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Software
Xin Chen
Institute of Biopharmaceutical Technology, School of Medicine, Zhejiang University
Corresponding Author
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Background
To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level.
Results
Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of 6 types of data that suggest functional associations between genes. This update of the HIR consists of 88,069 pairs of genes representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57.04% may represent protein interactions, which are expected to cover 32.48% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools.
Conclusions
We present the HIR V2, a high-quality functional interactome of human genes, along with the gene set linkage analysis (GSLA) webtool, which utilizes the HIR V2 to interpret the biological significance of transcriptionally changed genes. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn .
Keywords
human, functional interaction, database, gene set linkage analysis, transcriptomic analysis tool
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Software
Xin Chen
Institute of Biopharmaceutical Technology, School of Medicine, Zhejiang University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 17 Jun, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epigenetics & Genomics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level.
Results
Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of 6 types of data that suggest functional associations between genes. This update of the HIR consists of 88,069 pairs of genes representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57.04% may represent protein interactions, which are expected to cover 32.48% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools.
Conclusions
We present the HIR V2, a high-quality functional interactome of human genes, along with the gene set linkage analysis (GSLA) webtool, which utilizes the HIR V2 to interpret the biological significance of transcriptionally changed genes. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn .
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
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