So far, interpreting deep intronic, intergenic, and regulatory sequence variants has been difficult, by relying only on DNA level. Similar to WES, WGS can also be used in silico gene panels selection. This sets WGS apart in detecting non-exonic variants, and enhancing CNV detection. WGS enables the interrogation of both the coding and noncoding regions of the genome. A recent deep transcriptional study, identified over 2000 unannotated isoforms of protein-coding mRNAs. WGS makes no assumptions about the exome and the human genome that is not yet fully characterized. WGS exhibits the broadest coverage and variant detection. Finally, the current limitations and future development are discussed to provide guidance and direction for further exploration of WGS.Ībdellah Tebani, Soumeya Bekri, in Precision Medicine for Investigators, Practitioners and Providers, 2020 Whole genome sequencing and genome-wide association studies Next, we investigate the potential clinical applications of WGS for Mendelian diseases, complex diseases, and cancers in medical genetics. Some commonly used tools and platforms are summarized for the implementation of genome sequencing. In this manuscript, we present an overview of computational pipelines and workflows for WGS analysis, illustrating the fundamental steps and methods of the workflow, including data preparation, alignment and assembly, variant calling, annotation, and analysis. Meanwhile, the rapid progress and innovation of NGS technology has successfully enabled the generation of large volumes of sequence data and reduced the expense for WGS. The feasibility of WGS analysis is under the support of next generation sequencing (NGS) technologies, which require substantial computational and biomedical resources to acquire and analyze large and complex sequence data. Whole genome sequencing (WGS) has revolutionized the biosciences and proven to be essential and invaluable to the identification of gene functions and their involvement in disease. Jie Zheng, in Encyclopedia of Bioinformatics and Computational Biology, 2019 Abstract In this regard, thanatomicrobiome analysis using the WGS approach is still at a nascent stage due to the unavailability of suitable reference databases and limited availability of data. ![]() For the taxonomic analysis of WGS data, many software is available including sequence alignment, Bayesian classifier, k-mer mapping, however, for analysis of WGS results depends on the correct annotation of the reference database ( Zhou & Bian, 2018). As huge data is generated after the WGS approach, it is of huge importance to select an appropriate computational technique to analyze the sequenced data. Though the cost-effectiveness of this technique is an issue, the WGS technique provides a high taxonomic resolution and shows a complete microbial profile of the community besides generating information on the functional genes present in the microbes. In comparison to targeted sequencing, WGS explores a much larger sequence space to generate a huge genetic diversity. Whole-genome sequencing (WGS) directly sequences all available DNA materials from a sample. Hirak Ranjan Dash, Surajit Das, in Advances in Applied Microbiology, 2022 6.4 Whole-genome sequencing
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