A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data

Early diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma. Non-negative Matrix Factorization (NMF) has been widely used in num...

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Main Authors: Xiaoqin Huang, Akhilesh K. Bajpai, Jian Sun, Fuyi Xu, Lu Lu, Siamak Yousefi
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-06-01
Series:Frontiers in Genetics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2023.1204909/full
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author Xiaoqin Huang
Akhilesh K. Bajpai
Jian Sun
Fuyi Xu
Fuyi Xu
Lu Lu
Lu Lu
Siamak Yousefi
Siamak Yousefi
author_facet Xiaoqin Huang
Akhilesh K. Bajpai
Jian Sun
Fuyi Xu
Fuyi Xu
Lu Lu
Lu Lu
Siamak Yousefi
Siamak Yousefi
author_sort Xiaoqin Huang
collection DOAJ
description Early diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma. Non-negative Matrix Factorization (NMF) has been widely used in numerous transcriptome data analyses in order to identify subtypes and biomarkers of different diseases; however, its application in glaucoma biomarker discovery has not been previously reported. Our study applied NMF to extract latent representations of RNA-seq data from BXD mouse strains and sorted the genes based on a novel gene scoring method. The enrichment ratio of the glaucoma-reference genes, extracted from multiple relevant resources, was compared using both the classical differentially expressed gene (DEG) analysis and NMF methods. The complete pipeline was validated using an independent RNA-seq dataset. Findings showed our NMF method significantly improved the enrichment detection of glaucoma genes. The application of NMF with the scoring method showed great promise in the identification of marker genes for glaucoma.
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spelling doaj.art-9e3c077412814156b667b1f3be774de52023-06-12T16:10:50ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-06-011410.3389/fgene.2023.12049091204909A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq dataXiaoqin Huang0Akhilesh K. Bajpai1Jian Sun2Fuyi Xu3Fuyi Xu4Lu Lu5Lu Lu6Siamak Yousefi7Siamak Yousefi8Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, TN, United StatesDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United StatesIntegrated Data Science Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institute of Health (NIH), Bethesda, MD, United StatesDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United StatesSchool of Pharmacy, Binzhou Medical University, Yantai, Shandong, ChinaDepartment of Ophthalmology, University of Tennessee Health Science Center, Memphis, TN, United StatesDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United StatesDepartment of Ophthalmology, University of Tennessee Health Science Center, Memphis, TN, United StatesDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United StatesEarly diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma. Non-negative Matrix Factorization (NMF) has been widely used in numerous transcriptome data analyses in order to identify subtypes and biomarkers of different diseases; however, its application in glaucoma biomarker discovery has not been previously reported. Our study applied NMF to extract latent representations of RNA-seq data from BXD mouse strains and sorted the genes based on a novel gene scoring method. The enrichment ratio of the glaucoma-reference genes, extracted from multiple relevant resources, was compared using both the classical differentially expressed gene (DEG) analysis and NMF methods. The complete pipeline was validated using an independent RNA-seq dataset. Findings showed our NMF method significantly improved the enrichment detection of glaucoma genes. The application of NMF with the scoring method showed great promise in the identification of marker genes for glaucoma.https://www.frontiersin.org/articles/10.3389/fgene.2023.1204909/fullglaucomaRNA-seqDEGNMFBXD strainspathway analysis
spellingShingle Xiaoqin Huang
Akhilesh K. Bajpai
Jian Sun
Fuyi Xu
Fuyi Xu
Lu Lu
Lu Lu
Siamak Yousefi
Siamak Yousefi
A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data
Frontiers in Genetics
glaucoma
RNA-seq
DEG
NMF
BXD strains
pathway analysis
title A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data
title_full A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data
title_fullStr A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data
title_full_unstemmed A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data
title_short A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data
title_sort new gene scoring method for uncovering novel glaucoma related genes using non negative matrix factorization based on rna seq data
topic glaucoma
RNA-seq
DEG
NMF
BXD strains
pathway analysis
url https://www.frontiersin.org/articles/10.3389/fgene.2023.1204909/full
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