Ping Wang, Mar-02-09 1 Method Paper. Ping Wang, Mar-02-09 2 Outline Methods –Multiple QTL model identification procedure –Adjacency Measurement –Clustering.

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Presentation transcript:

Ping Wang, Mar Method Paper

Ping Wang, Mar Outline Methods –Multiple QTL model identification procedure –Adjacency Measurement –Clustering Methods QTL Archive Studies Application to F2 data: clinical trait data + expression data in islet

Ping Wang, Mar Model Identification Procedure 1.Apply a single QTL mapping method. Pick several markers with relatively high LOD scores from each chromosome as candidate marker effects. 2.Identify baseline model, the best model with main effects only using stepwise regression and BIC (or pLOD) criterion. Allowed main effects are those cadidate marker effects identified in Step 1 and other covariates such as sex. 3.Identify the best model allowing first order interactions using stepwise regression, and BIC (or pLOD) criterion, starting from the baseline model. Allowed interactions are between main effects in the baseline model and all candidate marker effects.

Ping Wang, Mar QTL archive studies (25 traits in 12 studies) TraitsBIC 1 (# main effects, # interactions)BIC 2 (# main effects, # interactions) Transformed % suppression (7,2)< (7,3) GBV (1,0)> (4,0) Total cholesterol (6,0)> (7,0) Non-HDL (3,0)> (4,0) HDL (6,2)> (5,0) Total cholesterol (1,0)> (1,0) Non-HDL (1,0)< (1,0) HDL (4,0)> (5,0) Non-HDL (6,3)> (2,0) TG (4,1)> (1,0) % fat (5,1)>997.37(3,0) BMI (3,0)> (2,0) HDL (11,2)> (6,0) HDL (9,1)> (6,0) Cecum total score652.52(3,1)>634.75(3,0) Percentage of IgM+ B cells (3,1)> (2,0)

Ping Wang, Mar QTL Archive Studies (25 traits in 12 studies) TraitsBIC 1 (# main effects,interactions)BIC 2 (# main effects, # interactions) Blood pressure972.65(3,0)>964.16(5,2) Total cholesterol (4,0)> (3,0) Non-HDL (1,0)> (2,0) B.CecumPC199.20(1,0)>87.49(6,2) B.MidPC (1,0)>184.76(2,0) B.DistPC (1,0)>94.76(6,2) C.CecumPC (2,0)>203.30(3,0) C.DistPC (2,1)>173.82(5,3) BMD (4,0)> (7,4) 1: published method; 2: our method.

Ping Wang, Mar QTL Archive Studies GBV Published ResultOur Result ModelD5Mit255 D2Mit151(1.8), D3Mit167(2.5), D5Mit183(3.67), D7Mit246(2.24) BIC Malcolm A. Lyons et al. (2003) New quantitative trait loci that contribute to cholesterol gallstone formation detected in an intercross of CAST/Ei and 129S1/SvImJ inbred mice. Physiological Genomics. 14:

Ping Wang, Mar QTL Archive Studies

Ping Wang, Mar QTL Archive Studies HDL Published ResultOur Result Model D1Mit159, D1Mit406, D8Mit248, D9Mit129, D12Mit172, D2Mit285, D1Mit159:D1Mit406, D1Mit406:D2Mit285 D1Mit406(9.29), D6Mit86(1.61), D6Mit15(2.68), D9Mit129(2.74), D12Mit172(5.24) BIC Naoki Ishimori et al. (2004) Quantitative Trait Loci Analysis for Plasma HDL-Cholesterol Concentrations and Atherosclerosis Susceptibility Between Inbred Mouse Strains C57BL/6J and 129S1/SvImJ. Arterioscler. Thromb. Vasc. Biol. 24:

Ping Wang, Mar QTL Archive Studies Hdlq14: D1Mit159 Hdlq15: D1Mit406 Hdlq19: D2Mit285

Ping Wang, Mar QTL Archive Studies HDL: Published ResultOur Result Model D2Mit94, D4Mit110, D6Mit36, D6Mit14 Lineage, D2Mit94(5.97), D4Mit110(6.26), D6Mit14(4.03), D14Mit98(1.33) BIC Malcolm A. Lyons et al. (2003) Quantitative trait loci that determine lipoprotein cholesterol levels in DBA/2J and CAST/Ei inbred mice. Journal of Lipid Research. 44:

Ping Wang, Mar QTL Archive Studies

Ping Wang, Mar Insulin’s Weighted Model 1984 transcripts’ weighted models overlap with insulin’s weighted model

Ping Wang, Mar Insulin’s Model Plots

Ping Wang, Mar Weighted Model The rest of the vector are 0. Weighted model vector:

Ping Wang, Mar Adjacency Measurement Similarity between weighted models Adjacency measurement

Ping Wang, Mar TOM Distance Topological Overlap Matrix (TOM): defined as reflects the similarity with respect to relationships to all other nodes considered. When defined previously are used here, the relationship refers to co-regulation and co-expression. TOM distance can be used as dissimilarity measurement in clustering.

Ping Wang, Mar transcripts ordered by their adjacency with insulin decreasingly from top.

Ping Wang, Mar transcripts ordered by their adjacency with insulin decreasingly from top.

Ping Wang, Mar transcripts clustered using 1-adjacency as distance

Ping Wang, Mar Cluster Identification Using TOM Distance

Ping Wang, Mar transcripts clustered using TOM distance

Ping Wang, Mar Enrichment Test Enrichment test for 1984 transcripts Polyunsaturated fatty acid biosynthesis Glutamate metabolism Regulation of autophagy Butanoate metabolism Methane metabolism Bile acid biosynthesis Fatty acid metabolism (p-value<0.05) Enrichment test for modules e.g., transcripts in yellow module are enriched for Phosphatidylinositol signaling system Long-term depression N-Glycan biosynthesis Gap junction Inositol phosphate metabolism (p-value<0.01)

Ping Wang, Mar Application Paper

Ping Wang, Mar Paper 2: Result Adipose

Ping Wang, Mar Paper 2: Result

Ping Wang, Mar Paper 2: Result

Ping Wang, Mar Insulin is red module

Ping Wang, Mar Paper 2: Result Enrichment tests on transcripts mapping to hot regions. – Enrichment tests on unique transcripts in each module. –Red module are enriched for Phosphatidylinositol signaling system Inositol phosphate metabolism Long-term depression N-Glycan biosynthesis (p-value<0.01) Enrichment tests on transcripts in a specific tissue in each module.