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Special issue on genome wide association study

Quantitative Biology 2021年第2期9卷 105-106页

作者： Lin Hou Qiongshi Lu Can Yang Hongyu Zhao Center for Statistical Science Department of Industrial EngineeringMOE Key Laboratory of BioinformaticsSchool of Life SciencesTsinghua UniversityBeijing 100084China Department of Biostatistics and Medical Informatics Department of StatisticsCenter for Demography of Health and AgingUniversity of Wisconsin-MadisonWl 53726USA Department of Mathematics the Hong Kong University of Science and TechnologyHong KongChina Department of Biostatistics Yale School of Public HealthNew HavenCT 06510USA Department of Genetics Yale UniversityNew HavenCT 06510USA Program of Computational Biology and Bioinformatics Yale UniversityNew HavenCT 06510USA

Since the first success of genome wide association study(GWAS)was reported in 2005 by Hoh and colleagues on the identification of a major gene for age related macular degeneration,many thousands of published studies have reported reproducible association signals between hundreds of thousands of genetic variants and thousands of traits and diseases in the past 16 *** is a growing number of biobanks with up to one million participants developed across the world to facilitate genetic studies of complex traits through ***,many consortium projects have been initiated to collect diverse types of data that have proved very valuable for integrated analysis of GWAS *** rich data present both great opportunities and challenges to scientists on data management,computation,analysis,integration,and *** special issue of Quantitative Biology collects nine papers that cover major progresses,challenges,and future directions for GWAS analysis.

关键词： hundreds GWAS initiated

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Trends and factors associated with initial and recurrent methicillin-resistant Staphylococcus aureus (MRSA) skin and soft-tissue infections among HIV-infected persons: An 18-year study

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Journal of the International Association of Providers of AIDS Care 2014年第3期13卷 206-213页

作者： Vyas, Kartavya J. Shadyab, Aladdin H. Lin, Chii-Dean Crum-Cianflone, Nancy F. Infectious Disease Clinical Research Program Uniformed Services University of the Health Sciences Bethesda MD United States Infectious Disease Clinic Naval Medical Center San Diego San Diego CA United States Department of Bioinformatics and Medical Informatics San Diego State University San Diego CA United States Graduate School of Public Health San Diego State University San Diego CA United States Deployment Health Research Department Naval Health Research Center San Diego CA United States

Background: Factors associated with initial methicillin-resistant Staphylococcus aureus (MRSA) skin and soft-tissue infections (SSTIs) and their recurrence have not been fully elucidated among HIV-infected persons. Methods: We retrospectively evaluated a large cohort of HIV-infected patients from 1993 to 2010 for culture-proven MRSA SSTIs. Separate logistic regression models evaluated factors associated with initial and recurrent infections. Results: Of the 794 patients, 63 (8%) developed an initial infection (19.8 infections/1000 person years [PY]);risk factors included CD4 count <500 cells/mm3 and HIV RNA level ≥400 copies/mL (P < .01), US Centers for Disease Control and Prevention (CDC) stage C versus A/B (P < .01), and injection drug use (IDU, P < .01). In all, 27% developed recurrence (206 infections/1000 PY);risk factors included hospital admission (P = .02). Minocycline for treatment of the initial infection was associated with an 80% decreased odds for recurrence (P = .03). Conclusion: HIV control and avoidance of IDU may be useful in reducing rates of MRSA SSTIs among HIV-infected persons. © The Author(s) 2013.

关键词： epidemiology HIV MRSA recurrence risk factors

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Improving microbiome classification with Dirichlet-Multinomial models 9

Improving microbiome classification with Dirichlet-Multinomi...

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9th International Conference on bioinformatics and Computational Biology, BICOB 2017

作者： Gao, Xiang Lin, Huaiying Dong, Qunfeng Department of Public Health Sciences Loyola University Chicago Health Sciences Division MaywoodIL60153 United States Center for Biomedical Informatics Loyola University Chicago Health Sciences Division MaywoodIL60153 United States Bioinformatics Program Loyola University Chicago Lake Shore Campus ChicagoIL60660 United States Department of Computer Science Loyola University Chicago Water Tower Campus ChicagoIL60611 United States

ISBN: (纸本)9781943436071

Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis. We have developed a Bayes classifier by modeling microbial compositions with Dirichlet-Multinomial distributions, which are widely used to model multi-categorical count data with extra variation. The parameters of the Dirichlet-Multinomial distributions are estimated from training microbiome datasets based on maximum likelihood. The posterior probability of a microbiome sample belonging to disease or healthy category is calculated based on Bayes' theorem, using the likelihood values computed from the estimated Dirichlet-Multinomial distribution, as well as a prior probability estimated from the training microbiome dataset or previously published information on disease prevalence. When tested on real-world microbiome datasets, our method, called DBMC, consistently shows better classification accuracy than a previously published Bayesian method based on a Dirichlet-Multinomial Mixture model. A unique advantage of DMBC is its builtin automatic feature selection, capable of identifying a subset of microbial taxa with the best classification accuracy between different classes of samples based on cross-validation. This unique ability enables DMBC to maintain and even improve its accuracy at modeling species-level taxa.

关键词： Classification (of information)

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A Bayesian framework for marker gene taxonomic classification based on sequence alignment 9

A Bayesian framework for marker gene taxonomic classificatio...

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9th International Conference on bioinformatics and Computational Biology, BICOB 2017

作者： Gao, Xiang Lin, Huaiying Revanna, Kashi Dong, Qunfeng Department of Public Health Sciences Loyola University Chicago Health Sciences Division MaywoodIL60153 United States Center for Biomedical Informatics Loyola University Chicago Health Sciences Division MaywoodIL60153 United States Bioinformatics Program Loyola University Chicago Lake Shore Campus ChicagoIL60660 United States Department of Computer Science Loyola University Chicago Water Tower Campus ChicagoIL60611 United States

ISBN: (纸本)9781943436071

Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers. The existing methods either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, typically ignoring other database sequences except the best hit, or use nucleotide kmer frequency as the proxy for sequence similarity measurement, a design driven by the pursuit of computational speed instead of classification accuracy. We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our software, called BLCA, is implemented in Python and freely available at https://***/qunfengdong/BLCA.

关键词： Classification (of information)

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Insights into the solution structure of the actin-binding tail domain of metavinculin by small angle X-ray scattering and molecular dynamics simulations

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International Journal of Biological Macromolecules 2025年 144376页

作者： Zeynep Aslıhan Durer Hande İpek İnce Zeynep Şevval Düvenci Emel Timuçin Tobias Gräwert Oya Orun Beki Kan Zehra Sayers School of Medicine Department of Biophysics Acibadem Mehmet Ali Aydinlar University Istanbul Turkey Faculty of Pharmacy Department of Biochemistry Acibadem Mehmet Ali Aydinlar University Istanbul Turkey Institute of Health Sciences Department of Biophysics Marmara University Istanbul Turkey Institute of Health Sciences Department of Biostatistics and Bioinformatics Acibadem Mehmet Ali Aydinlar University Istanbul Turkey School of Medicine Department of Biostatistics and Medical Informatics Acibadem Mehmet Ali Aydinlar University Istanbul Turkey European Molecular Biology Laboratory - Hamburg Unit Biological Small Angle Scattering Group Hamburg Germany School of Medicine Department of Biophysics Marmara University Istanbul Turkey Faculty of Engineering and Natural Sciences Molecular Biology Genetics and Bioengineering Program Sabanci University İstanbul Turkey

Vinculin is a ubiquitously expressed focal adhesion protein that plays an important role in cell-matrix and cell-to-cell junctions. Metavinculin, a muscle-specific splice variant of vinculin, contains a 68-amino acid disordered insert region in its actin binding tail domain (MVt). Mutations in this insert are linked to cardiomyopathies. This study investigates the solution structures and structural ensembles of wild-type (WT) and two mutant MVts, ΔLeu954 and R975W, which have been associated with cardiomyopathies, using small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations. SAXS analyses revealed subtle differences in the estimated maximum dimensions and corroborated the elongated shape of the MVts. Quantitative comparisons of SAXS profiles indicated similarity between the WT and ΔLeu954, whereas R975W exhibited differences in the small-angle region. MD simulations demonstrated reduced conformational flexibility and greater packing of the insert in WT compared to mutants. Notably, a salt-bridge observed between R975 and D928 in a WT simulation provides a structural basis for the destabilization caused by the R975W mutation. These findings provide insights into the structure and dynamics of WT and mutant MVt, reflecting the promise of SAXS combined with MD simulations to elucidate the structural properties of proteins with structural disorder.

关键词： Metavinculin Molecular dynamics simulations Mutation SAXS Tail domain

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An integrative approach revealing the landscape of long noncoding RNAs in human brain

An integrative approach revealing the landscape of long nonc...

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2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

作者： Li, Dan Yang, William Arthur, Carolyn Yoshigoe, Kenji Liu, Jun Tong, Weida Yang, Mary MidSouth Bioinformatics Center and Joint Bioinformatics Ph.D. Program University of Arkansas at Little Rock University of Arkansas for Medical Sciences 2801 S. University Avenue Little RockAR72204 United States Harvard T. H. Chan School of Public Health Harvard University One Oxford Street CambridgeMA02138 United States United States Food and Drug Adminstration National Center for Toxicological Research 3900 NCTR Road JeffersonAR72079 United States Department of Informatics Science MidSouth Bioinformatics Center and Joint Bioinformatics Ph.D. Program University of Arkansas at Little Rock University of Arkansas for Medical Sciences 2801 S. Univ. Avenue Little RockAR72204 United States

ISBN: (纸本)9781509055104

Long noncoding RNAs (lncRNAs) function as regulators and play critical roles in diverse biological processes, however, the majority of lncRNAs are not characterized, and their roles in regulation remain to be elucidated. Present RNA-seq assembly approaches are insufficient to identify complete full-length transcripts and often reveal excessive amount of single-exon lncRNAs, many of them tend to be the fragments of transcripts. Here we developed an integrated approach that combined the results from reference-guided and de novo assembly to systematically identify lncRNAs. Experiments on simulated data and real RNA-seq data showed that our method effectively yielded a more comprehensive set of lncRNAs. We applied the method on 299 human brain RNA-seq samples with a total of 4.5 billion raw reads. The results yield a comprehensive lncRNAs mapping in human brain, allowing discovery of novel lncRNAs and further function annotation. © 2016 IEEE.

关键词： RNA

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The rapid diagnosis of intraamniotic infection with nanopore sequencing

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American Journal of Obstetrics and Gynecology 2025年

作者： Chaemsaithong, Piya Romero, Roberto Pongchaikul, Pisut Warintaksa, Puntabut Mongkolsuk, Paninee Bhuwapathanapun, Maolee Kotchompoo, Kanyaphat Nimsamer, Pattaraporn Kruasuwan, Worarat Amnuaykiatlert, Orrakanya Vivithanaporn, Pornpun Meyyazhagan, Arun Awonuga, Awoniyi Settacomkul, Rapeewan Singhsnaeh, Arunee Laolerd, Warawut Santanirand, Pitak Thaipisuttikul, Iyarit Wongsurawat, Thidathip Jenjaroenpun, Piroon Department of Obstetrics and Gynecology Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Program in Translational Medicine Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Pregnancy Research Branch Division of Obstetrics and Maternal-Fetal Medicine Division of Intramural Research Eunice Kennedy Shriver National Institute of Child Health and Human Development National Institutes of Health United States Department of Health and Human Services Bethesda MD United States Department of Obstetrics and Gynecology University of Michigan Ann Arbor MI United States Department of Epidemiology and Biostatistics Michigan State University East Lansing MI United States Chakri Naruebodindra Medical Institute Faculty of Medicine Ramathibodi Hospital Mahidol University Samut Prakarn Thailand Integrative Computational BioScience Center Mahidol University Nakhon Pathom Thailand Institute of Infection Veterinary and Ecological Sciences University of Liverpool Liverpool United Kingdom Division of Medical Bioinformatics Research Department Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Siriraj Long-Read Lab (Si-LoL) Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Mahidol University International Demonstration School Mahidol University Nakhon Pathom Thailand Department of Obstetrics and Gynecology Wayne State University School of Medicine Detroit MI United States Department of Life Sciences Christ University Bengaluru India Department of Pathology Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Department of Microbiology Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Department of Biomedical Informatics University of Arkansas for Medical Sciences Little Rock AR United States

Background: Intraamniotic infection (defined as intraamniotic inflammation with microorganisms) is an important cause of the preterm labor syndrome. Methods for the detection of microorganisms in amniotic fluid are culture and/or polymerase chain reaction assay. However, both methods take time, and the results are rarely available for clinical decision-making. Nanopore sequencing technology offers real-time, long-read sequencing that can produce rapid results. Objective: To determine 1) the diagnostic performance of the 16S rDNA nanopore sequencing method for the identification of microorganisms in patients with intraamniotic inflammation and 2) the relationship between microbial burden and the intensity of the amniotic fluid inflammatory response. Study Design: We performed a prospective cohort study that included singleton pregnancies presenting with symptoms of preterm labor with intact membranes or of preterm prelabor rupture of the membranes. Amniotic fluid samples were obtained for the evaluation of bacteria in the amniotic cavity using cultivation and polymerase chain reaction-based 16S Sanger sequencing methods. Participants were classified into 4 groups according to the results of an amniotic fluid culture, 16S Sanger sequencing, and an amniotic fluid interleukin 6 concentration: 1) no intraamniotic infection and intraamniotic inflammation (interleukin 6 <2.6 ng/mL, and no microorganisms in the amniotic cavity, as determined by culture or 16S Sanger sequencing);2) microbial invasion of the amniotic cavity without intraamniotic inflammation, defined by the presence of bacteria detected by culture or 16S Sanger sequencing;3) sterile intraamniotic inflammation (interleukin 6 ≥2.6 ng/mL without microbial invasion of the amniotic cavity);and 4) intraamniotic infection (interkeukin 6 ≥2.6 ng/mL with microbial invasion of the amniotic cavity). Patients who underwent a mid-trimester amniocentesis, had no intraamniotic infection or intraamniotic inflammation, and de

关键词： 16S 16S PCR 16S rDNA genes 16S rRNA genes amniocentesis amniotic cavity amniotic fluid bacteria bacterial infection cultivation culture DNA DNA sequencing Escherichia coli (E. coli) infection intraamniotic infection intraamniotic inflammation long-read sequencing microbial invasion of the amniotic cavity (MIAC) microorganism molecular microbiologic technique Mycoplasma species nanopore Oxford nanopore technology (ONT) polymerase chain reaction (PCR) pregnancy preterm preterm labor preterm prelabor rupture of the membranes (PROM) preterm PROM rapid sequencing removal of false positive RNA Sanger sequencing sequencing short-read sterile inflammation third-generation sequencing Ureaplasma species

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The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

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Cell 2025年

作者： Pekar, Jonathan E. Lytras, Spyros Ghafari, Mahan Magee, Andrew F. Parker, Edyth Wang, Yu Ji, Xiang Havens, Jennifer L. Katzourakis, Aris Vasylyeva, Tetyana I. Suchard, Marc A. Hughes, Alice C. Hughes, Joseph Rambaut, Andrew Robertson, David L. Dellicour, Simon Worobey, Michael Wertheim, Joel O. Lemey, Philippe Institute of Ecology and Evolution University of Edinburgh Edinburgh United Kingdom Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla 92093 CA United States Department of Biomedical Informatics University of California San Diego La Jolla 92093 CA United States Department of Medicine University of California San Diego La Jolla 92093 CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Medical Research Council University of Glasgow Centre for Virus Research Glasgow United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles 90095 CA United States Department of Immunology and Microbiology The Scripps Research Institute La Jolla 92037 CA United States Institute of Genomics and Global Health Redeemer's University Osun State Ede Nigeria Department of Computer Science and Engineering University of California San Diego La Jolla 92093 CA United States Department of Mathematics School of Science and Engineering Tulane University New Orleans LA United States Department of Population Health and Disease Prevention University of California Irvine Irvine 92617 CA United States Department of Biostatistics Fielding School of Public Health University of California Los Angeles Los Angeles 90095 CA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles 90095 CA United States School of Biological Sciences University of Hong Kong Hong Kong Hong Kong China Biodiversity Green Development Foundation Beijing China Spatial Epidemiology Lab (SpELL) Université Libre de Bruxelles CP160/12 50 av. FD Roosevelt Bruxelles 1050 Belgium Department of Microbiology Immunology and Transplantation Rega Institute

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed less than a decade prior to their emergence in humans. Phylogeographic analyses show bat sarbecoviruses traveled at rates approximating their horseshoe bat hosts and circulated in Asia for millennia. We find that the direct ancestors of SARS-CoV and SARS-CoV-2 are unlikely to have reached their respective sites of emergence via dispersal in the bat reservoir alone, supporting interactions with intermediate hosts through wildlife trade playing a role in zoonotic spillover. These results can guide future sampling efforts and demonstrate that viral genomic regions extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses. © 2025 The Authors

关键词： molecular epidemiology phylogeography sarbecoviruses virus evolution

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Integrative modeling of transmitted and de novo variants identifies novel risk genes for congenital heart disease

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Quantitative Biology 2021年第2期9卷 216-227页

作者： Mo Li Xue Zeng Chentian Jin Sheng Chih Jin Weilai Dong Martina Brueckner Richard Lifton Qiongshi Lu Hongyu Zhao Department of Biostatistics Yale School of Public HealthNew HavenCT 06510USA Department of Genetics Yale UniversityNew HavenCT 06510USA Department of Molecular Cellular&Developmental BiologyYale UniversityCT 06510USA Department of Genetics Washington University School of MedicineSt LouisMO 63110USA Department of Pediatrics Yale UniversityNew HavenCT 06510USA Laboratory of Human Genetics and Genomics Rockefeller UniversityNew YorkNY 10065USA Department of Biostatistics and Medical Informatics University of Wisconsin-MadisonMadisonWl 53792USA Program of Computational Biology and Bioinformatics Yale UniversityNew HavenCT 06510USA

Background:Whole-exome sequencing(WES)studies have identified multiple genes enriched for de novo mutations(DNMs)in congenital heart disease(CHD)***,risk gene identification based on DNMs alone remains statistically challenging due to heterogenous etiology of CHD and low mutation rate in each ***:In this manuscript,we introduce a hierarchical Bayesian framework for gene-level association test which jointly analyzes de novo and rare transmitted *** integrative modeling of multiple types of genetic variants,gene-level annotations,and reference data from large population cohorts,our method accurately characterizes the expected frequencies of both de novo and transmitted variants and shows improved statistical power compared to analyses based on DNMs ***:Applied to WES data of 2,645 CHD proband-parent trios,our method identified 15 significant genes,half of which are novel,leading to new insights into the genetic bases of ***:These results showcase the power of integrative analysis of transmitted and de novo variants for disease gene discovery.

关键词： rare variants gene-level association test congenital heart disease de novo mutation

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Graph Representation Learning in Biomedicine

arXiv

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arXiv 2021年

作者： Li, Michelle M. Huang, Kexin Zitnik, Marinka Bioinformatics and Integrative Genomics Program Harvard Medical School BostonMA02115 United States Health Data Science Program Harvard T.H. Chan School of Public Health BostonMA02115 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Broad Institute of MIT and Harvard CambridgeMA02142 United States Harvard Data Science Initiative CambridgeMA02138 United States

Biomedical networks (or graphs) are universal descriptors for systems of interacting elements, from molecular interactions and disease co-morbidity to healthcare systems and scientific knowledge. Advances in artificial intelligence, specifically deep learning, have enabled us to model, analyze, and learn with such networked data. In this review, we put forward an observation that long-standing principles of systems biology and medicine-while often unspoken in machine learning research-provide the conceptual grounding for representation learning on graphs, explain its current successes and limitations, and even inform future advancements. We synthesize a spectrum of algorithmic approaches that, at their core, leverage graph topology to embed networks into compact vector spaces. We also capture the breadth of ways in which representation learning has dramatically improved the state-of-the-art in biomedical machine learning. Exemplary domains covered include identifying variants underlying complex traits, disentangling behaviors of single cells and their effects on health, assisting in diagnosis and treatment of patients, and developing safe and effective medicines. © 2021, CC BY.

关键词： Vector spaces

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