1 / 30

Overview of My Research

Overview of My Research. Jian Huang. Semiparametric Models and Survival Analysis ( Jong-Sung Kim) Nonparametric MLE Statistical Genetics ( Kai Wang, Yanming Jiang, Susan Slager, Elizabeth Ludington, Xinqun Yang ) [Veronica Vieland, PPHG & CSGR]

battin
Télécharger la présentation

Overview of My Research

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Overview of My Research Jian Huang • Semiparametric Models and Survival Analysis • (Jong-Sung Kim) • Nonparametric MLE • Statistical Genetics (Kai Wang, Yanming Jiang, • Susan Slager, Elizabeth Ludington, Xinqun Yang) • [Veronica Vieland, PPHG & CSGR] • Microarray Analysis (Deli Wang, Ning Yan, Kwang-youn Kim)[Soares’ Lab, Casavant CBCB, Sheffield’s Lab, Stone’s Lab] • [Cun-Hui Zhang]

  2. Statistical Genetics Main Goal: find chromosomal regions harboring genes that predispose diseases or affect traits of interest

  3. Genetic Linkage Analysis of a Dichotomous Trait Incorporating a Quantitative trait If a quantitative trait is linked to the same chromosomal regions as the disease, then joint analysis of disease status and the quantitative trait should in general increase the power to detect linkage. Huang J and Jiang Y (2003): American Journal of Human Genetics, 72: 949-960.

  4. Example Asthma: Associated quantitative trait: total serum IgE level [Sandford et al. 1993, Wjst et al. 1999]. QTL analysis of total IgE level [Marsh et al. 1994, Meyers et al. 1994,Daniels et al. 1996, Laitinen et al. 1997, Palmer et al. 1998 ......] Autism: Possibly associated quantitative scorebased on: Spoken language, social empathy, compulsions, imitation, milestone, head circumference, etc. [Piven 2001]

  5. Example: Asthma German asthma genome scan data [Wjst et al. 1999, Genetic Analysis Workshop 12] 97 families with 415 individuals: 91 families with affected sib-pairs (ASPs) 6 families with affected sib-triosAll affected children: Total serum IgE level331 markers on 22 autosomal chromosomes(about 10cM apart) are typed for each individual.

  6. Likelihood Data: Pedigree structure Dichotomous trait: T Quantitative trait: Y Marker: M Likelihood: P(Y,M,T| ascertainment) If ascertainment is based on the trait T: P(Y, M|T)

  7. Likelihood Putative locus: x

  8. Identity by Descent (IBD) B A 1 2 3 4 A B 13 14 23 24 24 23 14 13 IBD=0 13 13 14 14 23 23 24 24 14 23 13 24 13 24 14 23 IBD=1 13 14 23 24 13 14 23 24 IBD=2

  9. Likelihood: Formulation • Families in a linkage study are usually collected based on the • phenotypes of the individuals • Likelihood should be based on the distribution conditional on • the phenotype on which the ascertainment is based • Pleiotropy or tight coincident linkage

  10. Likelihood Ratio Statistic

  11. Likelihood:Asymptotic Distribution • The asymptotic null distribution of the LR statistic is nonstandard: disappears under • The asymptotic null distribution of the LR statistic is unknown • Conservative null distribution:

  12. Simulation:Null Distribution n = 100 ASPs # of replications = 100,000

  13. Microarray Analysis • Normalization • Identifying differentially expressed genes • Finding groups of co-regulated genes • Finding molecular finger prints of various types of cancer • Understanding how genes regulate development • Inferring gene networks

  14. Microarray Schematic Duggan, et. al. Nature Genetics (1999) 21:10-14.

  15. Blocks 4.5 mm 4 1 2 3 4 1 2 3 4 5 6 7 8 6 7 5 8 9 10 11 12 9 10 11 12 13 14 15 16 13 14 15 16 18 19 20 17 21 22 23 24 Printing configuration: 4 x 4 pins (1-16 and 17-32) Block 1 and 17, 2 and 18, 3 and 19, … are printed by the same pin 25 26 27 28 29 30 31 32 Courtesy of Liliana Menzella of Soares’ Lab

  16. Data File Example (Part of Slide AAE-248) ---- Red (Cy5) channel

  17. Expression Data • Background subtracted intensities: Red Channel (Cy5): R Green Channel (Cy3): G • Log Intensity Ratio log2(R/G) = 0 Constant expression > 0 R up-regulated < 0 R down-regulated Total Intensity 0.5*log2(R*G) =0.5*[log2(R) + log2(G)]

  18. Expression Data Matrices: I---II Log intensity ratio Log intensity product

  19. Normalization

  20. Comparison of normalization curves (Data from Callow et al. 2000) Green: TW-SRM normalization Red: loess normalization

  21. A Two-way Semiparametric Regression Model (TW-SRM) Observed intensity = normalization curve (bias) + signal + random error The TW-SRM The SRM

  22. Results Loess and T-test TW-SRM

  23. Results Loess and T-test TW-SRM

  24. Computation

  25. Problem: An Infinitely Semiparametric Model and Parameters: Asymptotic analysis?

  26. Problem: An Infinitely Semiparametric Model

More Related