Dissertation > Excellent graduate degree dissertation topics show

Statistical counting character position parameters and effect parameters

Author: LiuZuo
Tutor: MaWeiJun
School: Heilongjiang University
Course: Applied Mathematics
Keywords: Count trait Quantitative trait loci Multiple-interval mapping Mul-tivariate Poisson distribution EM algorithm
CLC: Q348
Type: Master's thesis
Year: 2012
Downloads: 7
Quote: 0
Read: Download Dissertation

Abstract


The variation of many quantitative traits in human, plants, or animals can beattributed to genetic efects. Quantitative traits locus (QTL) mapping, which mapsloci in the genome that afect a quantitative trait, is of important scientific andeconomic value. The method of interval mapping is widely used for the geneticmapping of QTL, and statistical methods have been extensively studied in mappingQTL. However, some biological trait is not controlled by one gene, not by manygenes, so multiple-interval mapping (MIM) will be used in mapping QTLs. Whengrown in diferent environments, an organism may show a range of phenotypes.Thegenotype of an organism, its environment, and the interaction between genotypeand environment determine the phenotype displayed. Phenotypic plasticity is theability of a single genotype to produce multiple phenotypes in response to diferentenvironments.While some biological traits are not continuous, but are discrete, for example,the number of branches. In this article, we consider the estimation problem of QTLparameters that control the phenotypic plasticity in diferent environments. Wedevelop a statistical methods that focus on count trait, while many of statisticalmethods are implemented to continuous data. The model is derived with in amultivariate Poisson mixture model on the basis of multivariate Poisson distribution.The EM algorithm is applied to obtain the maximum-likelihood estimates (MLE)of both QTLs position and the Poisson parameter simultaneous. Then, we also usecomputer simulation to study the statistical model, then the simulation results showthat our method has a certain practicality.

Related Dissertations

  1. The Analysis of the Data of Mental Health Status Based on GPCM Model,G444
  2. Using multi- gene mapping data with genotype error,Q78
  3. Counting interval mapping of quantitative trait,O212.7
  4. Moving Video Object Segmentation Based on Spatio-temporal Information,TP391.41
  5. On the Residual Analysis with Interval-Censored Data,O212
  6. QTL Mapping of Plant-type and Flowering Related Traits Using a Four-way Cross Population in Maize,S513
  7. Study on 3D Model Retrieval Technology Based on 3D Reconstruction,TP391.3
  8. EM Algorithm for Binary Markov Chains of Longitudinal Data with Missing Data,O212.1
  9. Application of EM Algorithm in Semiparametric Model with Missing Response,O212.1
  10. Construction of a Molecular Genetic Map and Analysis of Quantitative Trait Locus in Betula Platyphylla Suk,S792.153
  11. Estimations for Two-parametered Exponential Distribution under Censored and Missing Data,O211.67
  12. Mixture model based clustering algorithm,TP391.41
  13. Mapping of Major QTL for Grain Shape and Weight Traits in Rice(Oryza Sativa L.),S511
  14. GARCH beta distribution based on mixed -model modeling method and its application,F830
  15. Linear and nonlinear M-to-M communication channel modeling and estimation,TN911.5
  16. With missing data values ??from the regression model the entire statistical inference,O212.1
  17. The Mining Method of Clinical Thinking and Regularities of Prescription Use of Famous Doctors Through Clustering and Association Rule,TP311.13
  18. QTL Mapping and Analysis for Plant Type and Ear Traits in Maize,S513
  19. Research on Overlapping Community Detection Algorithms Based on Probabilistic Model,TP301.6
  20. Cabbage crop structure and content of glucosinolates Analysis and QTL Mapping,S634
  21. Censored data time series model parameter estimation and forecasting,O211.61

CLC: > Biological Sciences > Genetics > Genetics subdiscipline > Quantitative genetics ( bio- statistical genetics)
© 2012 www.DissertationTopic.Net  Mobile