Ray, Amrita
(2007)
Affected Relative Pair Linkage Statistics That Model Relationship Uncertainty.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Most of the complex diseases have major public health concern in United States. Linkage analysis helps to map disease genes, and we have proposed linkage statistics that give higher power in real data scenario where the true family structure might not be known. In linkage analysis with affected related pairs (ARP), stated familial relationships are usually assumed to be correct, thus misspecified relationships can lead to either reduced power or false-positive evidence for linkage. In practice, studies either discard individuals with erroneous relationships or use the best possible alternative pedigree structure. We have developed several linkage statistics that model the relationship uncertainty by properly weighting over possible true relationships. We consider ARP data for a genome-wide linkage scan. Simulation study is performed to assess the proposed statistics, and compare them to maximum likelihood statistic (MLS) and Sall LOD score using true and discarded structures. We have simulated small and large pedigree datasets with different underlying true and apparent relationships, and typed for 367 microsatellite markers. The results show that two of our relationship uncertainty linkage statistics (RULS) have power as high as MLS and Sall using the true structure. Also, these two RULS have greater power to detect linkage than MLS and Sall using the discarded structure. Thus, our RULS provide a statistically sound and powerful approach for dealing with the commonly encountered problem of relationship errors.To apply RULS on a real data, we have used Otitis Media with effusion (OME) data from Caucasian families. OME is an infection causing fluid in the middle ear, and is the most common cause of hearing loss among young children. We have recruited subjects (with history of tympanostomy tube insertion) and their families (parents and affected/unaffected siblings). Genotyping was done using Affymetrix 10K SNP chip technology, and out of 1584 enrolled individuals (322 families), 1191 (305 families) are genotyped at this date. We performed nonparametric multipoint linkage analysis using conservative dataset. The preliminary results show suggestive linkage peaks on chromosomes 2, 7 and 10, the highest being on chromosome 7 (rs2014450, 153cM) with Sall LOD score of 2.08 (p-value 0.001).
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
21 June 2007 |
| Date Type: |
Completion |
| Defense Date: |
11 April 2007 |
| Approval Date: |
21 June 2007 |
| Submission Date: |
12 April 2007 |
| Access Restriction: |
5 year -- Restrict access to University of Pittsburgh for a period of 5 years. |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Human Genetics |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
likelihood ratio statistic; nonparametric linkage analysis; relationship error |
| Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-04122007-200347/, etd-04122007-200347 |
| Date Deposited: |
10 Nov 2011 19:36 |
| Last Modified: |
30 Jun 2022 16:21 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/7060 |
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