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ImageGP 2 for enhanced data visualization and reproducible analysis in biomedical research

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机构: [1]China Acad Chinese Med Sci, Natl Resource Ctr Chinese Mat Med, State Key Lab Qual Ensurance & Sustainable Use Dao, Beijing 100000, Peoples R China [2]Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Genome Anal Lab Minist Agr & Rural Affairs, Shenzhen 518120, Peoples R China [3]Chinese Acad Sci, Northwest Inst Plateau Biol, Xining, Qinghai, Peoples R China [4]Chinese Acad Sci, Lushan Bot Garden, Jiujiang, Peoples R China [5]Kings Coll London, Sch Life Course & Populat Sci, London, England [6]Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing, Peoples R China [7]Chinese Acad Med Sci & Peking Union Med Coll, Inst Lab Anim Sci, Key Lab Human Dis Comparat Med, Natl Hlth Commiss China NHC, Beijing, Peoples R China [8]Nanjing Agr Univ, Nanjing, Peoples R China [9]Huazhong Agr Univ, Coll Resources & Environm, Wuhan, Hubei, Peoples R China [10]Natl Univ Singapore, Yong Loo Lin Sch Med, Immunol Translat Res Program, Singapore, Singapore [11]Natl Univ Singapore, Life Sci Inst, Immunol Program, Singapore, Singapore [12]Natl Univ Singapore, Cambridge Immunophenotyping Ctr, NUS, Singapore, Singapore [13]Northwest A&F Univ, Coll Agron, State Key Lab Crop Stress Resistance & High Effici, Yangling, Shaanxi, Peoples R China [14]Capital Med Univ, Xuanwu Hosp, Natl Ctr Neurol Disorders, Dept Neurol, Beijing, Peoples R China [15]Northwest A&F Univ, Coll Nat Resources & Environm, Yangling, Shaanxi, Peoples R China [16]Wuhan Polytech Univ, Sch Life Sci & Technol, Wuhan, Peoples R China
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关键词: biology cloud platform data analysis data transformation data visualization ImageGP

摘要:
ImageGP is an extensively utilized, open-access platform for online data visualization and analysis. Over the past 7 years, it has catered to more than 700,000 usages globally, garnering substantial user feedback. The updated version, ImageGP 2 (available at ), introduces a redesigned interface leveraging cutting-edge web technologies to enhance functionality and user interaction. Key enhancements include the following: (i) Addition of modules for data format transformation, facilitating operations such as matrix merging, subsetting, and transformation between long and wide formats. (ii) Streamlined workflows with features like preparameter selection data validation and grouping of parameters with similar attributes. (iii) Expanded repertoire of visualization functions and analysis tools, including Weighted Gene Co-Expression Network Analysis, differential gene expression analysis, and FASTA sequence processing. (iv) Personalized user space for uploading large data sets, tracking analysis history, and sharing reproducible analysis data, scripts, and results. (v) Enhanced user support through a simplified error debugging feature accessible with a single click. (vi) Introduction of an R package, ImageGP, enabling local data visualization and analysis. These updates position ImageGP 2 as a versatile tool serving both wet-lab and dry-lab researchers with expanded capabilities. The infinity symbol illustrates the seamless workflow of ImageGP 2, encompassing essential functions such as data format transformation, data validation, and parameter combination. This process culminates in the generation of diverse visual outputs, including line, point, and bar plots. Key features include a personalized user center for managing large data sets, interactive visualizations, and streamlined error feedback mechanisms. Additionally, the introduction of the ImageGP R package enables local and batch analyses. Overall, the infinity symbol embodies the limitless potential for data analysis and visualization offered by ImageGP 2. image Advanced user interface, expanded analytical capabilities, and seamless data handling. New modules for data transformation and preparameter selection data validation. Personalized user center, reproducible scripts, seamless error debugging, the introduction of local analysis capabilities.

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Q1 MICROBIOLOGY

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第一作者机构: [1]China Acad Chinese Med Sci, Natl Resource Ctr Chinese Mat Med, State Key Lab Qual Ensurance & Sustainable Use Dao, Beijing 100000, Peoples R China
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