JWES: a new pipeline for whole genome/exome sequence data processing, management, and gene‐variant discovery, annotation, prediction, and genotyping

Abstract

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.

Investigating underlying human immunity genes, implicated diseases and their relationship to COVID-19

“…An in-house developed gene-variant analysis pipeline (JWES) was applied for the whole genome and exome data preprocessing, modeling and downstream analysis ( Figure 1 ). JWES is mainly based on processing the raw sequence data, converting raw signals into base calling, identifying regions of interest in the genome, aligning, and assembling contigs and scaffolds and variant detection [ 81 ]. Its overall operations are divided into three modules: data preprocessing, storage and management, and visualization.…”

“…JWES is a cross-platform and user-friendly Java-based application that integrates multiple open-source command-line tools for sequence data processing and analysis, consisting of FASTQC (quality assessment) [ 82 ], Burrows–Wheeler Aligner software (BWA for short read alignment to reference human genome) [ 83 , 84 ], MarkDuplicates (removes redundant reads) [ 85 ], SAMtools (sorting and indexing) [ 86 ] and Genome Analysis Tool Kit (GATK for finding SNPs and indels) [ 87–89 ]. JWES is freely available for download and use by the community [ 81 ].…”

Investigating variant and expression of CVD genes associated phenotypes among high-risk Heart Failure patients

“…We applied our in-house developed gene-variant analysis pipeline (JWES) for the whole genome data pre-processing, modelling, and downstream analysis. JWES processes the raw sequence data, converts raw signals into base calling, identifies regions of interest in the genome, aligns, assembles contigs and scaffolds, and detects variants [20]. Its operations are divided into three separate modules: I) data preprocessing, II) storage and management, and III) visualization.…”

Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine

“…Standalone pipelines are mainly used in high-performance computing environments ( Petersen et al, 2017 ). These pipelines are designed to effectively collect and process the data from WGS or WES in a way so that it can be used by researchers or medical professionals to best recognize the links between genetic variants and diseases ( Petersen et al, 2017 ; Ahmed et al, 2021b ; Ahmed et al, 2021c ).…”