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      Wekemo Bioincloud: A user‐friendly platform for meta‐omics data analyses

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          Abstract

          The increasing application of meta‐omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud—a specialized platform for ‐omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user‐friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration‐independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

          Abstract

          Wekemo Bioincloud is a specialized platform for meta‐omics studies that addresses scalability challenges in handling vast microbial community data with 22 workflows and 65 visualization tools. It provides comprehensive analysis, online vector output modification, and ensures privacy with a registration‐independent dashboard system.

          Highlights

          • Wekemo Bioincloud offers not just workflows for diverse meta‐omics data analysis but also a rich array of tools for effective data visualization.

          • Enables modifying vector outputs online, achieving publication‐ready figures.

          • Displays tools' popularity/usage trends, enhancing the platform's flexibility and user‐friendly experience.

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          Most cited references64

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Contributors
                liuyongxin@caas.cn
                Journal
                Imeta
                Imeta
                10.1002/(ISSN)2770-596X
                IMT2
                Imeta
                John Wiley and Sons Inc. (Hoboken )
                2770-5986
                2770-596X
                13 February 2024
                February 2024
                : 3
                : 1 ( doiID: 10.1002/imt2.v3.1 )
                : e175
                Affiliations
                [ 1 ] Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
                [ 2 ] Shenzhen Wekemo Technology Group Co., Ltd. Shenzhen China
                Author notes
                [*] [* ] Correspondence Yong‐Xin Liu, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.

                Email: liuyongxin@ 123456caas.cn

                Author information
                http://orcid.org/0000-0003-3389-9385
                http://orcid.org/0000-0003-1832-9835
                Article
                IMT2175
                10.1002/imt2.175
                10989175
                38868508
                4c592d2d-7a7d-49cf-a114-878c389814a4
                © 2024 The Authors. iMeta published by John Wiley & Sons Australia, Ltd on behalf of iMeta Science.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 January 2024
                : 11 December 2023
                : 23 January 2024
                Page count
                Figures: 5, Tables: 0, Pages: 12, Words: 5790
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: U21A20182
                Award ID: U23A20148
                Funded by: Agricultural Science and Technology Innovation Program , doi 10.13039/501100012421;
                Award ID: CAAS‐ZDRW202308
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                February 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.0 mode:remove_FC converted:25.03.2024

                bioinformatics,meta‐omics,microbiome,user‐friendly platform,wekemo bioincloud

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