chr10.2254_chr10_81158040_81162643_-_2.R fitVsDatCorrelation=0.919638454353032 cont.fitVsDatCorrelation=0.214047625577489 fstatistic=9896.26173515064,69,1083 cont.fstatistic=1586.79385479729,69,1083 residuals=-1.15241399940346,-0.0930345492643996,-0.000105222326560419,0.0864549617523516,1.00915397592984 cont.residuals=-0.766991377540816,-0.280711626231095,-0.070842168315536,0.163240786904779,1.64429014930556 predictedValues: Include Exclude Both chr10.2254_chr10_81158040_81162643_-_2.R.tl.Lung 112.342337468556 43.8726059630785 90.6602514982365 chr10.2254_chr10_81158040_81162643_-_2.R.tl.cerebhem 74.1299527085561 43.1871232916154 68.1953363878037 chr10.2254_chr10_81158040_81162643_-_2.R.tl.cortex 81.7976639596978 42.763826606644 72.1982749693217 chr10.2254_chr10_81158040_81162643_-_2.R.tl.heart 89.5265707151322 43.865223979446 77.267537719923 chr10.2254_chr10_81158040_81162643_-_2.R.tl.kidney 83.9358425755727 42.9157012237859 75.8821730661137 chr10.2254_chr10_81158040_81162643_-_2.R.tl.liver 80.2361354261288 47.6201936273931 74.6077981166898 chr10.2254_chr10_81158040_81162643_-_2.R.tl.stomach 91.194673769727 43.8553781707321 78.5599908928935 chr10.2254_chr10_81158040_81162643_-_2.R.tl.testicle 87.7644628524053 46.2651615941235 78.2718741968924 diffExp=68.469731505477,30.9428294169407,39.0338373530538,45.6613467356862,41.0201413517868,32.6159417987356,47.3392955989948,41.4993012582818 diffExpScore=0.997122984569932 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 69.1977761903302 62.6659878142928 66.8314146823059 cerebhem 67.3973576561598 66.8220778520806 72.7042071839508 cortex 71.0637162556693 65.0214751483409 68.163149669453 heart 77.1268387547381 66.089983668983 73.7842648297453 kidney 67.4960007235027 67.3545690241393 70.7477377054982 liver 69.4389578401054 69.9784612203314 74.9567038856728 stomach 67.0486843699268 63.6231426212021 68.7185672899618 testicle 70.7989156102265 59.0680463904731 69.5535801525078 cont.diffExp=6.53178837603747,0.575279804079273,6.04224110732845,11.0368550857551,0.141431699363437,-0.539503380225952,3.42554174872468,11.7308692197534 cont.diffExpScore=1.00197791318482 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=0,0,0,0,0,0,0,0 cont.diffExp1.2Score=0 tran.correlation=-0.0590183932291042 cont.tran.correlation=-0.057810906396987 tran.covariance=-0.000188082410657765 cont.tran.covariance=-0.000151705149915123 tran.mean=65.9545533707871 cont.tran.mean=67.5119994462814 weightedLogRatios: wLogRatio Lung 3.99744348182501 cerebhem 2.18038681484860 cortex 2.64608989125461 heart 2.95198331303385 kidney 2.74674933830376 liver 2.15162143649934 stomach 3.03597625060297 testicle 2.66000576865263 cont.weightedLogRatios: wLogRatio Lung 0.415179611173204 cerebhem 0.0360577522367462 cortex 0.374910405054884 heart 0.659161005697735 kidney 0.00883306417850598 liver -0.0328486244302976 stomach 0.219164280147219 testicle 0.755277609028586 varWeightedLogRatios=0.337568803518949 cont.varWeightedLogRatios=0.089536990181753 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.60822611039614 0.0788627509256561 58.4334943469105 0 *** df.mm.trans1 0.277965095326035 0.0672583316491664 4.1327979524672 3.8601926905007e-05 *** df.mm.trans2 -0.82357651423628 0.0585852379430401 -14.0577480463083 2.35141648932205e-41 *** df.mm.exp2 -0.146736021261958 0.0734499599046645 -1.99776856859304 0.045991518860478 * df.mm.exp3 -0.115196785225927 0.0734499599046644 -1.56837097495285 0.117086693768470 df.mm.exp4 -0.067338502858045 0.0734499599046644 -0.916794276612922 0.359454557104982 df.mm.exp5 -0.135613189571658 0.0734499599046644 -1.84633442615461 0.0651163831415375 . df.mm.exp6 -0.0597360369302082 0.0734499599046645 -0.813288897744036 0.416231198972315 df.mm.exp7 -0.0656905835618729 0.0734499599046644 -0.894358331129615 0.371328910838583 df.mm.exp8 -0.0468643264642758 0.0734499599046644 -0.63804427565521 0.523579741489156 df.mm.trans1:exp2 -0.268995102000855 0.0667784801111191 -4.02817047577676 6.01355124547664e-05 *** df.mm.trans2:exp2 0.130988284773171 0.0443239836713257 2.95524621036964 0.00319181818385803 ** df.mm.trans1:exp3 -0.202105323501462 0.066778480111119 -3.0265037953119 0.0025324494994761 ** df.mm.trans2:exp3 0.089599242358634 0.0443239836713257 2.02146185737809 0.0434775609502277 * df.mm.trans1:exp4 -0.159676830400859 0.066778480111119 -2.39114202861697 0.0169659803984670 * df.mm.trans2:exp4 0.0671702291805496 0.0443239836713257 1.51543754908482 0.129953433052589 df.mm.trans1:exp5 -0.155884876253338 0.0667784801111191 -2.33435795474749 0.0197590742669219 * df.mm.trans2:exp5 0.113560829084685 0.0443239836713257 2.56206278584454 0.0105396314416783 * df.mm.trans1:exp6 -0.276840777239705 0.0667784801111191 -4.14565855316029 3.6529723904576e-05 *** df.mm.trans2:exp6 0.141702828721363 0.0443239836713257 3.19697863288027 0.00142895038126073 ** df.mm.trans1:exp7 -0.142863716689416 0.0667784801111191 -2.13936759943759 0.0326289645661981 * df.mm.trans2:exp7 0.0652978287815609 0.0443239836713257 1.47319404469061 0.140989291259569 df.mm.trans1:exp8 -0.200029799918451 0.0667784801111191 -2.99542307021068 0.0028029814732563 ** df.mm.trans2:exp8 0.0999634396001361 0.0443239836713257 2.25529005563651 0.0243141194369226 * df.mm.trans1:probe2 -0.644400513708203 0.0507218967619079 -12.7045823371524 1.42776562660091e-34 *** df.mm.trans1:probe3 -0.369675938399939 0.050721896761908 -7.28829089604482 6.04050649318911e-13 *** df.mm.trans1:probe4 -0.298296478376955 0.0507218967619079 -5.88101978475252 5.42707293012893e-09 *** df.mm.trans1:probe5 -0.665312620792847 0.0507218967619079 -13.1168718692810 1.37869615770306e-36 *** df.mm.trans1:probe6 -0.426835010105833 0.0507218967619079 -8.4152020597618 1.22757875046462e-16 *** df.mm.trans1:probe7 -0.181703277656417 0.050721896761908 -3.58234390384383 0.000355654196208598 *** df.mm.trans1:probe8 -0.647988748991004 0.050721896761908 -12.7753256553616 6.48916035742527e-35 *** df.mm.trans1:probe9 0.742258941793355 0.050721896761908 14.6338955989278 2.19084864281646e-44 *** df.mm.trans1:probe10 -0.589610031415822 0.0507218967619079 -11.6243687451889 1.61375324486383e-29 *** df.mm.trans1:probe11 -0.217743934112983 0.050721896761908 -4.2928980975433 1.92155107481224e-05 *** df.mm.trans1:probe12 -0.491678572766211 0.050721896761908 -9.69361566019867 2.29898428541752e-21 *** df.mm.trans1:probe13 -0.0477462952722086 0.050721896761908 -0.941334972079869 0.346743144683045 df.mm.trans1:probe14 0.0389406276452543 0.050721896761908 0.767728143686035 0.442816061772582 df.mm.trans1:probe15 -0.446616399394953 0.050721896761908 -8.80519909362619 5.08471497503174e-18 *** df.mm.trans1:probe16 -0.259117108250727 0.050721896761908 -5.10858474924627 3.83371911568012e-07 *** df.mm.trans1:probe17 -0.170493007725128 0.050721896761908 -3.36132949691204 0.000802767874582734 *** df.mm.trans1:probe18 -0.394601535782572 0.050721896761908 -7.77970779828795 1.68777260501335e-14 *** df.mm.trans1:probe19 -0.434630832951564 0.050721896761908 -8.5688994437994 3.55165580885524e-17 *** df.mm.trans1:probe20 -0.481629165125197 0.0507218967619079 -9.49548806082701 1.35053347327047e-20 *** df.mm.trans1:probe21 -0.40623187376728 0.0507218967619079 -8.00900399435298 2.96762017672332e-15 *** df.mm.trans1:probe22 -0.521785518081098 0.0507218967619079 -10.2871846557788 9.56100533275995e-24 *** df.mm.trans2:probe2 -0.0363586308710689 0.050721896761908 -0.716823170902673 0.473637769013443 df.mm.trans2:probe3 0.0128843419715512 0.050721896761908 0.254019324869320 0.799528846695355 df.mm.trans2:probe4 -0.0159314199251702 0.050721896761908 -0.314093536366618 0.753510490139488 df.mm.trans2:probe5 -0.0452885343772323 0.050721896761908 -0.892879353266693 0.372120138354512 df.mm.trans2:probe6 -0.00265225777035689 0.050721896761908 -0.0522901929871979 0.95830711052405 df.mm.trans3:probe2 0.245970787473428 0.050721896761908 4.84940042025699 1.41934459772668e-06 *** df.mm.trans3:probe3 0.473437861651635 0.050721896761908 9.33399363738277 5.59227576863511e-20 *** df.mm.trans3:probe4 0.0392895255946597 0.050721896761908 0.774606789235178 0.438741120766759 df.mm.trans3:probe5 0.449859266941302 0.050721896761908 8.86913336567385 2.98222445171296e-18 *** df.mm.trans3:probe6 0.306989867648372 0.050721896761908 6.05241300595291 1.96385579626666e-09 *** df.mm.trans3:probe7 0.307783820242641 0.050721896761908 6.06806606005684 1.78744309582384e-09 *** df.mm.trans3:probe8 0.201212265781543 0.050721896761908 3.96697045313677 7.75782852195488e-05 *** df.mm.trans3:probe9 1.59903739309436 0.050721896761908 31.5255835285566 2.62516212050439e-155 *** df.mm.trans3:probe10 0.75522471532636 0.050721896761908 14.8895203756168 9.33566059034797e-46 *** df.mm.trans3:probe11 0.490560242227325 0.050721896761908 9.67156738104744 2.80384875652169e-21 *** df.mm.trans3:probe12 0.244546844132744 0.050721896761908 4.82132687743646 1.62961099963158e-06 *** df.mm.trans3:probe13 0.642980280192358 0.050721896761908 12.6765819348309 1.94905558365830e-34 *** df.mm.trans3:probe14 0.159677909216203 0.050721896761908 3.14810603329252 0.00168823892740870 ** df.mm.trans3:probe15 0.162545320455848 0.050721896761908 3.20463805245389 0.00139181854067592 ** df.mm.trans3:probe16 0.232659161654433 0.050721896761908 4.58695704434222 5.02220467418764e-06 *** df.mm.trans3:probe17 0.369563355679954 0.050721896761908 7.28607128819945 6.1360816612168e-13 *** df.mm.trans3:probe18 0.279234412699916 0.050721896761908 5.50520446841058 4.60295698721661e-08 *** df.mm.trans3:probe19 0.334145003564955 0.050721896761908 6.58778604304674 6.95230649117005e-11 *** df.mm.trans3:probe20 1.59536852851297 0.050721896761908 31.4532505754218 8.63118803270543e-155 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.09947510758449 0.196134520554370 20.9013441182990 9.07774582399455e-82 *** df.mm.trans1 0.107153965459142 0.167273909120059 0.640589832705073 0.521924720163458 df.mm.trans2 0.0279838606845282 0.145703610648252 0.192060173114618 0.847731076014134 df.mm.exp2 -0.0463742252165037 0.182672713055872 -0.253865092605921 0.79964797073997 df.mm.exp3 0.0437760796835588 0.182672713055872 0.239642138944800 0.810653040712309 df.mm.exp4 0.0627087125544194 0.182672713055872 0.343284508700757 0.731451059603422 df.mm.exp5 -0.0096957897890317 0.182672713055872 -0.0530773842838046 0.957680039380857 df.mm.exp6 -0.000889423106653505 0.182672713055872 -0.00486894343317421 0.996116057247195 df.mm.exp7 -0.044237476994331 0.182672713055872 -0.242167953025368 0.808695875043513 df.mm.exp8 -0.0761779184802622 0.182672713055872 -0.417018596844087 0.676747450694612 df.mm.trans1:exp2 0.0200113123223624 0.166080500948933 0.120491642354304 0.904116049208244 df.mm.trans2:exp2 0.110588916568928 0.110235354262883 1.00320734040734 0.315984921984773 df.mm.trans1:exp3 -0.0171679191533753 0.166080500948933 -0.103371070386247 0.917687609576156 df.mm.trans2:exp3 -0.00687731880861974 0.110235354262883 -0.0623875965619805 0.950265683981412 df.mm.trans1:exp4 0.0457738844859402 0.166080500948933 0.275612634983651 0.782898181571428 df.mm.trans2:exp4 -0.00951035152729925 0.110235354262883 -0.0862731524826374 0.931265227178722 df.mm.trans1:exp5 -0.0152045887578149 0.166080500948933 -0.091549511658145 0.92707289696019 df.mm.trans2:exp5 0.0818476889939253 0.110235354262883 0.742481298683357 0.457956783202352 df.mm.trans1:exp6 0.00436875915376283 0.166080500948933 0.0263050697029518 0.979018857358652 df.mm.trans2:exp6 0.111258079602696 0.110235354262883 1.00927765276986 0.313066931529926 df.mm.trans1:exp7 0.0126877387734024 0.166080500948933 0.0763951138207589 0.939118866845204 df.mm.trans2:exp7 0.0593959174923152 0.110235354262883 0.538810056805108 0.590128656784414 df.mm.trans1:exp8 0.0990528766935369 0.166080500948933 0.596414847785135 0.551022763844867 df.mm.trans2:exp8 0.0170491851129920 0.110235354262883 0.154661680247646 0.877116858571757 df.mm.trans1:probe2 -0.0873011342401137 0.126147196061970 -0.692057667276461 0.48904945856949 df.mm.trans1:probe3 -0.0111415563213117 0.126147196061970 -0.088321870553812 0.929637185338971 df.mm.trans1:probe4 -0.00233247614336451 0.126147196061970 -0.0184901148513731 0.985251269194597 df.mm.trans1:probe5 -0.0482602740434645 0.126147196061970 -0.382571119692239 0.702112853812564 df.mm.trans1:probe6 0.0786736171886006 0.126147196061970 0.623665207349926 0.532978806158319 df.mm.trans1:probe7 -0.0171951192758509 0.126147196061970 -0.136309960210322 0.891601583408058 df.mm.trans1:probe8 0.164031461091544 0.126147196061970 1.30031793184656 0.193768669840749 df.mm.trans1:probe9 0.189132831747634 0.126147196061970 1.49930270074906 0.134086554304281 df.mm.trans1:probe10 -0.0410447310997377 0.126147196061970 -0.325371727482347 0.744962598530179 df.mm.trans1:probe11 0.176502281533991 0.126147196061970 1.39917720761136 0.162046183585613 df.mm.trans1:probe12 -0.0126604764187475 0.126147196061970 -0.100362725561716 0.920074936434347 df.mm.trans1:probe13 0.0544089378759353 0.126147196061970 0.431313097511946 0.666326567421866 df.mm.trans1:probe14 0.174909129103966 0.126147196061970 1.38654789455677 0.165865015092083 df.mm.trans1:probe15 -0.083716513575157 0.126147196061970 -0.663641493339502 0.507061036028759 df.mm.trans1:probe16 0.0209430135086704 0.126147196061970 0.166020444072194 0.868171848800323 df.mm.trans1:probe17 0.223176180307546 0.126147196061970 1.7691727384722 0.0771464515427669 . df.mm.trans1:probe18 0.182761079273324 0.126147196061970 1.44879224412996 0.147685076550395 df.mm.trans1:probe19 0.0946806673368133 0.126147196061970 0.750557049958534 0.453082312551035 df.mm.trans1:probe20 0.0764045945012667 0.126147196061970 0.605678103726797 0.544855433539869 df.mm.trans1:probe21 0.037135074387282 0.126147196061970 0.294378912465396 0.768524791937785 df.mm.trans1:probe22 0.105158842861999 0.126147196061970 0.833620136989326 0.404678889937541 df.mm.trans2:probe2 0.0154047468156983 0.126147196061970 0.122117235234707 0.902828827513829 df.mm.trans2:probe3 0.0156357133149395 0.126147196061970 0.123948163756714 0.901379317701966 df.mm.trans2:probe4 0.0196556924870872 0.126147196061970 0.155815532177435 0.87620746463233 df.mm.trans2:probe5 0.0267417834768898 0.126147196061970 0.211988726754995 0.832155717469601 df.mm.trans2:probe6 0.191918764076414 0.126147196061970 1.52138747485226 0.128454531975171 df.mm.trans3:probe2 -0.0265572409041088 0.126147196061970 -0.210525812171540 0.833296909659107 df.mm.trans3:probe3 0.00591316172433249 0.126147196061970 0.0468750944050125 0.96262142016047 df.mm.trans3:probe4 -0.082980526720702 0.126147196061970 -0.657807143647786 0.510801852814541 df.mm.trans3:probe5 -0.0623667429355486 0.126147196061970 -0.49439658496183 0.621126392383435 df.mm.trans3:probe6 -0.131653442668499 0.126147196061970 -1.04364937769860 0.296880537171852 df.mm.trans3:probe7 -0.0981771703291435 0.126147196061970 -0.778274693326623 0.436577088019386 df.mm.trans3:probe8 -0.113356155806108 0.126147196061970 -0.8986022626331 0.369064289871464 df.mm.trans3:probe9 0.0955425466586323 0.126147196061970 0.757389380352905 0.448981368643619 df.mm.trans3:probe10 -0.0822157984010287 0.126147196061970 -0.651744953257937 0.51470399938247 df.mm.trans3:probe11 -0.0207180794115979 0.126147196061970 -0.164237335893063 0.869574956406433 df.mm.trans3:probe12 0.0153554490732941 0.126147196061970 0.121726439846913 0.903138254650015 df.mm.trans3:probe13 -0.0774720569515347 0.126147196061970 -0.6141401423895 0.539251707661939 df.mm.trans3:probe14 -0.0970859187277805 0.126147196061970 -0.769624072183788 0.441690746989756 df.mm.trans3:probe15 -0.0530063446882376 0.126147196061970 -0.420194394667306 0.674426801810468 df.mm.trans3:probe16 0.0925574041499782 0.126147196061970 0.733725417919785 0.463274907507366 df.mm.trans3:probe17 -0.0342677481618008 0.126147196061970 -0.271648908826849 0.785943762184307 df.mm.trans3:probe18 0.0937812020369783 0.126147196061970 0.743426766227193 0.457384586659219 df.mm.trans3:probe19 -0.0994310575837513 0.126147196061970 -0.788214567487535 0.430743698631115 df.mm.trans3:probe20 0.0273448385036570 0.126147196061970 0.216769292995016 0.828428969528551