fitVsDatCorrelation=0.840756303010856 cont.fitVsDatCorrelation=0.306834228274383 fstatistic=9581.05192176751,50,646 cont.fstatistic=3091.63516150955,50,646 residuals=-0.516798627788104,-0.0892666878442428,-0.00162280053501298,0.0743588444774313,1.04112857282556 cont.residuals=-0.632622170678196,-0.191226858292989,-0.0315011343362521,0.161998992678821,1.30472826326683 predictedValues: Include Exclude Both Lung 60.7426490724511 56.7332439445674 58.4738113713544 cerebhem 71.1277336709576 75.6541511676878 68.7935743787502 cortex 70.952832100869 61.2033008448435 70.0126081779089 heart 64.8641160663183 59.0165702888419 57.7501470472502 kidney 63.8825759273976 58.6467984368904 56.3751742734013 liver 67.8817981728713 61.2409662267723 59.0828260684153 stomach 64.4699096667972 69.6989322837674 60.2005357238237 testicle 68.7356380202523 60.5890570121993 60.1924670076473 diffExp=4.00940512788365,-4.52641749673018,9.74953125602548,5.84754577747643,5.23577749050725,6.64083194609906,-5.22902261697025,8.14658100805305 diffExpScore=1.59955758356069 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=0,0,0,0,0,0,0,0 diffExp1.4Score=0 diffExp1.3=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 59.2905442772885 57.8378793963778 64.1684640468306 cerebhem 60.1131969671733 62.9344354808484 59.207275145631 cortex 68.7570129186546 61.5369591628386 60.8822453589024 heart 58.0571724607251 58.5971525293971 54.2516493719691 kidney 63.3637716266827 69.6337392297903 61.4906920397266 liver 63.1950611874687 57.9841910268051 61.7827001492426 stomach 55.8340357240298 65.0750966192583 58.416725763595 testicle 59.2553152145501 71.6274373543044 64.4564852675065 cont.diffExp=1.45266488091065,-2.82123851367513,7.22005375581602,-0.539980068671937,-6.2699676031076,5.21087016066354,-9.24106089522845,-12.3721221397543 cont.diffExpScore=2.45784530820821 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,0,0,0,0,0 cont.diffExp1.4Score=0 cont.diffExp1.3=0,0,0,0,0,0,0,0 cont.diffExp1.3Score=0 cont.diffExp1.2=0,0,0,0,0,0,0,-1 cont.diffExp1.2Score=0.5 tran.correlation=0.500824520480502 cont.tran.correlation=-0.0712830479512835 tran.covariance=0.00277385991689948 cont.tran.covariance=-0.000359098766533442 tran.mean=64.7150170564678 cont.tran.mean=62.068312573512 weightedLogRatios: wLogRatio Lung 0.278093814443415 cerebhem -0.265000002929445 cortex 0.619061850481936 heart 0.389720078375276 kidney 0.351827984643140 liver 0.428926367285589 stomach -0.327947772844755 testicle 0.525705794376269 cont.weightedLogRatios: wLogRatio Lung 0.100961272203942 cerebhem -0.188921537062086 cortex 0.463189781301692 heart -0.0376429338091328 kidney -0.395928379434663 liver 0.353103794767966 stomach -0.627790143717803 testicle -0.791990925752567 varWeightedLogRatios=0.124880498990853 cont.varWeightedLogRatios=0.200921351894049 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.851577620966 0.0744313022821233 51.7467450235794 5.80228181780353e-232 *** df.mm.trans1 0.330125514266981 0.062542131141229 5.27845003428986 1.78138790938379e-07 *** df.mm.trans2 0.211205322509015 0.0575460186761152 3.67019869259308 0.000262374308022649 *** df.mm.exp2 0.283111854878594 0.0749009050623037 3.7798188772632 0.000171472045881396 *** df.mm.exp3 0.051113661731129 0.0749009050623037 0.682417144206895 0.495219837761834 df.mm.exp4 0.117559482090629 0.0749009050623036 1.56953353224292 0.1170133294847 df.mm.exp5 0.120123305155846 0.0749009050623037 1.6037630660928 0.109255057521860 df.mm.exp6 0.177216549017453 0.0749009050623036 2.36601345297552 0.0182749955454197 * df.mm.exp7 0.236274907008513 0.0749009050623036 3.15450002656144 0.00168235159308954 ** df.mm.exp8 0.160407462178298 0.0749009050623037 2.14159577971547 0.0325994184622724 * df.mm.trans1:exp2 -0.125280600406237 0.06510588805787 -1.92425914373336 0.0547610681221092 . df.mm.trans2:exp2 0.0047001053091421 0.0535481814859812 0.087773387979059 0.930083990490662 df.mm.trans1:exp3 0.104255585956763 0.06510588805787 1.60132346039262 0.109794158634104 df.mm.trans2:exp3 0.0247271098311968 0.0535481814859812 0.461773101252192 0.644399501779825 df.mm.trans1:exp4 -0.0519109944196389 0.06510588805787 -0.797331792379474 0.425551322288179 df.mm.trans2:exp4 -0.0781015771380508 0.0535481814859812 -1.45852902882421 0.145180791685693 df.mm.trans1:exp5 -0.0697227301246648 0.06510588805787 -1.07091281917069 0.284608569503231 df.mm.trans2:exp5 -0.086950671027376 0.0535481814859812 -1.62378382634972 0.104909770535499 df.mm.trans1:exp6 -0.0660946905123136 0.06510588805787 -1.01518760413136 0.310396472110111 df.mm.trans2:exp6 -0.100760552520263 0.0535481814859812 -1.88168019387628 0.0603288283536464 . df.mm.trans1:exp7 -0.176722380830041 0.06510588805787 -2.71438399969230 0.00681717741762439 ** df.mm.trans2:exp7 -0.0304502599749046 0.0535481814859812 -0.568651616729064 0.569790214605079 df.mm.trans1:exp8 -0.03678572095478 0.06510588805787 -0.565013734580851 0.572260576451342 df.mm.trans2:exp8 -0.0946535146402849 0.0535481814859812 -1.76763266302638 0.0775943551725573 . df.mm.trans1:probe2 0.198740405870491 0.0453547503468212 4.38190937775541 1.37269790180077e-05 *** df.mm.trans1:probe3 0.0953255371638554 0.0453547503468212 2.10177625132792 0.0359595041242125 * df.mm.trans1:probe4 0.00350671645644168 0.0453547503468212 0.0773175120494838 0.938394900398947 df.mm.trans1:probe5 0.336326922352200 0.0453547503468213 7.4154729059328 3.82088170270547e-13 *** df.mm.trans1:probe6 -0.0217756744552908 0.0453547503468213 -0.480118935475895 0.63130535146088 df.mm.trans1:probe7 -0.291074632524616 0.0453547503468213 -6.41773199717361 2.67738234940018e-10 *** df.mm.trans1:probe8 -0.405238479725039 0.0453547503468213 -8.93486297744424 4.22478188993536e-18 *** df.mm.trans1:probe9 -0.403607902086372 0.0453547503468212 -8.89891133784313 5.64012362403725e-18 *** df.mm.trans1:probe10 -0.444065475297678 0.0453547503468213 -9.79093638267157 3.36697211209818e-21 *** df.mm.trans1:probe11 -0.387602702627638 0.0453547503468212 -8.54602218430697 9.17211714919353e-17 *** df.mm.trans1:probe12 -0.406847170023189 0.0453547503468213 -8.97033203605106 3.17416477669987e-18 *** df.mm.trans2:probe2 0.0114624029487159 0.0453547503468213 0.252727726667319 0.800559015973197 df.mm.trans2:probe3 -0.270857281246493 0.0453547503468213 -5.97197160551621 3.87005771662955e-09 *** df.mm.trans2:probe4 -0.234671536413341 0.0453547503468213 -5.17413357187155 3.05985536457634e-07 *** df.mm.trans2:probe5 -0.0249526760553418 0.0453547503468213 -0.550166760141602 0.582395171282443 df.mm.trans2:probe6 0.103835033562012 0.0453547503468213 2.28939709221195 0.0223779856132558 * df.mm.trans3:probe2 -0.385076121759699 0.0453547503468213 -8.49031510073537 1.41326021324504e-16 *** df.mm.trans3:probe3 -0.594631762695606 0.0453547503468213 -13.1106831841988 5.46441040285884e-35 *** df.mm.trans3:probe4 -0.354455755546362 0.0453547503468212 -7.81518480061933 2.23337660290432e-14 *** df.mm.trans3:probe5 -0.366446373630744 0.0453547503468213 -8.07955882963926 3.19908091070608e-15 *** df.mm.trans3:probe6 -0.504740490527838 0.0453547503468213 -11.128723819846 1.93280272654406e-26 *** df.mm.trans3:probe7 -0.274856160784469 0.0453547503468213 -6.06014052955166 2.31132073252848e-09 *** df.mm.trans3:probe8 -0.548057859162656 0.0453547503468213 -12.0838027984221 1.88162751919308e-30 *** df.mm.trans3:probe9 0.155096116364741 0.0453547503468213 3.41962231472433 0.000666547687280258 *** df.mm.trans3:probe10 -0.326455629312914 0.0453547503468213 -7.19782661830469 1.7044487921654e-12 *** df.mm.trans3:probe11 -0.36800016158347 0.0453547503468213 -8.11381737898292 2.47766538450964e-15 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.97331454242799 0.130844402649941 30.3667139133047 1.61259122207087e-126 *** df.mm.trans1 0.0840683803305216 0.109944170513241 0.764646092085408 0.444761538076994 df.mm.trans2 0.104691294725759 0.101161395914029 1.03489373371964 0.301105787292365 df.mm.exp2 0.178696577716472 0.131669927575227 1.35715558599648 0.175205753607798 df.mm.exp3 0.262693223434231 0.131669927575227 1.99508899466923 0.0464527917489412 * df.mm.exp4 0.159899090024196 0.131669927575227 1.21439339239281 0.225041268080819 df.mm.exp5 0.294673791477281 0.131669927575227 2.23797336949946 0.025562797877762 * df.mm.exp6 0.104191289091550 0.131669927575227 0.791306648452606 0.429055503201665 df.mm.exp7 0.151741453660828 0.131669927575227 1.15243819492597 0.249567331478324 df.mm.exp8 0.208761463265553 0.131669927575227 1.58549083386015 0.113344217558026 df.mm.trans1:exp2 -0.164917014394115 0.114451054472171 -1.44093923078896 0.150086365660343 df.mm.trans2:exp2 -0.0942470137962395 0.094133511099491 -1.00120576291506 0.317102214770285 df.mm.trans1:exp3 -0.114564323594598 0.114451054472171 -1.0009896730349 0.317206594027256 df.mm.trans2:exp3 -0.200699181036649 0.094133511099491 -2.13206942663094 0.0333777358794364 * df.mm.trans1:exp4 -0.180920670505446 0.114451054472171 -1.58076892641857 0.114420350855795 df.mm.trans2:exp4 -0.146856900177273 0.094133511099491 -1.56009160246937 0.119227972223885 df.mm.trans1:exp5 -0.228231356400791 0.114451054472171 -1.99413939393880 0.0465567148372538 * df.mm.trans2:exp5 -0.109068496452825 0.094133511099491 -1.15865747679962 0.247023966832930 df.mm.trans1:exp6 -0.0404149743544815 0.114451054472171 -0.353120157266079 0.724113557004909 df.mm.trans2:exp6 -0.101664798108956 0.094133511099491 -1.08000643895568 0.280542360086425 df.mm.trans1:exp7 -0.21180764860537 0.114451054472171 -1.85063955576636 0.0646777602271595 . df.mm.trans2:exp7 -0.03384343195125 0.094133511099491 -0.359525864444602 0.719319224803108 df.mm.trans1:exp8 -0.209355816605711 0.114451054472171 -1.82921701832478 0.0678279064771004 . df.mm.trans2:exp8 0.00507282666291322 0.094133511099491 0.0538896998918024 0.957039703909985 df.mm.trans1:probe2 0.0980982335542036 0.0797301005694256 1.23037890148883 0.219003084912754 df.mm.trans1:probe3 0.0294940302476393 0.0797301005694256 0.369923404548539 0.711560803595749 df.mm.trans1:probe4 0.0432895733526734 0.0797301005694256 0.542951445482985 0.587350511722689 df.mm.trans1:probe5 -0.0667863333326665 0.0797301005694257 -0.837655199926804 0.402534177009382 df.mm.trans1:probe6 0.205540682411703 0.0797301005694256 2.57795589048238 0.0101590473943990 * df.mm.trans1:probe7 0.0117913805672288 0.0797301005694257 0.147891203987148 0.882474777917012 df.mm.trans1:probe8 0.0412198115884273 0.0797301005694256 0.516991842403796 0.605338806844752 df.mm.trans1:probe9 0.107090564301916 0.0797301005694256 1.34316354221410 0.179690699720878 df.mm.trans1:probe10 0.047611250353365 0.0797301005694256 0.597155277785046 0.550612950916073 df.mm.trans1:probe11 0.081328595976978 0.0797301005694256 1.02004883219933 0.308087152233528 df.mm.trans1:probe12 -0.0221387477983631 0.0797301005694257 -0.277671138506662 0.781353656706438 df.mm.trans2:probe2 -0.123374916831629 0.0797301005694257 -1.54740701379399 0.122254860824445 df.mm.trans2:probe3 -0.0666817819722107 0.0797301005694256 -0.836343883877921 0.403270723162731 df.mm.trans2:probe4 -0.00783123567478384 0.0797301005694257 -0.0982218211046244 0.921786623625197 df.mm.trans2:probe5 -0.084148546325919 0.0797301005694256 -1.05541753647540 0.291628956108441 df.mm.trans2:probe6 -0.0641162143916109 0.0797301005694257 -0.80416572829707 0.421597094193985 df.mm.trans3:probe2 -0.0197360670438325 0.0797301005694256 -0.247535960733515 0.80457211840011 df.mm.trans3:probe3 -0.0602482348236545 0.0797301005694257 -0.755652311904371 0.450133118533528 df.mm.trans3:probe4 -0.0710113148873354 0.0797301005694256 -0.890646247529836 0.373450559356959 df.mm.trans3:probe5 0.088860136851586 0.0797301005694257 1.11451178685282 0.265474157277227 df.mm.trans3:probe6 0.0065508796682082 0.0797301005694256 0.082163193341315 0.934542392408537 df.mm.trans3:probe7 0.097576176272544 0.0797301005694257 1.22383109485205 0.221462125700108 df.mm.trans3:probe8 -0.0196197106100581 0.0797301005694256 -0.246076581741849 0.805701116032472 df.mm.trans3:probe9 -0.0716790041932759 0.0797301005694257 -0.899020616822887 0.36897665289155 df.mm.trans3:probe10 0.0373707856753429 0.0797301005694256 0.468716148712267 0.639430667743898 df.mm.trans3:probe11 0.00575059441896482 0.0797301005694257 0.0721257640200447 0.94252414716305