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TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction

Gene Ontology (GO) has been widely used to annotate functions of genes and gene products. Here, we proposed a new method, TripletGO, to deduce GO terms of protein-coding and non-coding genes, through the integration of four complementary pipelines built on transcript expression profile, genetic sequ...

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Detalles Bibliográficos
Autores principales: Zhu, Yi-Heng, Zhang, Chengxin, Liu, Yan, Omenn, Gilbert S., Freddolino, Peter L., Yu, Dong-Jun, Zhang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025770/
https://www.ncbi.nlm.nih.gov/pubmed/35568117
http://dx.doi.org/10.1016/j.gpb.2022.03.001
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author Zhu, Yi-Heng
Zhang, Chengxin
Liu, Yan
Omenn, Gilbert S.
Freddolino, Peter L.
Yu, Dong-Jun
Zhang, Yang
author_facet Zhu, Yi-Heng
Zhang, Chengxin
Liu, Yan
Omenn, Gilbert S.
Freddolino, Peter L.
Yu, Dong-Jun
Zhang, Yang
author_sort Zhu, Yi-Heng
collection PubMed
description Gene Ontology (GO) has been widely used to annotate functions of genes and gene products. Here, we proposed a new method, TripletGO, to deduce GO terms of protein-coding and non-coding genes, through the integration of four complementary pipelines built on transcript expression profile, genetic sequence alignment, protein sequence alignment, and naïve probability. TripletGO was tested on a large set of 5754 genes from 8 species (human, mouse, Arabidopsis, rat, fly, budding yeast, fission yeast, and nematoda) and 2433 proteins with available expression data from the third Critical Assessment of Protein Function Annotation challenge (CAFA3). Experimental results show that TripletGO achieves function annotation accuracy significantly beyond the current state-of-the-art approaches. Detailed analyses show that the major advantage of TripletGO lies in the coupling of a new triplet network-based profiling method with the feature space mapping technique, which can accurately recognize function patterns from transcript expression profiles. Meanwhile, the combination of multiple complementary models, especially those from transcript expression and protein-level alignments, improves the coverage and accuracy of the final GO annotation results. The standalone package and an online server of TripletGO are freely available at https://zhanggroup.org/TripletGO/.
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spelling pubmed-100257702023-03-21 TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction Zhu, Yi-Heng Zhang, Chengxin Liu, Yan Omenn, Gilbert S. Freddolino, Peter L. Yu, Dong-Jun Zhang, Yang Genomics Proteomics Bioinformatics Method Gene Ontology (GO) has been widely used to annotate functions of genes and gene products. Here, we proposed a new method, TripletGO, to deduce GO terms of protein-coding and non-coding genes, through the integration of four complementary pipelines built on transcript expression profile, genetic sequence alignment, protein sequence alignment, and naïve probability. TripletGO was tested on a large set of 5754 genes from 8 species (human, mouse, Arabidopsis, rat, fly, budding yeast, fission yeast, and nematoda) and 2433 proteins with available expression data from the third Critical Assessment of Protein Function Annotation challenge (CAFA3). Experimental results show that TripletGO achieves function annotation accuracy significantly beyond the current state-of-the-art approaches. Detailed analyses show that the major advantage of TripletGO lies in the coupling of a new triplet network-based profiling method with the feature space mapping technique, which can accurately recognize function patterns from transcript expression profiles. Meanwhile, the combination of multiple complementary models, especially those from transcript expression and protein-level alignments, improves the coverage and accuracy of the final GO annotation results. The standalone package and an online server of TripletGO are freely available at https://zhanggroup.org/TripletGO/. Elsevier 2022-10 2022-05-11 /pmc/articles/PMC10025770/ /pubmed/35568117 http://dx.doi.org/10.1016/j.gpb.2022.03.001 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method
Zhu, Yi-Heng
Zhang, Chengxin
Liu, Yan
Omenn, Gilbert S.
Freddolino, Peter L.
Yu, Dong-Jun
Zhang, Yang
TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
title TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
title_full TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
title_fullStr TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
title_full_unstemmed TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
title_short TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
title_sort tripletgo: integrating transcript expression profiles with protein homology inferences for gene function prediction
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025770/
https://www.ncbi.nlm.nih.gov/pubmed/35568117
http://dx.doi.org/10.1016/j.gpb.2022.03.001
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