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A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Reverter et.

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Presentation on theme: "A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Reverter et."— Presentation transcript:

1 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Reverter et al. 2005 Bioinformatics 21:1112 Validation of alternative methods of data normalization in gene co-expression studies

2 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Motivation Statistics are like a bikini, what they reveal is suggestive, but what they conceal is vital. Aaron Levenstein

3 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Motivation Correlations Are Dangerous! # # # # ## # # # # # # # # # # # # # # ## # # # # # # # # # Exp 1 Exp 2 Gene 1 Gene 2 Gene 1 Gene 2 # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

4 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Introduction Validation of alternative methods of data normalization in gene co-expression studies. Bioinformatics 2005, 21:1112 A. Reverter, W. Barris, S.M. McWilliam, K.A. Byrne, Y.H. Wang, S.H. Tan, N. Hudson, and B.P. Dalrymple Experiment a Hybs.Cond.Signals b NMeanSTD 1. Two breeds by two diets74193,1757.612.99 2. Three diets143361,3208.522.84 3. Two diets at three ages246801,80711.601.89 4. Two breeds at three ages186459,9788.343.28 5. Two fat treatments at two ages154418,8177.043.31 Expression of each clone (gene) across 23 conditions

5 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Co-Expression Introduction Armidale Animal Breeding Summer Course, UNE, Feb. 2006 1 2 3 4 5

6 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization ############################################ Clone i Experiment 1 (  E1,  E1 ) Experiment 2 (  E2,  E2 ) Cond 1 2 3 4 5 (  Ci,  Ci ) 1. RMNA 2. RMCE3. RMEC Expression of each clone (gene) across 23 conditions

7 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization Expression of each clone (gene) across 23 conditions

8 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization Expression of each clone (gene) across 23 conditions

9 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization Expression of each clone (gene) across 23 conditions

10 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization Expression of each clone (gene) across 23 conditions

11 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization Expression of each clone (gene) across 23 conditions Expected to be the equal!

12 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization Log2 Intensities Comparison Group Array|Block|Dye (FIXED) Main Gene Effect (RANDOM) Gene x Variety (RANDOM) Residual (RANDOM) DE Genes Gene x Array|Block (RANDOM) Gene x Dye (RANDOM) Mixed-Model Equations

13 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization 4. MM1NA 5. MM1CE6. MM1EC 7. MM5NA 8. MM5CE9. MM5EC

14 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Methods Nine Methods of Data Normalization 4. MM1NA 5. MM1CE6. MM1EC 7. MM5NA 8. MM5CE9. MM5EC Vector of BLUP Clone x Condition Interaction

15 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Observed (RED) vs Expected (BLUE) Results

16 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Results Average across all pair-wise gene correlations (bold, italics and on the diagonal); Correlation of correlations (above diagonal); and maximum absolute discrepancy between methods (below diagonal) 123456789 1. RMNA0.530.200.980.110.120.110.060.070.06 2. RMCE1.840.150.210.14 0.090.100.09 3. RMEC0.761.790.510.12 0.07 4. MM1NA1.781.721.740.020.940.990.570.600.56 5. MM1CE1.75 1.740.510.010.940.610.690.61 6. MM1EC1.791.711.740.500.550.020.570.610.58 7. MM5NA1.801.751.791.251.141.210.010.910.99 8. MM5CE1.781.741.771.191.091.190.590.010.90 9. MM5EC1.801.751.791.251.131.200.550.660.01

17 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Results Redundant genes (ie. those with many probes on the array) allow for Validation

18 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Results Redundant genes allow for Validation

19 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Results 624 Gene Co-Expression (Alphabetical order) Robisomal Proteins

20 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Brian Sigrid Siok Kwee Keren Applications

21 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Applications False Discovery Rate as a Function of Correlation

22 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Applications DLK1 COL3A1 LUM GNAI2 DCAL1 CIDEC KARS UBA52 TNFRSF21 0.584 0.602 0.611 0.545 -0.639 -0.658 -0.697 Callipyge Mutation

23 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Applications DLK1 COL3A1 LUM GNAI2 DCAL1 CIDEC KARS UBA52 TNFRSF21 DES FN1 CTSF SPARC CAV1 ACTA1 TM4SF2 0.853 0.880 0.584 0.602 0.611 0. 736 0. 611 0.545 -0.639 -0.658 -0.697 -0.822 0.754 0.747 0.767 0.743 -0.741 -0.738 0. 799 Callipyge Mutation

24 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Applications DLK1 COL3A1 LUM GNAI2 DCAL1 CIDEC KARS UBA52 TNFRSF21 DES FN1 CTSF SPARC CAV1 ACTA1 TM4SF2 MYBPC2 MYL1 LDHA PGK1 CASQ1 0.883 0.889 0.892 0.893 0.853 0.880 0.584 0.602 0.611 0. 736 0. 611 0.545 -0.639 -0.658 -0.697 -0.822 0.754 0.747 0.767 0.743 -0.741 -0.738 0. 799 Callipyge Mutation

25 A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb. 2006 Co-Expression Applications DLK1 COL3A1 LUM GNAI2 DCAL1 CIDEC KARS UBA52 TNFRSF21 DES FN1 CTSF SPARC CAV1 ACTA1 TM4SF2 MYBPC2 MYL1 LDHA PGK1 CASQ1 0.883 0.889 0.892 0.893 0.853 0.880 0.584 0.602 0.611 0. 736 0. 611 0.545 -0.639 -0.658 -0.697 -0.822 0.754 0.747 0.767 0.743 -0.741 -0.738 0. 799 0.911 ITM2B ENO3 PYGM -0.899 0.916 0.972 GPI 0.897 CKM 0.910 Callipyge Mutation

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