chr14.7475_chr14_70418632_70421540_-_0.R fitVsDatCorrelation=0.891579723883786 cont.fitVsDatCorrelation=0.320552314834499 fstatistic=10535.3062329794,40,416 cont.fstatistic=2400.05592076238,40,416 residuals=-0.587951991509548,-0.0790819029898084,-0.0120571563031939,0.0807163777581773,0.482335768233043 cont.residuals=-0.493983754510108,-0.172507915875939,-0.0509605627785633,0.104421207151935,1.39399991957500 predictedValues: Include Exclude Both chr14.7475_chr14_70418632_70421540_-_0.R.tl.Lung 44.6853404347172 50.7332501879669 66.6085994541481 chr14.7475_chr14_70418632_70421540_-_0.R.tl.cerebhem 48.2915907795349 48.7465312397307 67.1347219413543 chr14.7475_chr14_70418632_70421540_-_0.R.tl.cortex 46.0712880858767 63.9969537290275 82.2238488855947 chr14.7475_chr14_70418632_70421540_-_0.R.tl.heart 47.4135873191194 55.8268058092416 69.5830914589807 chr14.7475_chr14_70418632_70421540_-_0.R.tl.kidney 44.7241963748022 49.5557982911887 67.5544781160384 chr14.7475_chr14_70418632_70421540_-_0.R.tl.liver 50.9441381016416 49.7753350839061 61.6520330484217 chr14.7475_chr14_70418632_70421540_-_0.R.tl.stomach 46.027022962024 48.1071323240314 63.4827898996396 chr14.7475_chr14_70418632_70421540_-_0.R.tl.testicle 45.8128696472518 49.6594926663065 65.97711418767 diffExp=-6.0479097532497,-0.454940460195843,-17.9256656431508,-8.4132184901222,-4.83160191638652,1.16880301773557,-2.08010936200733,-3.84662301905471 diffExpScore=1.03079822833109 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,-1,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,0,-1,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 54.6213438376257 53.2154892972726 56.8618514203076 cerebhem 56.1489113170944 56.3439901354978 59.7981748532482 cortex 55.8534786766118 55.0359681302695 65.5403094098824 heart 55.0561512770836 62.3680012872086 54.0863494059757 kidney 52.9552750949654 63.9596649154874 51.5858878259532 liver 55.7453577828983 58.612591019747 56.0573653272053 stomach 56.7630302765563 51.385192665789 62.5230431727246 testicle 53.0662207758718 54.4642458203636 53.2361556683207 cont.diffExp=1.40585454035312,-0.195078818403417,0.817510546342241,-7.31185001012509,-11.0043898205220,-2.86723323684872,5.37783761076727,-1.39802504449176 cont.diffExpScore=1.87802638692669 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,-1,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=-0.0936550402327112 cont.tran.correlation=-0.431554348877177 tran.covariance=-0.000360050430578958 cont.tran.covariance=-0.00083413235132302 tran.mean=49.3982083147729 cont.tran.mean=55.9746820193964 weightedLogRatios: wLogRatio Lung -0.490368270740303 cerebhem -0.036399449712575 cortex -1.31277881239161 heart -0.643675485584518 kidney -0.395136122570836 liver 0.0909633499732828 stomach -0.170235574252272 testicle -0.311603860546827 cont.weightedLogRatios: wLogRatio Lung 0.103971968140455 cerebhem -0.0139763127436733 cortex 0.0592059605738715 heart -0.50761156069968 kidney -0.767275059940256 liver -0.202922315991952 stomach 0.397057574205803 testicle -0.103613502223512 varWeightedLogRatios=0.190569964575518 cont.varWeightedLogRatios=0.133787705697784 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.70703908579436 0.068268013314092 54.3012591964376 6.15436745588028e-191 *** df.mm.trans1 0.0838324415592544 0.0553726706879291 1.51396782054671 0.130793370761064 df.mm.trans2 0.178896860024391 0.0553726706879291 3.23077897095886 0.00133262903512671 ** df.mm.exp2 0.0297967855867856 0.0748775171641348 0.397940352662465 0.690878286145042 df.mm.exp3 0.0521867086163937 0.0748775171641348 0.696960991668542 0.486216488414455 df.mm.exp4 0.111248064697586 0.0748775171641348 1.485733887967 0.138106938195371 df.mm.exp5 -0.0367137426412532 0.0748775171641348 -0.490317307941382 0.624167883731826 df.mm.exp6 0.189349755544056 0.0748775171641349 2.52879319073833 0.0118142822306731 * df.mm.exp7 0.0244969619290559 0.0748775171641348 0.327160446243931 0.743711095376478 df.mm.exp8 0.0130533639426616 0.0748775171641348 0.174329550939143 0.861691282543248 df.mm.trans1:exp2 0.0478151626204216 0.0603681842929904 0.792058982399669 0.428777704641267 df.mm.trans2:exp2 -0.0697442626188768 0.0603681842929904 -1.15531489700569 0.24862464549317 df.mm.trans1:exp3 -0.0216422640894211 0.0603681842929904 -0.358504472892257 0.720147681806082 df.mm.trans2:exp3 0.180067257738940 0.0603681842929904 2.98281718835542 0.00302416216053831 ** df.mm.trans1:exp4 -0.0519847181214702 0.0603681842929904 -0.861127740221043 0.389663748853134 df.mm.trans2:exp4 -0.0155754377020109 0.0603681842929904 -0.258007390555549 0.796528792905674 df.mm.trans1:exp5 0.0375829103814683 0.0603681842929904 0.622561549955913 0.533913785780812 df.mm.trans2:exp5 0.0132314976782175 0.0603681842929904 0.219179984178419 0.826617344179616 df.mm.trans1:exp6 -0.0582655478239566 0.0603681842929904 -0.96516979111333 0.335020510612165 df.mm.trans2:exp6 -0.208411691532033 0.0603681842929904 -3.45234321642886 0.00061268217383833 *** df.mm.trans1:exp7 0.00508622442157282 0.0603681842929904 0.0842533940873124 0.932895496396843 df.mm.trans2:exp7 -0.0776480325325843 0.0603681842929904 -1.28624098011178 0.199074374812304 df.mm.trans1:exp8 0.0118661910201042 0.0603681842929904 0.196563656155583 0.844265004608653 df.mm.trans2:exp8 -0.0344453179460443 0.0603681842929904 -0.570587277875837 0.568587508896491 df.mm.trans1:probe2 -0.0547426880526461 0.0383633115929092 -1.42695418564346 0.154343219258465 df.mm.trans1:probe3 0.0689442679389739 0.0383633115929092 1.79714068145559 0.0730384686207202 . df.mm.trans1:probe4 0.0721766486638832 0.0383633115929092 1.88139776434795 0.0606158972638439 . df.mm.trans1:probe5 0.0268496746696118 0.0383633115929092 0.69987896129839 0.484394083056829 df.mm.trans1:probe6 0.000833654734384638 0.0383633115929092 0.0217305206399002 0.982673336624562 df.mm.trans2:probe2 0.135366049441066 0.0383633115929092 3.52852879014977 0.000464477131613894 *** df.mm.trans2:probe3 0.08344108778343 0.0383633115929092 2.17502307071042 0.0301909975894218 * df.mm.trans2:probe4 0.152359896523313 0.0383633115929092 3.97150011813563 8.41536738739144e-05 *** df.mm.trans2:probe5 0.105430964693883 0.0383633115929092 2.74822376682858 0.0062526380420108 ** df.mm.trans2:probe6 0.0517944384529892 0.0383633115929092 1.35010342700870 0.177716906974187 df.mm.trans3:probe2 0.225922465879661 0.0383633115929092 5.88902408314039 8.0173991419814e-09 *** df.mm.trans3:probe3 0.280618941836311 0.0383633115929092 7.31477367788496 1.33686738836414e-12 *** df.mm.trans3:probe4 0.901870650053016 0.0383633115929092 23.5086756749047 2.29710898252452e-78 *** df.mm.trans3:probe5 0.159692790939162 0.0383633115929092 4.1626435338465 3.82537198449954e-05 *** df.mm.trans3:probe6 0.107575753858383 0.0383633115929092 2.8041310666795 0.00528155730068862 ** df.mm.trans3:probe7 -0.0722234832038185 0.0383633115929092 -1.88261858022621 0.0604497020973921 . cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.96432436668445 0.142792534464730 27.7628265479359 9.73009029639686e-97 *** df.mm.trans1 0.0277015516000269 0.115820039338659 0.239177535754648 0.81108571098624 df.mm.trans2 0.0190123210292945 0.115820039338659 0.164153985250361 0.869689650314703 df.mm.exp2 0.0343581762977633 0.156617278447827 0.219376665450158 0.82646424372038 df.mm.exp3 -0.0860961756498708 0.156617278447827 -0.54972335430124 0.582804132229744 df.mm.exp4 0.216674549620821 0.156617278447827 1.38346516915757 0.167264221576514 df.mm.exp5 0.250302638217827 0.156617278447827 1.59818023080518 0.110762109899147 df.mm.exp6 0.131218569876656 0.156617278447827 0.837829460306757 0.402607589710824 df.mm.exp7 -0.0914494492188837 0.156617278447827 -0.583903960822226 0.55960139509392 df.mm.exp8 0.0601976867005154 0.156617278447827 0.384361721114753 0.700906767293316 df.mm.trans1:exp2 -0.00677560327447204 0.126268886668343 -0.0536601173357045 0.957231717848771 df.mm.trans2:exp2 0.0227678998935827 0.126268886668343 0.180312826812077 0.85699479046778 df.mm.trans1:exp3 0.108403266146868 0.126268886668343 0.858511300821076 0.391104576179488 df.mm.trans2:exp3 0.119733606969264 0.126268886668343 0.948243151012774 0.34355619581044 df.mm.trans1:exp4 -0.208745672016091 0.126268886668343 -1.65318375352735 0.0990478861424675 . df.mm.trans2:exp4 -0.0579717118321353 0.126268886668343 -0.459113193770399 0.646392680796004 df.mm.trans1:exp5 -0.281279666195288 0.126268886668343 -2.22762450526784 0.0264397548905081 * df.mm.trans2:exp5 -0.0663994954110549 0.126268886668343 -0.525857930350329 0.599267123518715 df.mm.trans1:exp6 -0.110849150613026 0.126268886668343 -0.877881745359665 0.380514624389055 df.mm.trans2:exp6 -0.0346185387307967 0.126268886668343 -0.274165232974023 0.784093731067646 df.mm.trans1:exp7 0.129909968480495 0.126268886668343 1.02883593819684 0.304154591648627 df.mm.trans2:exp7 0.0564499935693513 0.126268886668343 0.447061782667195 0.655063117297903 df.mm.trans1:exp8 -0.0890818235997646 0.126268886668343 -0.705493062861531 0.480898297691974 df.mm.trans2:exp8 -0.0370027464884401 0.126268886668343 -0.293047222199965 0.769632179701385 df.mm.trans1:probe2 0.0383299746760944 0.0802424770676736 0.477676862390082 0.633131100059072 df.mm.trans1:probe3 0.056535187133743 0.0802424770676736 0.704554360729209 0.481481846416484 df.mm.trans1:probe4 0.0275709568539899 0.0802424770676735 0.343595535201855 0.731324070595023 df.mm.trans1:probe5 -0.02821774756013 0.0802424770676736 -0.351655988091347 0.725274321714482 df.mm.trans1:probe6 0.0149660400362269 0.0802424770676736 0.186510194888489 0.852135603210502 df.mm.trans2:probe2 -0.139082815302488 0.0802424770676736 -1.73328167804678 0.083786603050672 . df.mm.trans2:probe3 0.044400632417052 0.0802424770676736 0.553330779901101 0.580334175202958 df.mm.trans2:probe4 0.0149146107455707 0.0802424770676735 0.185869271370975 0.852637876087166 df.mm.trans2:probe5 -0.0586868573989536 0.0802424770676736 -0.731368964961778 0.464965578622616 df.mm.trans2:probe6 0.0216210695402467 0.0802424770676736 0.269446686223461 0.787719560016268 df.mm.trans3:probe2 -0.006306249866058 0.0802424770676736 -0.0785899201583663 0.93739659338968 df.mm.trans3:probe3 -0.0339732767673877 0.0802424770676735 -0.423382702140861 0.672234865095824 df.mm.trans3:probe4 0.191179076764471 0.0802424770676735 2.38251713744128 0.0176431034502458 * df.mm.trans3:probe5 -0.0742116337191216 0.0802424770676735 -0.924842258502741 0.355584127698688 df.mm.trans3:probe6 0.0871122814557557 0.0802424770676735 1.08561306478972 0.278278907156303 df.mm.trans3:probe7 0.0433047940126941 0.0802424770676736 0.539674192462583 0.589710487093848