chr4.16305_chr4_122389234_122390726_+_1.R fitVsDatCorrelation=0.978836021022927 cont.fitVsDatCorrelation=0.323383583851045 fstatistic=8578.4197147767,36,324 cont.fstatistic=392.644241751303,36,324 residuals=-0.66021535393411,-0.0908221719431546,-0.00146166164908843,0.0923651741354604,1.37727433670924 cont.residuals=-2.00493046138814,-0.579233817807489,-0.0192099214755551,0.726466507334435,2.0198026354935 predictedValues: Include Exclude Both chr4.16305_chr4_122389234_122390726_+_1.R.tl.Lung 279.867788258812 1141.10146244154 78.6723930038186 chr4.16305_chr4_122389234_122390726_+_1.R.tl.cerebhem 171.592817567453 743.173442947643 96.3673921439482 chr4.16305_chr4_122389234_122390726_+_1.R.tl.cortex 213.971640883525 679.373938497567 86.4750695387885 chr4.16305_chr4_122389234_122390726_+_1.R.tl.heart 238.448268066176 733.556225228353 81.9770981976887 chr4.16305_chr4_122389234_122390726_+_1.R.tl.kidney 272.151992229547 1027.86189626168 77.4237551094418 chr4.16305_chr4_122389234_122390726_+_1.R.tl.liver 259.200982806116 767.578907668427 76.2835589954656 chr4.16305_chr4_122389234_122390726_+_1.R.tl.stomach 283.843959777983 772.0292877833 77.7133312127728 chr4.16305_chr4_122389234_122390726_+_1.R.tl.testicle 274.619216938026 946.650603959814 99.320476980109 diffExp=-861.233674182723,-571.58062538019,-465.402297614042,-495.107957162178,-755.70990403213,-508.377924862311,-488.185328005316,-672.031387021788 diffExpScore=0.99979247209536 diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.888888888888889 diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.4Score=0.888888888888889 diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.3Score=0.888888888888889 diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 355.805601814454 247.201820947709 201.314823365023 cerebhem 318.500352360041 392.550740285057 283.388773570704 cortex 300.986244812415 406.05386615929 316.868026748595 heart 262.855672443673 250.562567279855 397.82230454993 kidney 372.463967951846 297.912052508641 406.085455759532 liver 331.345554206636 352.435586125552 407.246753327578 stomach 224.334303061237 488.123515302076 129.649284040017 testicle 332.300935285743 228.462469539564 298.641558863587 cont.diffExp=108.603780866746,-74.0503879250161,-105.067621346875,12.2931051638181,74.5519154432045,-21.0900319189158,-263.789212240839,103.838465746179 cont.diffExpScore=4.60614678753566 cont.diffExp1.5=0,0,0,0,0,0,-1,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=1,0,0,0,0,0,-1,1 cont.diffExp1.4Score=1.5 cont.diffExp1.3=1,0,-1,0,0,0,-1,1 cont.diffExp1.3Score=4 cont.diffExp1.2=1,-1,-1,0,1,0,-1,1 cont.diffExp1.2Score=6 tran.correlation=0.602939987854865 cont.tran.correlation=-0.558664313437055 tran.covariance=0.0191752249315174 cont.tran.covariance=-0.0233123405489670 tran.mean=550.313901957247 cont.tran.mean=322.618453130237 weightedLogRatios: wLogRatio Lung -8.90626913534205 cerebhem -8.61604193120898 cortex -6.86670197696226 heart -6.78299808532973 kidney -8.33310966718559 liver -6.62284763324469 stomach -6.1523995032781 testicle -7.71504830222187 cont.weightedLogRatios: wLogRatio Lung 2.07301666368207 cerebhem -1.22669000643393 cortex -1.75364301252952 heart 0.265713063035141 kidney 1.29727506941043 liver -0.359994127437675 stomach -4.51054098729493 testicle 2.10515536014634 varWeightedLogRatios=1.06629126308712 cont.varWeightedLogRatios=4.99726467203195 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 8.0409334357659 0.112935299807929 71.1994695143259 6.40780906938901e-200 *** df.mm.trans1 -2.42709472482301 0.0956550191993542 -25.3734173610347 5.55204415194029e-79 *** df.mm.trans2 -0.985801099530127 0.0956550191993542 -10.3057958461712 9.96004451505709e-22 *** df.mm.exp2 -1.12088837542313 0.133211212180967 -8.41436960952214 1.28383583427381e-15 *** df.mm.exp3 -0.881615247344137 0.133211212180967 -6.61817599967836 1.50727031643069e-10 *** df.mm.exp4 -0.643157559357115 0.133211212180967 -4.82810379717428 2.12820021644395e-06 *** df.mm.exp5 -0.116471117825627 0.133211212180967 -0.87433419393708 0.382583903454064 df.mm.exp6 -0.44238666578703 0.133211212180967 -3.32094167258271 0.00099953459741931 *** df.mm.exp7 -0.364353949706512 0.133211212180967 -2.73515977927998 0.0065782715998771 ** df.mm.exp8 -0.438810486721741 0.133211212180967 -3.29409574117244 0.00109660736480747 ** df.mm.trans1:exp2 0.631695399068548 0.115364293817636 5.47565783280492 8.75376946115525e-08 *** df.mm.trans2:exp2 0.692068558851842 0.115364293817636 5.9989840526033 5.30643216101452e-09 *** df.mm.trans1:exp3 0.613141427483724 0.115364293817636 5.31482842042058 1.99105966178202e-07 *** df.mm.trans2:exp3 0.363037672702681 0.115364293817636 3.14688072616782 0.00180346833872804 ** df.mm.trans1:exp4 0.482992633910275 0.115364293817636 4.18667351853054 3.65172749933461e-05 *** df.mm.trans2:exp4 0.201312537300530 0.115364293817636 1.7450159892519 0.0819301762373991 . df.mm.trans1:exp5 0.0885145161504777 0.115364293817636 0.767260936823296 0.443485131307241 df.mm.trans2:exp5 0.011957942611494 0.115364293817636 0.103653758158453 0.917508254188253 df.mm.trans1:exp6 0.365673115083274 0.115364293817636 3.16972525018284 0.00167147884649381 ** df.mm.trans2:exp6 0.0458786812114044 0.115364293817636 0.397685277594884 0.6911240737676 df.mm.trans1:exp7 0.37846129260526 0.115364293817636 3.28057564503899 0.00114874579122732 ** df.mm.trans2:exp7 -0.0263728334918142 0.115364293817636 -0.228604818866255 0.819320297232252 df.mm.trans1:exp8 0.419878652308075 0.115364293817636 3.63958932537483 0.000317702952296548 *** df.mm.trans2:exp8 0.251991291370221 0.115364293817636 2.18430922628937 0.0296560045533403 * df.mm.trans1:probe2 0.304182024284248 0.0576821469088182 5.27341717646342 2.45265444377540e-07 *** df.mm.trans1:probe3 -0.369433863921064 0.0576821469088182 -6.40464829620596 5.29817628435741e-10 *** df.mm.trans1:probe4 0.231692826277771 0.0576821469088182 4.01671641390225 7.34054820942311e-05 *** df.mm.trans1:probe5 -0.0897894097659222 0.0576821469088182 -1.55662392226590 0.120536023443490 df.mm.trans1:probe6 0.107655786423439 0.0576821469088182 1.86636233553542 0.0628939252980388 . df.mm.trans2:probe2 -0.0252633610168552 0.0576821469088182 -0.437975393960121 0.661695960990536 df.mm.trans2:probe3 -0.268092165116210 0.0576821469088182 -4.64774942479169 4.89003049457068e-06 *** df.mm.trans2:probe4 0.432686636816808 0.0576821469088182 7.50122282204203 6.13152615994229e-13 *** df.mm.trans2:probe5 -0.253872060015179 0.0576821469088182 -4.40122418495432 1.46317826871316e-05 *** df.mm.trans2:probe6 -0.0239066463709191 0.0576821469088182 -0.414454864322402 0.678815275613847 df.mm.trans3:probe2 -0.330815512325456 0.0576821469088182 -5.73514562223901 2.23432268006099e-08 *** df.mm.trans3:probe3 -0.457420403523808 0.0576821469088182 -7.93001696429368 3.58286573273054e-14 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.64468876379077 0.52220410507371 10.8093534863997 1.8428371671914e-23 *** df.mm.trans1 0.182187902210559 0.442301421980201 0.411908922641254 0.680678552806836 df.mm.trans2 -0.322293654575078 0.442301421980201 -0.728674244663644 0.466727300050976 df.mm.exp2 0.00975002857536123 0.615958358113482 0.0158290385168618 0.987380524569686 df.mm.exp3 -0.124654619434773 0.615958358113483 -0.202375075835577 0.839750527645896 df.mm.exp4 -0.970411311245707 0.615958358113482 -1.57544953885815 0.116128607092885 df.mm.exp5 -0.46934464279713 0.615958358113482 -0.7619746312634 0.446629452462532 df.mm.exp6 -0.421109245999626 0.615958358113482 -0.683665121923781 0.494675284574024 df.mm.exp7 0.659153209789487 0.615958358113482 1.07012625302837 0.285359031877387 df.mm.exp8 -0.541550757901395 0.615958358113482 -0.879200275096554 0.379944281506364 df.mm.trans1:exp2 -0.120510966639550 0.533435585799628 -0.225914749311114 0.82141016890738 df.mm.trans2:exp2 0.452710683053746 0.533435585799628 0.848669820884045 0.396691612112709 df.mm.trans1:exp3 -0.0426653345449312 0.533435585799628 -0.0799821678206473 0.936300817234384 df.mm.trans2:exp3 0.620935353655383 0.533435585799629 1.16403061622631 0.245268044855832 df.mm.trans1:exp4 0.667631899426737 0.533435585799628 1.25156985622912 0.211629492795704 df.mm.trans2:exp4 0.983914878313934 0.533435585799628 1.84448676561207 0.066024922108612 . df.mm.trans1:exp5 0.515100426220692 0.533435585799628 0.965628165673553 0.334950465866911 df.mm.trans2:exp5 0.655937868084688 0.533435585799629 1.22964775044287 0.219721209353558 df.mm.trans1:exp6 0.349886527844588 0.533435585799628 0.655911486145234 0.512346576756924 df.mm.trans2:exp6 0.775772025308662 0.533435585799628 1.45429372535349 0.146832909848592 df.mm.trans1:exp7 -1.12040036549914 0.533435585799628 -2.10034799950522 0.0364708974029172 * df.mm.trans2:exp7 0.0212101773154421 0.533435585799628 0.0397614592653163 0.968307792005937 df.mm.trans1:exp8 0.473207228453662 0.533435585799628 0.887093476795922 0.375686575236586 df.mm.trans2:exp8 0.462717615804276 0.533435585799629 0.867429223175381 0.386348854084877 df.mm.trans1:probe2 0.17795552301006 0.266717792899814 0.667205292437705 0.505115908235548 df.mm.trans1:probe3 -0.0131794914036270 0.266717792899814 -0.0494136190178267 0.960620121847744 df.mm.trans1:probe4 -0.0577699897532967 0.266717792899814 -0.216595935071330 0.828659566192449 df.mm.trans1:probe5 -0.0227030455670974 0.266717792899814 -0.0851201013635608 0.932218482405822 df.mm.trans1:probe6 0.343267684182827 0.266717792899814 1.28700706634809 0.199010523239791 df.mm.trans2:probe2 0.373819184164772 0.266717792899814 1.40155323010336 0.162005891918503 df.mm.trans2:probe3 0.289229576635896 0.266717792899814 1.08440300698101 0.278992400309215 df.mm.trans2:probe4 0.341040710640415 0.266717792899814 1.27865751636794 0.201932810654974 df.mm.trans2:probe5 0.350375917729879 0.266717792899814 1.31365783257470 0.189890803032323 df.mm.trans2:probe6 0.335824454535354 0.266717792899814 1.25910030554841 0.208900468821816 df.mm.trans3:probe2 -0.244123755288381 0.266717792899814 -0.915288600112555 0.36072083313259 df.mm.trans3:probe3 -0.3550153746557 0.266717792899814 -1.33105246108966 0.184107609401083