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1
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- Hui Wang
- Department of Statistics, Columbia University
- This is joint work with professor Shaw-Hwa Lo and Tian Zheng
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2
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- Introduction to the background and some methods
- Motivation of BGTA method and its advantages
- Implementing BGTA algorithm and some results
- Further discussion and future work
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3
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- A lot of new technologies have been
- developed in the molecular
biology.
- Current methods and problems in
- detecting genetic associations, especially
- the gene interactions in the complex traits.
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4
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- Case-Control studies --- easy sample collection and implementation.
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5
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- How to denote and index the genotype?
- A vector is used to denote the haplotype. Each entry of the vector is
- 0 or 1 to represent the allele status for each marker.
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6
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7
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8
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9
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10
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11
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12
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13
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- The marker being tested M(r) is in transmission disequilibrium (due to
true linkage/LD) with the disease while the other markers’
transmissions are independent of the disease status.
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14
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15
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16
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17
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18
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19
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- Simulate 15 markers, 4 markers
are linked to the disease loci
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20
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21
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- BGTA algorithm is based on genotypes with diallelic markers. It can
also be generalized to more complicated situations.
- In step 1 and 2, how to compute the variance of GTA and set a more
stringent and proper threshold to select suspect markers, and how to
create the entire gene network based on the returning marker sets are still
on-working.
- The model of interactions among markers need more considerations.
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Notes
