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MMI Genomics/UCD & MSU Visits – May 2003 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries Toni Reverter (

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1 MMI Genomics/UCD & MSU Visits – May 2003 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries Toni Reverter ( Tony.Reverter-Gomez@csiro.au ) CLI Bioinformatics Queensland Bioscience Precinct Brisbane, 4067 Australia

2 Introduction: Analysis possibilities Challenges Process for microarray Technical Concerns: Design Image (data) quality Data analysis Contents MMI Genomics/UCD & MSU Visits – May 2003 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter )

3 Determine genes which are differentially expressed (DE). Connect DE genes to sequence databases to search for common upstream regions. Overlay DE genes on pathway diagrams. Relate expression levels to other information on cells, e.g. tumor types. Identify temporal and spatial trends in gene expression. Seek roles of genes based on patterns of co-regulation. …many more!!! Analysis Possibilities (adapted from Hongzhe Li, 2002) Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) MMI Genomics/UCD & MSU Visits – May 2003

4 Challenges Time Dependent Chronology Logical 1800s – DATA 30-60s – METHODS 50-70s – SOFTWARE 1980s – COMPUTER cDNA  Human Dependent Skill Integration Quantitative Computer Sci. Statisticians Mathematicians ……. Non-Q Biochemists Physiologists Pathologists ……. BANANAEGG “banana omelette” Historical Excitement Balance Interdisciplinary Data Dependent Paradigm Distribution SourceSize Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) MMI Genomics/UCD & MSU Visits – May 2003

5 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Array Process cDNA “A” Cy5cDNA “B” Cy3 Tissue Samples Treat ATreat B mRNA Extraction & Amplification Hybridization Laser 1 Laser 2 Optical Scanner + Image Capture Analysis MMI Genomics/UCD & MSU Visits – May 2003

6 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) What you see is What you get MMI Genomics/UCD & MSU Visits – May 2003

7 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Egg Level (Biochemist): 1.Preparation (Printing) of the Chip 2.RNA Extraction, Amplification and Hybridisation 3.Optical Scanner (Reading) Banana Level (Quantitative): 1.Design 2.Image (data) Quality 3.Data Analysis Replication: 1.Animal 2.Sample 3.Array 4.Spot Technical Concerns MMI Genomics/UCD & MSU Visits – May 2003

8 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) ############################################################## # GP3xCLI # # GenePix Processing Program by CSIRO Livestock Industries # # # # Enquiries: Tony.Reverter-Gomez@csiro.au # # Copyright (c) 2003 CSIRO-LI # ############################################################## GPR Input: F12.gpr Processed on: Tue Apr 8 13:40:01 EST 2003 =-=-=-=-=-=-= IMAGE QUALITY =-=-=-=-=-=-=-= Total No. of Spots ------------------------> 19200 Spots with Flag = -50 --------------------> 4720 Spots with Flag = -100 --------------------> 12 Red dye with Background >= Foreground ---> 892 Green dye with Background >= Foreground ---> 915 Median to Mean Correlation Analysis: DATA LEFT RED GREEN Corr Raw Log2 Raw Log2 ______________________________________ > 0.00 19200 19200 19200 19200 > 0.20 19199 19200 19199 19200 > 0.40 19183 19200 19192 19200 > 0.60 19008 19200 19102 19200 > 0.80 17061 19199 18541 19198 > 0.85 14466 19193 17872 19196 > 0.90 10491 19137 15786 19181 =-=-=-=-=-=-= VALID SPOTS* =-=-=-=-=-=-=-= Total No. of Valid Spots -----------------> 14433 Percentage of Valid Spots -----------------> 75.2 Total No. of Genes ------------------------> 7220 Mean No. Repetitions -----> 2 for 6600 Genes Min. No. Repetitions -----> 1 for 580 Genes Max. No. Repetitions -----> 24 for 8 Genes Log(R/G) vs 0.5*Log(R*G) ________ ____________ N 14433 14433 Mean -0.017 10.327 Std 0.617 2.079 Min -8.711 3.246 Max 4.030 15.994 Correlation 0.362 Log(R/G) across Intensity Values Intensity Spots % 0 __________________________________ ( 0, 4) 4 100.0 0.0 ( 4, 8) 1499 74.1 25.9 ( 8, 12) 9847 40.4 59.6 (12, 16) 3083 17.3 82.7 __________________________________ *NB: Valid Spot defined as spots with Background < Foreground for both Red and Green channels and with a Quality Flag of 0. Technical Concerns: Image (Data) QualityGP3xCLI MMI Genomics/UCD & MSU Visits – May 2003

9 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Clever ProgrammingTailored to your needs N=1 for filename in R16T0S1.gpr R16T0S2.gpr R16T24S1.gpr R16T24S2.gpr S32T0S1.gpr S32T0S2.gpr S32T24S1.gpr S32T24S2.gpr do # Get valid readings, compute log ratios awk 'NR>30 && $NF>=0 && $4!="no_spot" && substr($4,1,5)!="score" && \ substr($4,1,5)!="custo" && substr($4,1,6)!="spotre" && \ $9>$12 && $18>$21 {print $4, $9-$12, $18-$21, log($9-$12)/log(2.0), \ log($18-$21)/log(2.0)}' $filename | sort > junk1 awk '$2!=$3 {print $0, $4-$5, 0.5*($4+$5)}' junk1 > junk2 # get the median of log ratios REC=`wc -l junk2 | awk '{print int($1/2)}'` MED=`sort -n +5 junk2 | awk -v rec=$REC 'NR==rec {print $6}'` echo "Median of file" $filename " = " $MED # Global normalization: substract the median to each log ratio awk -v median=$MED -v slide=$N '{print "Slide_"slide, int(slide/2+.5), \ $1, $6-median}' junk2 | sort +2 > dat.$N N=`expr $N + 1` done cat dat.* > total.dat MMI Genomics/UCD & MSU Visits – May 2003

10 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) MMI Genomics/UCD & MSU Visits – May 2003

11 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) MMI Genomics/UCD & MSU Visits – May 2003

12 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) MMI Genomics/UCD & MSU Visits – May 2003

13 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Technical Concerns: Experimental Design O B A AB O B A O B A ReferenceLoopAll-Pairs Variance of Estimated Effects (Relative to the All-Pairs) Reference 1 3 2 Loop 4/3 1 8/3 1 All-Pairs 1 2 1 Main effect of A Main effect of B Interaction AB Contrast A-B MMI Genomics/UCD & MSU Visits – May 2003

14 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Technical Concerns: Experimental Design Glonek & SolomonFactorial and Time Course Designs for cDNA Microarray Experiments Read pp 1-2 Definition A design with a total of n slides and design matrix X is said to be admissible if there exists no other design with n slides and design matrix X* such that ci*  ci For all i with strict inequality for at least one i. Where ci* and ci are respectively the diagonal elements of (X*’X*)-1 and (X’X)-1. Read pp 24 MMI Genomics/UCD & MSU Visits – May 2003

15 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) What is the No. of Possible Configurations? No. of Arrays: (S-1) to S·(S-1) S = 326 S = 4312 S = 1211132 MMI Genomics/UCD & MSU Visits – May 2003

16 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) S A-1 MMI Genomics/UCD & MSU Visits – May 2003

17 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Pie-Bald black Non-Pie-Bald black Normal White Recessive S A-1 = 5 3 = 125 MMI Genomics/UCD & MSU Visits – May 2003

18 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) x5 MMI Genomics/UCD & MSU Visits – May 2003

19 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) 0 hr24 hr MMI Genomics/UCD & MSU Visits – May 2003 S A-1 = 12 10 = 62 Billion!

20 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) 0 hr24 hr R R RR R R R R R R R R G G G G G G G G G G G G MMI Genomics/UCD & MSU Visits – May 2003

21 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) F HS M TM F HS M HS F TM M HS F HS M HS R R R R R R R R R R R R R R G G G G G G G G G G G G G G MMI Genomics/UCD & MSU Visits – May 2003 24: 23 To 552 14: 13 To 182 pooling

22 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) MMI Genomics/UCD & MSU Visits – May 2003

23 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) RESSUS0324MFHSTM RES8-810-1.7661.766-3.8663.866 SUS8011.766-1.7663.866-3.866 08-4 -1.3351.3350.666-0.666 310-6-1.0331.033-0.4680.468 24102.368-2.368-0.1980.198 M6.247-6.2470.493-0.493 F6.247-0.4930.493 HS3.798-3.798 TM3.798 Sum(ABS)29.3 22.023.027.121.7 17.6 Sum(ABS) 26.8 26.8 39.1 23.1 17.3 7.1 7.1 14.3 14.3 Reference Design MMI Genomics/UCD & MSU Visits – May 2003

24 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Technical Concerns: Statistical Analysis TechniqueChoiceAim RealIdeal 1. TransformationBase-2 Log Numerically tractableGaussian 2. NormalisationLocation: M - c Systematic effectsGaussian 2.i. Global: - Mean - Median - Regr. Coeff (LOWESS) 2.ii. Local: - LOWESS within print-tip-group 3. StandarisationScale Parameter Stabilise varianceGaussian Data Beautifying Techniques MMI Genomics/UCD & MSU Visits – May 2003

25 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Technical Concerns: Statistical Analysis Assumption: The proportion of genes that are DE is minimal Q:Which genes to use? A: Only the ones (housekeeping) that we know are not DE NB:“Boutique” arrays become a nuisance Adapted from T Speed 2002 MMI Genomics/UCD & MSU Visits – May 2003

26 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Except Log 2, everything else applies only to Ratios: M = log 2 (R/G) Except Log 2, everything else applies only within slide Everything is beautified to identify DE genes straight from “M vs A” plot (A = Average) from a single slide or from a function of M’s (t-stat) across slides Technical Concerns: Statistical Analysis Data Beautifying Techniques MMI Genomics/UCD & MSU Visits – May 2003

27 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Include the “possible systematic sources of variation” into a model-based (eg. ANOVA) analysis and the data will be implicitly normalised. Then check the residuals. Whenever possible, avoid ratios. Technical Concerns: Statistical Analysis Log 2 (Intensity) =Array+ Dye+ A*D+ Treatment+ Sample+ Gene+ Gene*Treatment+ Gene*Sample+ Residuals Normalisation Model Gene Model MMI Genomics/UCD & MSU Visits – May 2003

28 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Rockhampton Model Log 2 (Intensity) = Design+ Array+ Dye+ Array*Dye+ (Diet+) Gene+ Gene*Diet+ Residuals N Levels 2 14 2 28 3 7,347 22,041 300,936 Rockhampton MEDIUM (4  Animals) LOW (3  Ani, 1 Rep) (pooled 3 Anim) HIGH (pooled 2 Anim) MEDIUM (Pooled & Ampl) LOW (Pooled & Ampl) Reference All Pairs MMI Genomics/UCD & MSU Visits – May 2003

29 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Japanese Model Log 2 (Intensity) = Array+ Dye+ Array*Dye+ Breed+ Time+ Breed*Time+ Gene+ Gene*Br*Ti+ Residuals N Levels 12 2 24 2 3 6 5900 35,400 259,080 Japanese JANUARY 01 JAPANESE JUNE 01 JAPANESE OCTOBER 01 JAPANESE HOLSTEIN MMI Genomics/UCD & MSU Visits – May 2003

30 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Rockhampton Japanese Residual Gene Gene*Treatment % Total Variance Explained by Gene Gene*Treatment 0.720 3.664 0.137 81.1 3.0 0.889 2.883 0.133 73.8 3.4 REML MMI Genomics/UCD & MSU Visits – May 2003

31 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Clever ProgrammingTailored to your needs Interaction Solutions Your Needs: “Important values are…” 1.Away from (0,0) 2.In quadrants 1 and 4. Generate a new variable: +1.0*[(R 24 -R 0 )+(S 0 -S 24 )] if R 0 S 24 +0.5*[(R 24 -R 0 )+(S 24 -S 0 )] if R 0 <R 24 & S 0 <S 24 -0.5*[(R 0 -R 24 )+(S 0 -S 24 )] if R 0 >R 24 & S 0 >S 24 -1.0*[(R 0 -R 24 )+(S 24 -S 0 )] if R 0 >R 24 & S 0 <S 24 …then apply model-based clustering. MMI Genomics/UCD & MSU Visits – May 2003

32 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Clever Programming BAYESMIX MMI Genomics/UCD & MSU Visits – May 2003

33 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Clever Programming BAYESMIX MMI Genomics/UCD & MSU Visits – May 2003

34 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Clever Programming BAYESMIX MMI Genomics/UCD & MSU Visits – May 2003

35 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Human Dependent Challenges Interdisciplinary Skills Minimal knowledge of the application discipline is needed …..failing that, the Statisticians will win,..…but with the wrong weapons. 1.Amount of Expression = Amount of Response 2.Same cut-off point to judge all genes 3.Over-emphasis in normalization (hence, despise “Boutique Arrays”) 4.Over-emphasis in variance stabilization 5.Over-emphasis in controlling false-positives MMI Genomics/UCD & MSU Visits – May 2003

36 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) The Statistical Analysis of cDNA Microarray Data: General: 1.Still in its infancy (…possibly even embryonic stage) 2.Many decisions have a heuristic rather than a theoretical foundation 3.No hope for a “One size fits all” software (even method) 4.Safer to aim towards “Tailor to one’s needs” 5.Integration of interdisciplinary skills is a must Conclusion Livestock Species: 1.Tailing humans (…at the moment) 2.Strong background knowledge of genetics accumulated 3.Journals will soon be inundated 4.We have the opportunity to participate MMI Genomics/UCD & MSU Visits – May 2003

37 Design and Analysis of cDNA Microarray Experiments at CSIRO Livestock Industries ( Toni Reverter ) Thank You! MMI Genomics/UCD & MSU Visits – May 2003

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