scholarly journals Challenges and Strategies for Next Generation Sequencing (NGS) Data Analysis

2010 ◽  
Vol 03 (02) ◽  
Author(s):  
Vivek Thakur
Keyword(s):  
Data Analysis ◽  
Next Generation Sequencing ◽  
Next Generation ◽  
Ngs Data Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing ◽  
Challenges And Strategies

scholarly journals PM4NGS, a project management framework for next-generation sequencing data analysis

GigaScience ◽  
2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Roberto Vera Alvarez ◽  
Lorinc Pongor ◽  
Leonardo Mariño-Ramírez ◽  
David Landsman
Keyword(s):  
Project Management ◽  
Data Analysis ◽  
Next Generation Sequencing ◽  
Organizational Structure ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Management Framework ◽  
Ngs Data Analysis ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Background FAIR (Findability, Accessibility, Interoperability, and Reusability) next-generation sequencing (NGS) data analysis relies on complex computational biology workflows and pipelines to guarantee reproducibility, portability, and scalability. Moreover, workflow languages, managers, and container technologies have helped address the problem of data analysis pipeline execution across multiple platforms in scalable ways. Findings Here, we present a project management framework for NGS data analysis called PM4NGS. This framework is composed of an automatic creation of a standard organizational structure of directories and files, bioinformatics tool management using Docker or Bioconda, and data analysis pipelines in CWL format. Pre-configured Jupyter notebooks with minimum Python code are included in PM4NGS to produce a project report and publication-ready figures. We present 3 pipelines for demonstration purposes including the analysis of RNA-Seq, ChIP-Seq, and ChIP-exo datasets. Conclusions PM4NGS is an open source framework that creates a standard organizational structure for NGS data analysis projects. PM4NGS is easy to install, configure, and use by non-bioinformaticians on personal computers and laptops. It permits execution of the NGS data analysis on Windows 10 with the Windows Subsystem for Linux feature activated. The framework aims to reduce the gap between researcher in experimental laboratories producing NGS data and workflows for data analysis. PM4NGS documentation can be accessed at https://pm4ngs.readthedocs.io/.

scholarly journals Evaluation and Comparison of Multiple Aligners for Next-Generation Sequencing Data Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Jing Shang ◽  
Fei Zhu ◽  
Wanwipa Vongsangnak ◽  
Yifei Tang ◽  
Wenyu Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
Next Generation Sequencing ◽  
Real Life ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Computational Performance ◽  
Alignment Algorithms ◽  
Ngs Data Analysis ◽  
Ngs Data ◽  
Generation Sequencing

Next-generation sequencing (NGS) technology has rapidly advanced and generated the massive data volumes. To align and map the NGS data, biologists often randomly select a number of aligners without concerning their suitable feature, high performance, and high accuracy as well as sequence variations and polymorphisms existing on reference genome. This study aims to systematically evaluate and compare the capability of multiple aligners for NGS data analysis. To explore this capability, we firstly performed alignment algorithms comparison and classification. We further used long-read and short-read datasets from both real-life andin silicoNGS data for comparative analysis and evaluation of these aligners focusing on three criteria, namely, application-specific alignment feature, computational performance, and alignment accuracy. Our study demonstrated the overall evaluation and comparison of multiple aligners for NGS data analysis. This serves as an important guiding resource for biologists to gain further insight into suitable selection of aligners for specific and broad applications.

Introduction to the analysis of next generation sequencing data and its application to venous thromboembolism

2015 ◽  
Vol 114 (11) ◽  
pp. 920-932 ◽  
Author(s):  
Joost C. M. Meijers ◽  
Saskia Middeldorp ◽  
Marisa L. R. Cunha
Keyword(s):  
Venous Thromboembolism ◽  
Next Generation Sequencing ◽  
Clinical Care ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

SummaryDespite knowledge of various inherited risk factors associated with venous thromboembolism (VTE), no definite cause can be found in about 50% of patients. The application of data-driven searches such as GWAS has not been able to identify genetic variants with implications for clinical care, and unexplained heritability remains. In the past years, the development of several so-called next generation sequencing (NGS) platforms is offering the possibility of generating fast, inexpensive and accurate genomic information. However, so far their application to VTE has been very limited. Here we review basic concepts of NGS data analysis and explore the application of NGS technology to VTE. We provide both computational and biological viewpoints to discuss potentials and challenges of NGS-based studies.

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.

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