
File Formats ◽  
Next Generation Sequencing Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

scholarly journals Whole genome sequencing suggests transmission of Corynebacterium diphtheriae-caused cutaneous diphtheria in two siblings, Germany, 2018

2019 ◽  
Vol 24 (2) ◽  
Author(s):  
Anja Berger ◽  
Alexandra Dangel ◽  
Tilmann Schober ◽  
Birgit Schmidbauer ◽  
Regina Konrad ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Corynebacterium Diphtheriae ◽  
Whole Genome ◽  
Next Generation ◽  
Insect Bites ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

In September 2018, a child who had returned from Somalia to Germany presented with cutaneous diphtheria by toxigenic Corynebacterium diphtheriae biovar mitis. The child’s sibling had superinfected insect bites harbouring also toxigenic C. diphtheriae. Next generation sequencing (NGS) revealed the same strain in both patients suggesting very recent human-to-human transmission. Epidemiological and NGS data suggest that the two cutaneous diphtheria cases constitute the first outbreak by toxigenic C. diphtheriae in Germany since the 1980s.

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 ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Michael T. Wolfinger ◽  
Jörg Fallmann ◽  
Florian Eggenhofer ◽  
Fabian Amman
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Motif ◽  
Software Components ◽  
Sequencing Analysis ◽  
Next Generation ◽  
File Formats ◽  
Next Generation Sequencing Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

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.

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