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Progress in bioinformatics tools for analysis of metagenomically isolated microbiome: Current status and future prospects

Authors
Kukkar, DeepakChopra, ChahatKim, Ki-HyunRajesh, Preeti
Issue Date
Jun-2026
Publisher
Elsevier Inc.
Keywords
Binning; Bioinformatics pipelines; Genomic Standards Consortium; Next-generation sequencing
Citation
Gene Reports, v.43, pp 1 - 27
Pages
27
Indexed
SCOPUS
ESCI
Journal Title
Gene Reports
Volume
43
Start Page
1
End Page
27
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/211012
DOI
10.1016/j.genrep.2026.102437
ISSN
2452-0144
2452-0144
Abstract
Recent advances in the metagenomic exploration of non-cultivable microbiota have been achieved with the aid of high-throughput sequencing techniques and related data interpretation methods. The generation of metagenomic data is increasing exponentially, aided by the low cost of next generation sequencing (NGS) analyses. Since the pandemic, demand for bioinformatics tools and the related data sciences has been growing rapidly because of their potential to identify novel microbes (e.g., by uncoupling and decoding the phylogenetic relationships among the metagenomically mined microorganisms). In accordance with those developments, this review outlines historical evolution and recent trends in the advancement of NGS technologies for deciphering the genomic potential of the living world. The discussion extends to the recent advances in the field of bioinformatic tools used for the quality control (QC), assembly, binning, taxonomic classification, functional annotation, and comparative analyses of amplicon sequences, and shotgun metagenomic sequences in terms of their merits and demerits. Specifically, the acquisition of input data in various bioinformatics tools is discussed within a modular, decision-based pipeline framework based upon their applications in the analysis for whole metagenome (PRINSEQ, Decontam, Meta-QC, DAMIAN, CLARK, Kraken, MetaPhlAn4, Metagenome analyzer (MEGAN), MetaPop, and STRONG) or amplicon sequenced data (DADA2, MOTHUR, and QIIME) has been discussed. Issues related to workflow integration, reproducibility, and interoperability are also highlighted. Future challenges are also deliberated with respect to expanding the applicability of bioinformatics tools, especially to identifying metagenomically isolated microorganisms.
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