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Article ; Online: Fatty liver classification via risk controlled neural networks trained on grouped ultrasound image data.

Yen, Tso-Jung / Yang, Chih-Ting / Lee, Yi-Ju / Chen, Chun-Houh / Yang, Hsin-Chou

2024 Volume 14, Issue 1, Page(s) 7345

Abstract: Ultrasound imaging is a widely used technique for fatty liver diagnosis as it is practically affordable and can be quickly deployed by using suitable devices. When it is applied to a patient, multiple images of the targeted tissues are produced. We ... ...

Abstract	Ultrasound imaging is a widely used technique for fatty liver diagnosis as it is practically affordable and can be quickly deployed by using suitable devices. When it is applied to a patient, multiple images of the targeted tissues are produced. We propose a machine learning model for fatty liver diagnosis from multiple ultrasound images. The machine learning model extracts features of the ultrasound images by using a pre-trained image encoder. It further produces a summary embedding on these features by using a graph neural network. The summary embedding is used as input for a classifier on fatty liver diagnosis. We train the machine learning model on a ultrasound image dataset collected by Taiwan Biobank. We also carry out risk control on the machine learning model using conformal prediction. Under the risk control procedure, the classifier can improve the results with high probabilistic guarantees.
MeSH term(s)	Humans ; Neural Networks, Computer ; Ultrasonography/methods ; Fatty Liver/diagnostic imaging ; Machine Learning ; Taiwan
Language	English
Publishing date	2024-03-28
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-57386-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Evaluating statistical significance in a

Lin, Yin-Chun / Liang, Yu-Jen / Yang, Hsin-Chou

Computational and structural biotechnology journal

2022 Volume 20, Page(s) 3615–3620

Abstract: Meta-analysis is a method for enhancing statistical power through the integration of information from multiple studies. Various methods for integrating p-values (i.e., statistical significance), including Fisher's method under an independence assumption, ...

Abstract	Meta-analysis is a method for enhancing statistical power through the integration of information from multiple studies. Various methods for integrating p-values (i.e., statistical significance), including Fisher's method under an independence assumption, the permutation method, and the decorrelation method, have been broadly used in bioinformatics and computational biotechnology studies. However, these methods have limitations related to statistical assumption, computing efficiency, and accuracy of statistical significance estimation. In this study, we proposed a numerical integration method and examined its theoretical properties. Simulation studies were conducted to evaluate its Type I error, statistical power, computational efficiency, and estimation accuracy, and the results were compared with those of other methods. The results demonstrate that our proposed method performs well in terms of Type I error, statistical power, computing efficiency (regardless of sample size), and statistical significance estimation accuracy. P-value data from multiple large-scale genome-wide association studies (GWASs) and transcriptome-wise association studies (TWASs) were analyzed. The results demonstrate that our proposed method can be used to identify critical genomic regions associated with rheumatoid arthritis and asthma, increase statistical significance in individual GWASs and TWASs, and control for false-positives more effectively than can Fisher's method under an independence assumption. We created the software package Pbine, available at GitHub (https://github.com/Yinchun-Lin/Pbine).
Language	English
Publishing date	2022-07-04
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2694435-2
ISSN	2001-0370
ISSN	2001-0370
DOI	10.1016/j.csbj.2022.06.055
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Article ; Online: Common and ethnic-specific genetic determinants of hemoglobin concentration between Taiwanese Han Chinese and European Whites: findings from comparative two-stage genome-wide association studies.

Timoteo, Vanessa Joy / Chiang, Kuang-Mao / Yang, Hsin-Chou / Pan, Wen-Harn

The Journal of nutritional biochemistry

2022 Volume 111, Page(s) 109126

Abstract: Human iron nutrition is a result of interplays between genetic and environmental factors. However, there has been scarcity of data on the genetic variants associated with altered iron homeostasis and ethnic-specific associations are further lacking. In ... ...

Abstract	Human iron nutrition is a result of interplays between genetic and environmental factors. However, there has been scarcity of data on the genetic variants associated with altered iron homeostasis and ethnic-specific associations are further lacking. In this study, we compared between the Taiwanese Han Chinese (HC) and European Whites the genetic determinants of hemoglobin (Hb) concentration, a biochemical parameter that in part reflects the amount of functional iron in the body. Through sex-specific two-stage genome-wide association studies (2S-GWAS), we observed the consistent Hb-association of SNPs in TMPRSS6 (chr 22), ABO (chr 9), and PRKCE (chr 2) across sexes in both ethnic groups. Specific to the Taiwanese HC, the Hb-association of AXIN1, together with other loci near the chr 16 alpha-globin gene cluster, was found novel. On the other hand, majority of the Hb-associated SNPs among Europeans were identified along the chr 6 major histocompatibility complex (MHC) region, which has established roles in immune system control. We report here strong Hb-associations of HFE and members of gene families (SLC17; H2A, H2B, H3, H4, H1; TRIM; ZSCAN, ZKSCAN, ZNF; HLA; BTN, OR), numerous SNPs in/nearby CARMIL1, PRRC2A, PSORS1C1, NOTCH4, TSBP1, C6orf15, and distinct associations with non-coding RNA genes. Our findings provide evidence for both common and ethnic-specific genetic determinants of Hb between East Asians and Caucasians. These will help to further our understanding of the iron and/or erythropoiesis physiology in humans and to identify high risk subgroups for iron imbalances - a primary requirement to meet the goal of precision nutrition for optimal health.
MeSH term(s)	Female ; Humans ; Male ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Hemoglobins/genetics ; Iron ; Polymorphism, Single Nucleotide ; Asian People/genetics ; White People/genetics ; Taiwan
Chemical Substances	Hemoglobins ; Iron (E1UOL152H7)
Language	English
Publishing date	2022-08-11
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1014929-6
ISSN	1873-4847 ; 0955-2863
ISSN (online)	1873-4847
ISSN	0955-2863
DOI	10.1016/j.jnutbio.2022.109126
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Article ; Online: Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits.

Guo, Chao-Yu / Wang, Reng-Hong / Yang, Hsin-Chou

Scientific reports

2021 Volume 11, Issue 1, Page(s) 7431

Abstract: After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare ... ...

Abstract	After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.
MeSH term(s)	Algorithms ; Environment ; Gene-Environment Interaction ; Genetic Association Studies ; Genetic Predisposition to Disease ; Genetic Testing/methods ; Genetic Variation ; Genome-Wide Association Study ; Humans ; Models, Genetic ; Multifactorial Inheritance ; Phenotype ; Quantitative Trait Loci ; Quantitative Trait, Heritable ; Software
Language	English
Publishing date	2021-04-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-86871-2
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Article ; Online: Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

Chao-Yu Guo / Reng-Hong Wang / Hsin-Chou Yang

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 8

Abstract: Abstract After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and ...

Abstract	Abstract After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.
Keywords	Medicine ; R ; Science ; Q
Subject code	500
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Homozygosity disequilibrium associated with treatment response and its methylation regulation.

Yang, Hsin-Chou / Chen, Chia-Wei

BMC proceedings

2018 Volume 12, Issue Suppl 9, Page(s) 45

Abstract: Homozygosity disequilibrium (HD), indicating a nonrandom pattern of sizable runs of homozygosity that deviates from a random allocation of homozygous and heterozygous genotypes in the genome, is an important phenomenon in population genomics and medical ... ...

Abstract	Homozygosity disequilibrium (HD), indicating a nonrandom pattern of sizable runs of homozygosity that deviates from a random allocation of homozygous and heterozygous genotypes in the genome, is an important phenomenon in population genomics and medical genomics. We performed the first genome-wide study investigating the roles of HD in pharmacogenomics and pharmacoepigenomics by analyzing GAW20 data. We inferred whole-genome profiles of homozygosity intensities and performed genome-wide homozygosity association analyses to identify regions of HD associated with triglyceride (TG) response to fenofibrate by using LOHAS (Loss-of-Heterozygosity Analysis Suite) software. The analysis identified a region of HD contained in
Language	English
Publishing date	2018-09-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2411867-9
ISSN	1753-6561
ISSN	1753-6561
DOI	10.1186/s12919-018-0150-9
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Article ; Online: Genetic ancestry plays a central role in population pharmacogenomics

Hsin-Chou Yang / Chia-Wei Chen / Yu-Ting Lin / Shih-Kai Chu

Communications Biology, Vol 4, Iss 1, Pp 1-

2021 Volume 14

Abstract: Hsin-Chou Yang et al. examine population structure in several genomic databases and identify ...

Abstract	Hsin-Chou Yang et al. examine population structure in several genomic databases and identify that pharmacogenetic loci are enriched for markers of genetic ancestry. Their results suggest that genetic ancestry must be carefully considered in population pharmacogenetics studies.
Keywords	Biology (General) ; QH301-705.5
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Evaluating statistical significance in a meta-analysis by using numerical integration

Lin, Yin-Chun / Liang, Yu-Jen / Yang, Hsin-Chou

Computational and Structural Biotechnology Journal. 2022, v. 20

2022

Abstract	Meta-analysis is a method for enhancing statistical power through the integration of information from multiple studies. Various methods for integrating p-values (i.e., statistical significance), including Fisher’s method under an independence assumption, the permutation method, and the decorrelation method, have been broadly used in bioinformatics and computational biotechnology studies. However, these methods have limitations related to statistical assumption, computing efficiency, and accuracy of statistical significance estimation. In this study, we proposed a numerical integration method and examined its theoretical properties. Simulation studies were conducted to evaluate its Type I error, statistical power, computational efficiency, and estimation accuracy, and the results were compared with those of other methods. The results demonstrate that our proposed method performs well in terms of Type I error, statistical power, computing efficiency (regardless of sample size), and statistical significance estimation accuracy. P-value data from multiple large-scale genome-wide association studies (GWASs) and transcriptome-wise association studies (TWASs) were analyzed. The results demonstrate that our proposed method can be used to identify critical genomic regions associated with rheumatoid arthritis and asthma, increase statistical significance in individual GWASs and TWASs, and control for false-positives more effectively than can Fisher’s method under an independence assumption. We created the software package Pbine, available at GitHub (https://github.com/Yinchun-Lin/Pbine).
Keywords	asthma ; bioinformatics ; biotechnology ; genomics ; meta-analysis ; rheumatoid arthritis ; sample size
Language	English
Size	p. 3615-3620.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	2694435-2
ISSN	2001-0370
ISSN	2001-0370
DOI	10.1016/j.csbj.2022.06.055
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Genetic ancestry plays a central role in population pharmacogenomics.

Yang, Hsin-Chou / Chen, Chia-Wei / Lin, Yu-Ting / Chu, Shih-Kai

Communications biology

2021 Volume 4, Issue 1, Page(s) 171

Abstract: Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, ...

Abstract	Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD ( http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/ ).
MeSH term(s)	Biomarkers, Pharmacological/analysis ; Biomarkers, Pharmacological/metabolism ; Biotransformation/genetics ; Continental Population Groups/genetics ; Databases, Genetic ; Gene Frequency ; Gene-Environment Interaction ; Genetic Variation/physiology ; Genome, Human/physiology ; Homozygote ; Humans ; Inactivation, Metabolic/genetics ; Linkage Disequilibrium ; Pharmacogenetics ; Polymorphism, Single Nucleotide ; Precision Medicine/methods ; Precision Medicine/trends ; Principal Component Analysis ; Proteome/drug effects ; Proteome/metabolism ; Transcriptome/drug effects ; Transcriptome/physiology
Chemical Substances	Biomarkers, Pharmacological ; Proteome
Language	English
Publishing date	2021-02-05
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2399-3642
ISSN (online)	2399-3642
DOI	10.1038/s42003-021-01681-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Common and Ethnic-Specific Genetic Determinants of Hemoglobin Concentration between Taiwanese Han Chinese and European Whites: Findings from Comparative Two-Stage Genome-Wide Association Studies

Timoteo, Vanessa Joy / Chiang, Kuang-Mao / Yang, Hsin-Chou / Pan, Wen-Harn

Journal of nutritional biochemistry. 2022 July 15,

2022

Abstract	Human iron nutrition is a result of interplays between genetic and environmental factors. However, there has been scarcity of data on the genetic variants associated with altered iron homeostasis and ethnic-specific associations are further lacking. In this study, we compared between the Taiwanese Han Chinese (HC) and European Whites the genetic determinants of hemoglobin (Hb) concentration, a biochemical parameter that in part reflects the amount of functional iron in the body. Through sex-specific two-stage genome-wide association studies (2S-GWAS), we observed the consistent Hb-association of SNPs in TMPRSS6 (chr 22), ABO (chr 9), and PRKCE (chr 2) across sexes in both ethnic groups. Specific to the Taiwanese HC, the Hb-association of AXIN1, together with other loci near the chr 16 alpha-globin gene cluster, was found novel. On the other hand, majority of the Hb-associated SNPs among Europeans were identified along the chr 6 major histocompatibility complex (MHC) region, which has established roles in immune system control. We report here strong Hb-associations of HFE and members of gene families (SLC17; H2A, H2B, H3, H4, H1; TRIM; ZSCAN, ZKSCAN, ZNF; HLA; BTN, OR), numerous SNPs in/nearby CARMIL1, PRRC2A, PSORS1C1, NOTCH4, TSBP1, C6orf15, and distinct associations with non-coding RNA genes. Our findings provide evidence for both common and ethnic-specific genetic determinants of Hb between East Asians and Caucasians. These will help to further our understanding of the iron and/or erythropoiesis physiology in humans and to identify high risk subgroups for iron imbalances – a primary requirement to meet the goal of precision nutrition for optimal health.
Keywords	Chinese people ; erythropoiesis ; hemoglobin ; homeostasis ; humans ; immune system ; iron ; major histocompatibility complex ; multigene family ; non-coding RNA ; nutrition ; risk
Language	English
Dates of publication	2022-0715
Publishing place	Elsevier Inc.
Document type	Article
Note	Pre-press version
ZDB-ID	1014929-6
ISSN	1873-4847 ; 0955-2863
ISSN (online)	1873-4847
ISSN	0955-2863
DOI	10.1016/j.jnutbio.2022.109126
Database	NAL-Catalogue (AGRICOLA)

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