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APIR:Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control

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Genomics, Proteomics & bioinformatics 2024年第2期22卷 171-187页

作者： Yiling Elaine Chen Xinzhou Ge Kyla Woyshner MeiLu McDermott Antigoni Manousopoulou Scott B.Ficarro Jarrod A.Marto Kexin Li Leo David Wang Jingyi Jessica Li Department of Statistics and Data Science University of CaliforniaLos AngelesCA 90095USA Department of Immuno-Oncology Beckman Research InstituteCity of Hope National Medical CenterDuarteCA 91010USA Department of Quantitative and Computational Biology University of Southern CaliforniaLos AngelesCA 90089USA Department of Cancer Biology and Blais Proteomics Center Dana-Farber Cancer InstituteDepartment of PathologyBrigham and Women’s Hospital and Harvard Medical SchoolBostonMA 02215USA Department of Pediatrics City of Hope National Medical CenterDuarteCA 91010USA bioinformatics Interdepartmental Program University of CaliforniaLos AngelesCA 90095USA Department of Human Genetics University of CaliforniaLos AngelesCA 90095USA Department of Computational Medicine University of CaliforniaLos AngelesCA 90095USA Department of biostatistics University of CaliforniaLos AngelesCA 90095USA

Advances in mass spectrometry(MS)have enabled high-throughput analysis of proteomes in biological *** state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide–spectrum matches(PSMs),which convert mass spectra to peptide *** database search algorithms use distinct search strategies and thus may identify unique ***,no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate(FDR).To fill in this gap,we proposed a statistical framework,Aggregation of Peptide Identification Results(APIR),that is universally compatible with all database search ***,under an FDR threshold,APIR is guaranteed to identify at least as many,if not more,peptides as individual database search algorithms *** of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the *** data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search *** APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis,e.g.,differential gene expression analysis on RNA sequencing *** APIR R package is available at https://***/yiling0210/APIR.

关键词： Shotgun proteomics Peptide–spectrum match Peptide identification Aggregation of lists FDR control

Prevalence of Work-Aggravated Asthma among Bakery Workers in Abidjan (Cote d’Ivoire)

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Health 2024年第3期16卷 204-217页

作者： Loukou Leandre Konan Esme Marie Laure Essis Brou Michel Kouassi Marius Kedote Julius Fobil William Yavo Ossey Bernard Yapo Issaka Tiembre National institute of Public Health Abidjan Cote d’Ivoire interuniversity Doctoral Program Cotonou Benin Medical Sciences Training and Research Unit Department of Public Health and Biostatistics Felix Houphouet Boigny University Abidjan C&#244te d’Ivoire Global Environmental Occupational Health (GEOHealth) Accra Ghana UFR of Pharmaceutical and Biological Sciences Department of Public Health Felix Houphou&#235t Boigny University Abidjan Cote d’Ivoire Nangui Abrogoua University Abidjan C&#244te d’Ivoire National institute of Public Hygiene Abidjan C&#244te d’Ivoire

Introduction: Work-aggravated asthma is pre-existing or concomitant asthma whose symptoms are aggravated by the work environment. The aim of this study was to determine the prevalence of this pathology and its associated factors among bakery workers in Abidjan. Materials and Methods: This descriptive and analytical cross-sectional study was conducted over a period of four (4) months from 18 December 2019 to 18 April 2020. Two questionnaires were used, one on employees and the other on the indoor environment of bakeries. In addition, a spirometry test was performed on all bakery workers. statistical analysis was performed using stata 15.1 software. Results: A total of 599 bakery employees, including bakers (59.73%), sales assistants/ cashiers (23.52%), cleaners (6.34%) and administrative staff (10.18%), were investigated. The mean age was 30.8 ± 8 years, with a sex ratio (M/F) = 2.2. Asthma symptoms were found in 95 (15.86%) employees, of whom 74 (77.9%) had work-related asthma and 11 (14.9%) had asthma aggravated by work. The factors associated with work-aggravated asthma were personal or family history of allergy or atopy [ORa = 3.75;CI95%: 1.56 - 8.93;p = 0.003], exposure to dust [ORa = 5.01;CI95%: 1.43 - 7.50;p = 0.011] and humidity level (60% - 70%) [ORa = 1.80;CI 95%: 0.99 - 3.28;p = 0.05]. Conclusion: Work-aggravated asthma is a reality in bakeries in Abidjan, with an estimated prevalence of 14.9%. Two of the three factors associated with this condition suggest a link with indoor air pollution. Combating air pollution in these establishments must therefore be a priority for the relevant authorities, in order to provide employees with a working environment that protects their health.

关键词： Work-Aggravated Asthma Occupational Asthma Work-Related Asthma Bakeries Abidjan Ivory Coast

Integration between Genomic and Computational statistical Surveys for the Screening of SNP Genetic Variants in Inflammatory Bowel Disease (IBD) Pediatric Patients*

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Computational Molecular Bioscience 2024年第3期14卷 146-191页

作者： Dago Dougba Noel Koffi N’Guessan Bénédicte Sonia Dagnogo Olefongo Daramcoum Wentoin Alimata Marie-Pierre Mauro Giacomelli Dagnogo Dramane Eboulé Ago Eliane Rebecca Yao Saraka Didier Martial Diarrassouba Nafan Giovanni Malerba Raffaele Badolato Department of Clinical and Experimental Sciences University of Brescia Brescia Italy Angelo Nocivelli institute of Molecular Medicine Childrens Hospital ASST Spedali Civili Brescia Italy Unit of biostatistics and Biomathematics & Unit of bioinformatics Department of Molecular and Translational Medicine University of Brescia Brescia Italy Biological Sciences Training and Research Unit Department of Genetic and Biochemistry Peleforo Gon Coulibaly University Korhogo Cte dIvoire Department of Neurosciences Biomedicine and Movement Sciences Section of Biology and Genetics University of Verona Verona Italy Biosciences Training and Research Unit Biology and Health Laboratory Felix Houphouet-Boigny University Abidjan Cte dIvoire

Inflammatory bowel diseases (IBD) are complex multifactorial disorders that include Crohn’s disease (CD) and ulcerative colitis (UC). Considering that IBD is a genetic and multifactorial disease, we screened for the distribution dynamism of IBD pathogenic genetic variants (single nucleotide polymorphisms;SNPs) and risk factors in four (4) IBD pediatric patients, by integrating both clinical exome sequencing and computational statistical approaches, aiming to categorize IBD patients in CD and UC phenotype. To this end, we first aligned genomic read sequences of these IBD patients to hg19 human genome by using bowtie 2 package. Next, we performed genetic variant calling analysis in terms of single nucleotide polymorphism (SNP) for genes covered by at least 20 read genomic sequences. Finally, we checked for biological and genomic functions of genes exhibiting statistically significant genetic variant (SNPs) by introducing Fitcon genomic parameter. Findings showed Fitcon parameter as normalizing IBD patient’s population variability, as well as inducing a relative good clustering between IBD patients in terms of CD and UC phenotypes. Genomic analysis revealed a random distribution of risk factors and as well pathogenic SNPs genetic variants in the four IBD patient’s genome, claiming to be involved in: i) Metabolic disorders, ii) Autoimmune deficiencies;iii) Crohn’s disease pathways. Integration of genomic and computational statistical analysis supported a relative genetic variability regarding IBD patient population by processing IBD pathogenic SNP genetic variants as opposite to IBD risk factor variants. Interestingly, findings clearly allowed categorizing IBD patients in CD and UC phenotypes by applying Fitcon parameter in selecting IBD pathogenic genetic variants. Considering as a whole, the study suggested the efficiency of integrating clinical exome sequencing and computational statistical tools as a right approach in discriminating IBD phenotypes as well as improvi

关键词： Inflammatory Bowel Disease (IBD) Crohn Disease (CD) Ulcerative Colitis (UC) Clinical Exome Analysis Computational Statistic SNP Genetic Variants

High prevalence of epilepsy in onchocerciasis endemic health areas in Democratic Republic of the Congo

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Infectious Diseases of Poverty 2018年第1期7卷 663-676页

作者： Evy Lenaerts Michel Mandro Deby Mukendi Patrick Suykerbuyk Housseini Dolo Deogratias Wonya’Rossi Françoise Ngave Chellafe Ensoy-Musoro Anne Laudisoit An Hotterbeekx Robert Colebunders Global Health institute University of AntwerpAntwerpBelgium Provincial Health Division of Ituri Ministry of HealthBuniaDemocratic Republic of Congo Centre Neuro Psycho Pathologique Universitede Kinshasa(CNPP-UNIKIN)KinshasaDemocratic Republic of Congo International Center of Excellence in Research Faculty of Medicine and OdontostomatologyBamakoMali Neglected Tropical Diseases Control program Ministry of HealthBuniaDemocratic Republic of the Congo Centre de Recherche en Maladies Tropicales Hopital General de Reference de RethyRethyDemocratic Republic of Congo interuniversity institute for biostatistics and statistical bioinformatics University of HasseltHasseltBelgium EcoHealth Alliance New YorkUSA Global Health institute Faculty of Medicine and Health SciencesGouverneur Kinsbergen CentrumDoornstraat 3312610 WilrijkBelgium

Background:A high prevalence of epilepsy has been observed in many onchocerciasis endemic *** study is to estimate the prevalence of active epilepsy and exposure to Onchocerca volvulus infection in a rural population in Ituri province,Democratic Republic of ***:In August 2016,a community-based cross-sectional study was conducted in an onchocerciasis endemic area in the rural health zone of Logo,Ituri *** within two neighbouring health areas were randomly *** identify persons with epilepsy,a three-stage approach was *** the first stage,all individuals of the selected households were screened for epilepsy by non-medical field workers using a validated 5-item *** the second and third stage,suspected cases of epilepsy were examined by non-specialist medical doctors,and by a neurologist,respectively.A case of epilepsy was defined according to the 2014 International League Against Epilepsy(ILAE)*** to *** was assessed by testing for IgG4 antibodies to an *** antigen(OV16 Rapid Test,)in individuals aged 3 years and ***:Out of 1389 participants included in the survey,64 were considered to have active epilepsy(prevalence 4.6%)(95%confidence interval[CI]:3.6-5.8).The highest age-specific epilepsy prevalence estimate was observed in those aged 20 to 29 years(8.2%).Median age of epilepsy onset was 10 years,with a peak incidence of epilepsy in the 10 to 15 year-old age ***16 test results were available for 912 participants,of whom 30.5%(95%CI,27.6-33.6)tested *** prevalence of OV16 positivity in a village ranged from 8.6 to 68.0%.After adjusting for age,gender and ivermectin use,a significant association between exposure to onchocerciasis and epilepsy was observed(adjusted odds ratio=3.19,95%CI:1.63-5.64)(P<0.001).Conclusions:A high prevalence of epilepsy and a significant association between epilepsy and exposure to *** were observed in the population in Ituri

关键词： Onchocerciasis epilepsy Prevalence Democratic Republic of Congo

Distance-Based Regression Analysis for Measuring Associations

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Journal of Systems Science & Complexity 2023年第1期36卷 393-411页

作者： SHI Yuke ZHANG Wei LIU Aiyi LI Qizhai LSC Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China biostatistics and bioinformatics Branch Eunice Kennedy Shriver National Institute of Child Health Human Development National Institutes of HealthBethesdaMD 20847USA

Distance-based regression model,as a nonparametric multivariate method,has been widely used to detect the association between variations in a distance or dissimilarity matrix for outcomes and predictor variables of interest in genetic association studies,genomic analyses,and many other research *** on it,a pseudo-F statistic which partitions the variation in distance matrices is often constructed to achieve the *** the best of our knowledge,the statistical properties of the pseudo-F statistic has not yet been well established in the *** fill this gap,the authors study the asymptotic null distribution of the pseudo-F statistic and show that it is asymptotically equivalent to a mixture of chi-squared random *** that the pseudo-F test statistic has unsatisfactory power when the correlations of the response variables are large,the authors propose a square-root F-type test statistic which replaces the similarity matrix with its square *** asymptotic null distribution of the new test statistic and power of both tests are also *** studies are conducted to validate the asymptotic distributions of the tests and demonstrate that the proposed test has more robust power than the pseudo-F *** test statistics are exemplified with a gene expression dataset for a prostate cancer pathway.

关键词： Asymptotic distribution chi-squared-type mixture nonparametric test pseudo-F test similarity matrix

A theoretic study of a distance-based regression model

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Science China Mathematics 2019年第5期62卷 979-998页

作者： Jialu Li Wei Zhang Sanguo Zhang Qizhai Li School of Mathematics and Statistics Beijing Institute of Technology biostatistics and bioinformatics Branch National Institute of Child Health and Human Development School of Mathematical Sciences University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences LSC NCMIS Academy of Mathematics and Systems Science Chinese Academy of Sciences

The distance-based regression model has many applications in analysis of multivariate response regression in various ?elds, such as ecology, genomics, genetics, human microbiomics, and neuroimaging. It yields a pseudo F test statistic that assesses the relation between the distance(dissimilarity) of the subjects and the predictors of interest. Despite its popularity in recent decades, the statistical properties of the pseudo F test statistic have not been revealed to our knowledge. This study derives the asymptotic properties of the pseudo F test statistic using spectral decomposition under the matrix normal assumption, when the utilized dissimilarity measure is the Euclidean or Mahalanobis distance. The pseudo F test statistic with the Euclidean distance has the same distribution as the quotient of two Chi-squared-type mixtures. The denominator and numerator of the quotient are approximated using a random variable of the form ξχ_d^2+ η, and the approximate error bound is given. The pseudo F test statistic with the Mahalanobis distance follows an F *** simulation studies, the approximated distribution well matched the "exact" distribution obtained by the permutation procedure. The obtained distribution was further validated on H1N1 in?uenza data, aging human brain data, and embryonic imprint data.

关键词： distance-based regression Euclidean pseudo F test statistic Mahalanobis

Computational Methods for Single-cell Multi-omics Integration and Alignment

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Genomics, Proteomics & bioinformatics 2022年第5期20卷 836-849页

作者： Stefan Stanojevic Yijun Li Aleksandar Ristivojevic Lana X.Garmire Department of Computational Medicine and bioinformatics University of MichiganAnn ArborMI 48109USA Department of biostatistics University of MichiganAnn ArborMI 48109USA Amherst College AmherstMA 01002USA

Recently developed technologies to generate single-cell genomic data have made a revolutionary impact in the field of ***-omics assays offer even greater opportunities to understand cellular states and biological *** problem of integrating different omics data with very different dimensionality and statistical properties remains,however,quite challenging.A growing body of computational tools is being developed for this task,leveraging ideas ranging from machine translation to the theory of networks,and represents another frontier on the interface of biology and data *** goal in this review is to provide a comprehensive,up-to-date survey of computational techniques for the integration of single-cell multi-omics data,while making the concepts behind each algorithm approachable to a non-expert audience.

关键词： Single-cell Multi-omics Machine learning Unsupervised learning Integration

Metabolite variation in hybrid corn grain from a large-scale multisite study

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The Crop Journal 2016年第3期4卷 177-187页

作者： Mingjie Chen R.Shyama Prasad Rao Yiming Zhang Cathy Zhong Jay J.Thelen Haixia institute of Science and Technology Horticulture Biology and Metabolomics CenterFujian Agriculture and Forestry University Department of Biochemistry Christopher S.Bond Life Science CenterUniversity of Missouri biostatistics and bioinformatics Division Yenepoya Research CenterYenepoya University Regulatory Group Du Pont Experimental Station

Metabolite composition is strongly affected by genotype,environment,and interactions between genotype and environment,although the extent of variation caused by these factors may depend upon the type of *** characterize the complexity of genotype,environment,and their interaction in hybrid seeds,50 genetically diverse non-genetically modified(GM) maize hybrids were grown in six geographically diverse locations in North *** metabolites from 553 harvested corn grain samples were isolated and analyzed by gas chromatography–mass spectrometry and 45 metabolites detected in all samples were used to generate a data matrix for statistical *** was moderate variation among biological replicates and across genotypes and test *** genotype effects were detected by univariate and Hierarchical clustering analyses(HCA) when environmental effects were ***,environment exerted larger effects than genotype,and polar metabolite accumulation showed a geographic *** conclude that it is possible to increase seed polar metabolite content in hybrid corn by selection of appropriate inbred lines and growing regions.

关键词： Corn grain Genotype Environment GC–MS Metabolomics

Partial least squares regression and principal component analysis:similarity and differences between two popular variable reduction approaches

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General Psychiatry 2022年第1期35卷 67-71页

作者： Chenyu Liu Xinlian Zhang Tanya T Nguyen Jinyuan Liu Tsungchin Wu Ellen Lee Xin M Tu Division of biostatistics and bioinformatics Herbert Wertheim School of Public Health and Human Longevity ScienceUC San DiegoLa JollaCaliforniaUSA Department of Psychiatry Stein Institute for Research on AgingUC San DiegoLa JollaCaliforniaUSA

SUMMARY In many statistical applications,composite variables are constructed to reduce the number of variables and improve the performances of statistical analyses of these variables,especially when some of the variables are highly *** component analysis(PCA)and factor analysis(FA)are generally used for such *** the variables are used as explanatory or independent variables in linear regression analysis,partial least squares(PLS)regression is a better *** PCA and FA,PLS creates composite variables by also taking into account the response,or dependent variable,so that they have higher correlations with the response than composites from their PCA and FA *** this report,we provide an introduction to this useful approach and illustrate it with data from a real study.

关键词： composite composites component