chr7.21114_chr7_132863964_132864351_+_1.R fitVsDatCorrelation=0.951147387783017 cont.fitVsDatCorrelation=0.274150128664780 fstatistic=8276.93260658668,46,554 cont.fstatistic=842.258373730192,46,554 residuals=-0.466521776943031,-0.0916785935868676,-0.00262948499486650,0.083158226429976,0.790772831400482 cont.residuals=-0.836452728042428,-0.364176872266629,-0.162521559534944,0.301175733378743,1.96039291642542 predictedValues: Include Exclude Both chr7.21114_chr7_132863964_132864351_+_1.R.tl.Lung 59.1035293007686 189.504913245731 54.1564401676304 chr7.21114_chr7_132863964_132864351_+_1.R.tl.cerebhem 61.6350531710399 121.591082361695 58.251333048816 chr7.21114_chr7_132863964_132864351_+_1.R.tl.cortex 54.3703424921219 137.803417842571 51.8187707025983 chr7.21114_chr7_132863964_132864351_+_1.R.tl.heart 57.0694876888696 152.046286432262 52.8209865493824 chr7.21114_chr7_132863964_132864351_+_1.R.tl.kidney 59.6668541129039 247.195124520501 53.1162048777193 chr7.21114_chr7_132863964_132864351_+_1.R.tl.liver 54.1023719258193 148.710808639422 52.8071466021746 chr7.21114_chr7_132863964_132864351_+_1.R.tl.stomach 67.5313662379201 190.288893706631 73.6416059257798 chr7.21114_chr7_132863964_132864351_+_1.R.tl.testicle 54.680163032362 137.033918849417 53.8335586794002 diffExp=-130.401383944962,-59.9560291906547,-83.4330753504496,-94.9767987433923,-187.528270407597,-94.6084367136024,-122.757527468711,-82.3537558170546 diffExpScore=0.9988331596576 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 74.02172158641 74.6300094243212 81.3440782812145 cerebhem 63.1116107590464 58.6213957582198 71.2403224473683 cortex 69.8675291324409 98.688965223136 74.5716480485307 heart 62.5284589289471 58.9120966956679 69.8985216072736 kidney 63.7426481739663 73.7339451813004 81.6909608358342 liver 72.0894952337849 72.0679482779865 71.7343569933858 stomach 72.8150853197924 59.6876538566306 81.7937542314257 testicle 65.2088559341767 87.0091551402492 72.1545721558106 cont.diffExp=-0.608287837911178,4.49021500082652,-28.8214360906951,3.61636223327919,-9.99129700733415,0.0215469557983567,13.1274314631617,-21.8002992060725 cont.diffExpScore=2.01331225778373 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,-1,0,0,0,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,-1,0,0,0,0,-1 cont.diffExp1.3Score=0.666666666666667 cont.diffExp1.2=0,0,-1,0,0,0,1,-1 cont.diffExp1.2Score=1.5 tran.correlation=0.389505727502158 cont.tran.correlation=0.198077549495561 tran.covariance=0.00706156191552864 cont.tran.covariance=0.00305831047924465 tran.mean=112.020850847502 cont.tran.mean=70.4210359141298 weightedLogRatios: wLogRatio Lung -5.43163802922441 cerebhem -3.03091418647487 cortex -4.14860747402171 heart -4.44315907979327 kidney -6.82198352756744 liver -4.54646598078742 stomach -4.90063755010575 testicle -4.09831903780977 cont.weightedLogRatios: wLogRatio Lung -0.035260844064476 cerebhem 0.30319115975255 cortex -1.52629859343908 heart 0.244606503010613 kidney -0.615586930636692 liver 0.00127877797624597 stomach 0.832670034690593 testicle -1.24648640649173 varWeightedLogRatios=1.23083315355405 cont.varWeightedLogRatios=0.655348877064422 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.24462333652872 0.0853285946183536 61.4638429237722 1.4273732846976e-249 *** df.mm.trans1 -1.19028282749507 0.067781437512025 -17.5606017102235 3.28331131795731e-55 *** df.mm.trans2 -0.0262134646660903 0.067781437512025 -0.386735153875127 0.699100789093876 df.mm.exp2 -0.474701285764036 0.0902187559592002 -5.26166960203609 2.04367785753919e-07 *** df.mm.exp3 -0.357934154088034 0.0902187559592002 -3.96740290067737 8.2206507489466e-05 *** df.mm.exp4 -0.230282679459288 0.0902187559592002 -2.55249229509914 0.0109626200301953 * df.mm.exp5 0.294643909701836 0.0902187559592002 3.26588309237032 0.00115867847679386 ** df.mm.exp6 -0.305593660537824 0.0902187559592002 -3.38725198866656 0.00075608410799386 *** df.mm.exp7 -0.169903271695384 0.0902187559592002 -1.88323669384468 0.0601919087002926 . df.mm.exp8 -0.395996261833074 0.0902187559592002 -4.38928976156749 1.36215778946364e-05 *** df.mm.trans1:exp2 0.51664139937309 0.0695182203206668 7.43174087296794 4.08710942692948e-13 *** df.mm.trans2:exp2 0.0309499651610938 0.0695182203206668 0.445206523100431 0.656344416486803 df.mm.trans1:exp3 0.274462344440828 0.0695182203206668 3.94806344545092 8.89379167791914e-05 *** df.mm.trans2:exp3 0.0393473636769466 0.0695182203206668 0.566000733267464 0.571622466237734 df.mm.trans1:exp4 0.195261647007165 0.0695182203206668 2.80878374196695 0.00514839490123386 ** df.mm.trans2:exp4 0.0100527183472231 0.0695182203206668 0.144605519256001 0.885074929235182 df.mm.trans1:exp5 -0.285157891047206 0.0695182203206668 -4.10191586798192 4.71261471832001e-05 *** df.mm.trans2:exp5 -0.0288808587307799 0.0695182203206668 -0.41544301044476 0.677978482484711 df.mm.trans1:exp6 0.217181048719839 0.0695182203206668 3.12408815585392 0.00187685362183351 ** df.mm.trans2:exp6 0.0631822473127987 0.0695182203206668 0.908858814586418 0.363819860333196 df.mm.trans1:exp7 0.303204806577319 0.0695182203206668 4.36151565990507 1.54054336112649e-05 *** df.mm.trans2:exp7 0.174031730664823 0.0695182203206668 2.50339738074517 0.0125873576286135 * df.mm.trans1:exp8 0.31820661518634 0.0695182203206668 4.5773124472771 5.81904016169988e-06 *** df.mm.trans2:exp8 0.0718097882556048 0.0695182203206668 1.03296355868099 0.302071664994501 df.mm.trans1:probe2 -0.0465777323962659 0.0497994048930779 -0.93530700811126 0.350037608894279 df.mm.trans1:probe3 0.343684075169908 0.0497994048930779 6.90136912093261 1.41326006184067e-11 *** df.mm.trans1:probe4 -0.0113435177032483 0.0497994048930779 -0.227784201992040 0.8198980503179 df.mm.trans1:probe5 0.181862099014861 0.0497994048930779 3.65189301770431 0.00028500356980377 *** df.mm.trans1:probe6 0.00642756560784873 0.0497994048930779 0.129069124854987 0.89734979611477 df.mm.trans2:probe2 -0.103221181466103 0.0497994048930779 -2.07273925637714 0.0386583809566206 * df.mm.trans2:probe3 0.353392843288292 0.0497994048930779 7.09632663376292 3.93655900701666e-12 *** df.mm.trans2:probe4 0.0765687016252552 0.0497994048930779 1.53754250255907 0.124731434707859 df.mm.trans2:probe5 0.175344012389182 0.0497994048930779 3.52100618000667 0.000465317179145371 *** df.mm.trans2:probe6 -0.00798786074158033 0.0497994048930779 -0.160400726850666 0.872623885617138 df.mm.trans3:probe2 -0.226150606770161 0.0497994048930779 -4.54123111020542 6.86678440256382e-06 *** df.mm.trans3:probe3 -0.231951982510284 0.0497994048930779 -4.65772599106953 4.00745784507813e-06 *** df.mm.trans3:probe4 0.131191690876116 0.0497994048930779 2.63440278368371 0.00866427955826225 ** df.mm.trans3:probe5 0.296440050931774 0.0497994048930779 5.95268259868261 4.68391730267529e-09 *** df.mm.trans3:probe6 -0.0796594222479036 0.0497994048930779 -1.59960590731831 0.110256137782933 df.mm.trans3:probe7 -0.0810621110276564 0.0497994048930779 -1.62777268527006 0.104141640029615 df.mm.trans3:probe8 -0.210189102964392 0.0497994048930779 -4.22071515544572 2.84565235447060e-05 *** df.mm.trans3:probe9 -0.193959066133484 0.0497994048930779 -3.89480690682801 0.000110276364224008 *** df.mm.trans3:probe10 -0.0391029166414885 0.0497994048930779 -0.785208512540353 0.432666985457678 df.mm.trans3:probe11 0.296504532732453 0.0497994048930779 5.95397742943042 4.6492044441818e-09 *** df.mm.trans3:probe12 -0.0256134269031929 0.0497994048930779 -0.514331987665041 0.607225007399109 df.mm.trans3:probe13 -0.107699537283823 0.0497994048930779 -2.16266715465898 0.0309939502497077 * cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.23764268539022 0.265790443700511 15.9435479560174 2.23588358278081e-47 *** df.mm.trans1 0.0274164657042245 0.211132720883985 0.129854176981357 0.89672893195217 df.mm.trans2 0.0560864444878819 0.211132720883985 0.265645439764407 0.79061110999534 df.mm.exp2 -0.268267725633017 0.281022830432814 -0.954611855626988 0.340190361028946 df.mm.exp3 0.308600520565797 0.281022830432814 1.09813327298180 0.272623329314812 df.mm.exp4 -0.253589501122407 0.281022830432814 -0.90238042486386 0.367246976667842 df.mm.exp5 -0.165839468161526 0.281022830432814 -0.590128097087737 0.555345393834399 df.mm.exp6 0.0643346821082532 0.281022830432814 0.228930446715553 0.819007460122682 df.mm.exp7 -0.245365785538912 0.281022830432814 -0.873116910683076 0.382977638848592 df.mm.exp8 0.146584733588174 0.281022830432814 0.521611476770102 0.602149332601054 df.mm.trans1:exp2 0.108813898860629 0.216542633884252 0.502505658626065 0.615511555076254 df.mm.trans2:exp2 0.0268247734816976 0.216542633884252 0.123877561663151 0.90145715020707 df.mm.trans1:exp3 -0.366358097493037 0.216542633884252 -1.69185204281235 0.091236521803665 . df.mm.trans2:exp3 -0.0291700789844994 0.216542633884252 -0.134708248723397 0.89289147655062 df.mm.trans1:exp4 0.0848527120081131 0.216542633884252 0.391852220904773 0.695318094152895 df.mm.trans2:exp4 0.0170932501055922 0.216542633884252 0.0789371118240348 0.937111147817605 df.mm.trans1:exp5 0.0163347377058666 0.216542633884252 0.0754342801362526 0.93989641663855 df.mm.trans2:exp5 0.153760049802182 0.216542633884252 0.710068253276955 0.477960583869472 df.mm.trans1:exp6 -0.0907849306884952 0.216542633884252 -0.419247374339329 0.67519786312314 df.mm.trans2:exp6 -0.0992679794624313 0.216542633884252 -0.458422333199719 0.646828822776885 df.mm.trans1:exp7 0.22893035012381 0.216542633884252 1.05720682351255 0.290877978858593 df.mm.trans2:exp7 0.0219482840553629 0.216542633884252 0.101357795745178 0.919303110168238 df.mm.trans1:exp8 -0.27334803175065 0.216542633884252 -1.26232893194031 0.207361575504328 df.mm.trans2:exp8 0.00688591360319339 0.216542633884252 0.0317993435273079 0.974643522905282 df.mm.trans1:probe2 0.0532800808900206 0.155120402272576 0.34347564929852 0.731370965354593 df.mm.trans1:probe3 0.292040235612521 0.155120402272576 1.88266811672749 0.0602691240566368 . df.mm.trans1:probe4 0.109548523852196 0.155120402272576 0.706216089226605 0.480350648766921 df.mm.trans1:probe5 0.063182924398521 0.155120402272576 0.407315372271255 0.683933709108775 df.mm.trans1:probe6 0.228637481023599 0.155120402272576 1.47393558599623 0.141066914831484 df.mm.trans2:probe2 0.0321181739159742 0.155120402272576 0.207053188654943 0.836044400170325 df.mm.trans2:probe3 0.0434460538701005 0.155120402272576 0.280079559062499 0.779521013788264 df.mm.trans2:probe4 0.105992073487584 0.155120402272576 0.683289057627226 0.494709862201185 df.mm.trans2:probe5 0.151819303450044 0.155120402272576 0.978719118992926 0.328145971869806 df.mm.trans2:probe6 0.0240821786462012 0.155120402272576 0.155248299342882 0.876682119113083 df.mm.trans3:probe2 0.246298545263465 0.155120402272576 1.58778949548282 0.112904482194409 df.mm.trans3:probe3 0.0325079323926828 0.155120402272576 0.209565807697947 0.834083609002039 df.mm.trans3:probe4 -0.0837545528394469 0.155120402272576 -0.539932540223009 0.589460517601291 df.mm.trans3:probe5 0.201962851673628 0.155120402272576 1.30197478033058 0.193466077009506 df.mm.trans3:probe6 0.203262576820377 0.155120402272576 1.31035359528791 0.190619244755236 df.mm.trans3:probe7 -0.128241474816689 0.155120402272576 -0.826722165091766 0.408750475053714 df.mm.trans3:probe8 0.184025666737751 0.155120402272576 1.18634082971486 0.235996243762136 df.mm.trans3:probe9 0.171565811308333 0.155120402272576 1.10601706026303 0.269199186175052 df.mm.trans3:probe10 -0.0200432983946664 0.155120402272576 -0.129211232700690 0.897237404412541 df.mm.trans3:probe11 -0.0169035137230721 0.155120402272576 -0.108970280346291 0.91326552009029 df.mm.trans3:probe12 0.191394936205229 0.155120402272576 1.23384760096813 0.217782878113108 df.mm.trans3:probe13 0.0259762696875872 0.155120402272576 0.167458756598258 0.867070204936165