SmCCNet 2.0: A Comprehensive Tool for Multi-omics Network Inference with Shiny Visualization
Abstract Summary Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are specific to this variable. We present the second-generation SmCCNet (SmCCNet 2.0) that adeptly integrates single or multiple omics data types along with a quantitative or binary phenotype of interest. In addition, this new package offers a streamlined setup process that can be configured manually or automatically, ensuring a flexible and user-friendly experience.Availability This package is available in both CRAN:<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://cran.r-project.org/web/packages/SmCCNet/index.html">https://cran.r-project.org/web/packages/SmCCNet/index.html</jats:ext-link>and Github:<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/KechrisLab/SmCCNet">https://github.com/KechrisLab/SmCCNet</jats:ext-link>under the MIT license. The network visualization tool is available at<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://smccnet.shinyapps.io/smccnetnetwork/">https://smccnet.shinyapps.io/smccnetnetwork/</jats:ext-link>..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 09. Apr. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Weixuan [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
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| doi: |
10.1101/2023.11.20.567893 |
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| PPN (Katalog-ID): |
XBI041614976 |
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| 245 | 1 | 0 | |a SmCCNet 2.0: A Comprehensive Tool for Multi-omics Network Inference with Shiny Visualization |
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| 520 | |a Abstract Summary Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are specific to this variable. We present the second-generation SmCCNet (SmCCNet 2.0) that adeptly integrates single or multiple omics data types along with a quantitative or binary phenotype of interest. In addition, this new package offers a streamlined setup process that can be configured manually or automatically, ensuring a flexible and user-friendly experience.Availability This package is available in both CRAN:<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://cran.r-project.org/web/packages/SmCCNet/index.html">https://cran.r-project.org/web/packages/SmCCNet/index.html</jats:ext-link>and Github:<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/KechrisLab/SmCCNet">https://github.com/KechrisLab/SmCCNet</jats:ext-link>under the MIT license. The network visualization tool is available at<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://smccnet.shinyapps.io/smccnetnetwork/">https://smccnet.shinyapps.io/smccnetnetwork/</jats:ext-link>. | ||
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| 700 | 1 | |a Vu, Thao |e verfasserin |4 aut | |
| 700 | 1 | |a Konigsberg, Iain |e verfasserin |0 (orcid)0000-0001-7356-100X |4 aut | |
| 700 | 1 | |a Pratte, Katherine |e verfasserin |4 aut | |
| 700 | 1 | |a Zhuang, Yonghua |e verfasserin |4 aut | |
| 700 | 1 | |a Kechris, Katerina |e verfasserin |4 aut | |
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