JWES: a new pipeline for whole genome/exome sequence data processing, management, and gene‐variant discovery, annotation, prediction, and genotyping
| Autor: | Eduard Gibert Renart, Zeeshan Ahmed, Deepshikha Mishra, Saman Zeeshan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
QH301-705.5
Computer science Pipeline (computing) Big data Sequence assembly Method computer.software_genre General Biochemistry Genetics and Molecular Biology Workflow Data visualization Databases Genetic Exome Sequencing Methods Humans Exome Biology (General) gene whole exome Exome sequencing database Data Management variants Genome whole genome Whole Genome Sequencing business.industry Computational Biology Genetic Variation Reproducibility of Results bioinformatics application Molecular Sequence Annotation Genomics Sequence Analysis DNA Visualization Data mining business computer Imputation (genetics) Software |
| Zdroj: | FEBS Open Bio FEBS Open Bio, Vol 11, Iss 9, Pp 2441-2452 (2021) |
| ISSN: | 2211-5463 |
| Popis: | Whole genome and exome sequencing (WGS/WES) are the most popular next‐generation sequencing (NGS) methodologies and are at present often used to detect rare and common genetic variants of clinical significance. We emphasize that automated sequence data processing, management, and visualization should be an indispensable component of modern WGS and WES data analysis for sequence assembly, variant detection (SNPs, SVs), imputation, and resolution of haplotypes. In this manuscript, we present a newly developed findable, accessible, interoperable, and reusable (FAIR) bioinformatics‐genomics pipeline Java based Whole Genome/Exome Sequence Data Processing Pipeline (JWES) for efficient variant discovery and interpretation, and big data modeling and visualization. JWES is a cross‐platform, user‐friendly, product line application, that entails three modules: (a) data processing, (b) storage, and (c) visualization. The data processing module performs a series of different tasks for variant calling, the data storage module efficiently manages high‐volume gene‐variant data, and the data visualization module supports variant data interpretation with Circos graphs. The performance of JWES was tested and validated in‐house with different experiments, using Microsoft Windows, macOS Big Sur, and UNIX operating systems. JWES is an open‐source and freely available pipeline, allowing scientists to take full advantage of all the computing resources available, without requiring much computer science knowledge. We have successfully applied JWES for processing, management, and gene‐variant discovery, annotation, prediction, and genotyping of WGS and WES data to analyze variable complex disorders. In summary, we report the performance of JWES with some reproducible case studies, using open access and in‐house generated, high‐quality datasets. In this manuscript, we present JWES, a newly developed FAIR bioinformatics‐genomics pipeline for gene‐variant discovery, annotation, prediction, and genotyping, and big data modelling and visualization. JWES is an open‐source and freely available application, allowing scientists to take full advantage of all the computing resources available, without requiring much computer science knowledge. |
| Databáze: | OpenAIRE |
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