Degui Zhi

Summary

Affiliation: University of Alabama at Birmingham
Country: USA

Publications

  1. pmc Statistical quantification of methylation levels by next-generation sequencing
    Guodong Wu
    Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 6:e21034. 2011
  2. pmc Genotype calling from next-generation sequencing data using haplotype information of reads
    Degui Zhi
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
    Bioinformatics 28:938-46. 2012
  3. pmc Statistical guidance for experimental design and data analysis of mutation detection in rare monogenic mendelian diseases by exome sequencing
    Degui Zhi
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 7:e31358. 2012
  4. pmc Hierarchical generalized linear models for multiple groups of rare and common variants: jointly estimating group and individual-variant effects
    Nengjun Yi
    Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA
    PLoS Genet 7:e1002382. 2011
  5. pmc A unified GMDR method for detecting gene-gene interactions in family and unrelated samples with application to nicotine dependence
    Guo Bo Chen
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, 1665 University Boulevard, RPHB 327, Birmingham, AL, 35294 0022, USA
    Hum Genet 133:139-50. 2014
  6. pmc Joint haplotype phasing and genotype calling of multiple individuals using haplotype informative reads
    Kui Zhang
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
    Bioinformatics 29:2427-34. 2013
  7. pmc Genomics of Post-Prandial Lipidomic Phenotypes in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study
    Marguerite R Irvin
    Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 9:e99509. 2014
  8. pmc Bayesian analysis of rare variants in genetic association studies
    Nengjun Yi
    Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35294 0022, USA
    Genet Epidemiol 35:57-69. 2011
  9. pmc Pathway-based approaches for sequencing-based genome-wide association studies
    Guodong Wu
    Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
    Genet Epidemiol 37:478-94. 2013
  10. pmc Expression signature of IFN/STAT1 signaling genes predicts poor survival outcome in glioblastoma multiforme in a subtype-specific manner
    Christine W Duarte
    Department of Biostatistics Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 7:e29653. 2012

Detail Information

Publications12

  1. pmc Statistical quantification of methylation levels by next-generation sequencing
    Guodong Wu
    Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 6:e21034. 2011
    ..Therefore, there is a need to investigate the statistical issues related to the quantification of methylation levels for these emerging technologies, with the goal of developing an accurate quantification method...
  2. pmc Genotype calling from next-generation sequencing data using haplotype information of reads
    Degui Zhi
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
    Bioinformatics 28:938-46. 2012
    ..Current LD-based methods use read counts or genotype likelihoods at individual potential polymorphic sites (PPSs). Reads that span multiple PPSs (jumping reads) can provide additional haplotype information overlooked by current methods...
  3. pmc Statistical guidance for experimental design and data analysis of mutation detection in rare monogenic mendelian diseases by exome sequencing
    Degui Zhi
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 7:e31358. 2012
    ....
  4. pmc Hierarchical generalized linear models for multiple groups of rare and common variants: jointly estimating group and individual-variant effects
    Nengjun Yi
    Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA
    PLoS Genet 7:e1002382. 2011
    ..The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/)...
  5. pmc A unified GMDR method for detecting gene-gene interactions in family and unrelated samples with application to nicotine dependence
    Guo Bo Chen
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, 1665 University Boulevard, RPHB 327, Birmingham, AL, 35294 0022, USA
    Hum Genet 133:139-50. 2014
    ....
  6. pmc Joint haplotype phasing and genotype calling of multiple individuals using haplotype informative reads
    Kui Zhang
    Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
    Bioinformatics 29:2427-34. 2013
    ..Although our model improves the accuracy of genotype calling and haplotype phasing, haplotype information in reads covering non-adjacent sites and/or more than two adjacent sites is not used because of the severe computational burden...
  7. pmc Genomics of Post-Prandial Lipidomic Phenotypes in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study
    Marguerite R Irvin
    Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 9:e99509. 2014
    ..We hypothesized that detailed lipid profiles (eg, sterols and fatty acids) may help elucidate specific genetic and dietary pathways contributing to the PPL response...
  8. pmc Bayesian analysis of rare variants in genetic association studies
    Nengjun Yi
    Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35294 0022, USA
    Genet Epidemiol 35:57-69. 2011
    ..We evaluate the proposed method and compare its performance to existing methods on extensive simulated data. The results show that the proposed method performs well under all situations and is more powerful than existing approaches...
  9. pmc Pathway-based approaches for sequencing-based genome-wide association studies
    Guodong Wu
    Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
    Genet Epidemiol 37:478-94. 2013
    ..We applied pathway association analysis to an exome-sequencing data of the chronic obstructive pulmonary disease, and found that the WKS-Variant method confirms associated genes previously published...
  10. pmc Expression signature of IFN/STAT1 signaling genes predicts poor survival outcome in glioblastoma multiforme in a subtype-specific manner
    Christine W Duarte
    Department of Biostatistics Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
    PLoS ONE 7:e29653. 2012
    ....
  11. pmc Length bias correction for RNA-seq data in gene set analyses
    Liyan Gao
    Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
    Bioinformatics 27:662-9. 2011
    ..Since transcript length is not related to gene expression, adjusting for such length dependency in GSA becomes necessary...
  12. pmc Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the Genetics of Lipid Lowering Drugs and Diet Network study
    Bertha Hidalgo
    Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL
    Diabetes 63:801-7. 2014
    ..75 × 10(-3) and P = 3.35 × 10(-2), respectively). Our findings suggest that methylation of a CpG site within ABCG1 is associated with fasting insulin and merits further evaluation as a novel disease risk marker. ..