chr15.8601_chr15_7638198_7660204_+_0.R fitVsDatCorrelation=0.992676310599764 cont.fitVsDatCorrelation=0.283874156828127 fstatistic=10299.0484153579,43,485 cont.fstatistic=152.375196612875,43,485 residuals=-1.30087407330845,-0.0835298964307817,0.000158156870586473,0.0881205322035183,0.733766626325426 cont.residuals=-1.90411087788229,-0.852151744325746,-0.527512409049861,1.16833737794940,3.61801308521202 predictedValues: Include Exclude Both chr15.8601_chr15_7638198_7660204_+_0.R.tl.Lung 49.4494264590659 903.003078403075 54.8187221310519 chr15.8601_chr15_7638198_7660204_+_0.R.tl.cerebhem 48.7854066550486 767.485051827312 48.6886676859178 chr15.8601_chr15_7638198_7660204_+_0.R.tl.cortex 47.8453347502572 700.83108362781 52.0484527464001 chr15.8601_chr15_7638198_7660204_+_0.R.tl.heart 48.3583796913819 644.83138615399 50.6014818558592 chr15.8601_chr15_7638198_7660204_+_0.R.tl.kidney 48.6168296354471 838.282805380402 54.8272100649075 chr15.8601_chr15_7638198_7660204_+_0.R.tl.liver 48.930056793058 537.205291380231 55.6523967082033 chr15.8601_chr15_7638198_7660204_+_0.R.tl.stomach 49.1556478551705 628.862417020332 55.0062532847956 chr15.8601_chr15_7638198_7660204_+_0.R.tl.testicle 47.9205097382063 768.18182051854 51.9684359468529 diffExp=-853.55365194401,-718.699645172263,-652.985748877552,-596.473006462608,-789.665975744955,-488.275234587173,-579.706769165161,-720.261310780334 diffExpScore=0.999814836120413 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 129.548169398846 100.079605313779 107.165401073923 cerebhem 133.916226737176 100.935678020237 142.614836494991 cortex 142.254341904329 90.0673344303472 141.605677297237 heart 141.312787063436 119.009106422987 138.479204764719 kidney 52.5349535707551 78.4899711792436 133.803207356565 liver 104.796646772952 68.7477631049736 105.043063553235 stomach 140.897068076408 56.9373503784439 116.255146246112 testicle 96.4799106647161 80.4848211617149 126.020475140709 cont.diffExp=29.4685640850672,32.9805487169395,52.1870074739815,22.3036806404494,-25.9550176084885,36.0488836679782,83.9597176979636,15.9950895030012 cont.diffExpScore=1.20529194103054 cont.diffExp1.5=0,0,1,0,0,1,1,0 cont.diffExp1.5Score=0.75 cont.diffExp1.4=0,0,1,0,-1,1,1,0 cont.diffExp1.4Score=1.33333333333333 cont.diffExp1.3=0,1,1,0,-1,1,1,0 cont.diffExp1.3Score=1.25 cont.diffExp1.2=1,1,1,0,-1,1,1,0 cont.diffExp1.2Score=1.2 tran.correlation=0.114358711700623 cont.tran.correlation=0.329676936341490 tran.covariance=0.000113524128611558 cont.tran.covariance=0.0196110939284395 tran.mean=386.109032868083 cont.tran.mean=102.280733387521 weightedLogRatios: wLogRatio Lung -15.5502456941640 cerebhem -14.5094542814735 cortex -13.9854907732844 heart -13.4019862097293 kidney -15.1129630218857 liver -12.1917142939120 stomach -13.1765237846471 testicle -14.5848599366785 cont.weightedLogRatios: wLogRatio Lung 1.22204366667882 cerebhem 1.34462577716329 cortex 2.16147201981488 heart 0.835704203749502 kidney -1.67110050118371 liver 1.87232423526927 stomach 4.07281235650148 testicle 0.811837227889045 varWeightedLogRatios=1.21663826269597 cont.varWeightedLogRatios=2.57710897222804 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 6.44226919000918 0.085669372035285 75.1992110710906 1.73591211688303e-269 *** df.mm.trans1 -2.57424582137366 0.0685828124406488 -37.5348535553481 1.43880040305442e-145 *** df.mm.trans2 0.162166659546215 0.0685828124406488 2.36453790352435 0.0184454992398003 * df.mm.exp2 -0.057540721376875 0.0918370581872194 -0.626552314639394 0.531247522399111 df.mm.exp3 -0.234579201193284 0.0918370581872194 -2.55429785996705 0.0109447142883984 * df.mm.exp4 -0.278997117466168 0.0918370581872194 -3.03795791125412 0.00251030300526446 ** df.mm.exp5 -0.0915059666199725 0.0918370581872194 -0.99639479341148 0.319555212878582 df.mm.exp6 -0.544997605561849 0.0918370581872194 -5.93439746785894 5.61887211305787e-09 *** df.mm.exp7 -0.37118726614597 0.0918370581872194 -4.04180266085251 6.1673355478642e-05 *** df.mm.exp8 -0.139711133401418 0.0918370581872195 -1.52129364941767 0.128837834363321 df.mm.trans1:exp2 0.0440214859591293 0.072042915656552 0.611045313171272 0.54145584773523 df.mm.trans2:exp2 -0.105066238293363 0.072042915656552 -1.45838403867830 0.145381977424616 df.mm.trans1:exp3 0.201602357356408 0.072042915656552 2.79836477353999 0.0053406931469136 ** df.mm.trans2:exp3 -0.0188798681718503 0.072042915656552 -0.262064187710776 0.793383221912316 df.mm.trans1:exp4 0.256686177910099 0.072042915656552 3.56296209794993 0.00040293832708504 *** df.mm.trans2:exp4 -0.0577399792243332 0.072042915656552 -0.801466441191736 0.423254142950721 df.mm.trans1:exp5 0.0745252667771366 0.072042915656552 1.03445656103674 0.301438292155569 df.mm.trans2:exp5 0.0171355242618107 0.072042915656552 0.237851620879704 0.812096627904412 df.mm.trans1:exp6 0.534439011961985 0.072042915656552 7.41834234624539 5.3443790947235e-13 *** df.mm.trans2:exp6 0.0256519575929706 0.072042915656552 0.356064955994568 0.721946749915301 df.mm.trans1:exp7 0.365228557120392 0.072042915656552 5.06959711155411 5.68182023321178e-07 *** df.mm.trans2:exp7 0.00937380354840872 0.072042915656552 0.130114161302080 0.89653005286372 df.mm.trans1:exp8 0.108304264826426 0.072042915656552 1.50332983943545 0.133404858433998 df.mm.trans2:exp8 -0.0219883784992677 0.072042915656552 -0.305212223837417 0.760335463235878 df.mm.trans1:probe2 0.078472946607327 0.0493244125169195 1.59095552492204 0.112271146803285 df.mm.trans1:probe3 0.194194042297025 0.0493244125169195 3.93707765359419 9.45587277687083e-05 *** df.mm.trans1:probe4 0.0801560913954467 0.0493244125169195 1.62507949522868 0.104795239822453 df.mm.trans1:probe5 0.0545967176623738 0.0493244125169195 1.10689037895070 0.268890015049601 df.mm.trans1:probe6 0.119413657475299 0.0493244125169195 2.42098489129165 0.0158446049640780 * df.mm.trans2:probe2 0.523169587070139 0.0493244125169195 10.6067069099035 8.86556620886173e-24 *** df.mm.trans2:probe3 1.11788396137969 0.0493244125169195 22.6639082826628 4.33247212127351e-78 *** df.mm.trans2:probe4 -0.269045335156763 0.0493244125169195 -5.45460800094625 7.83584986266937e-08 *** df.mm.trans2:probe5 0.78433815184724 0.0493244125169195 15.901621769508 3.96421349279305e-46 *** df.mm.trans2:probe6 1.06429544190010 0.0493244125169195 21.5774580495008 6.95494195346947e-73 *** df.mm.trans3:probe2 -0.0125228920095012 0.0493244125169195 -0.253888315551767 0.799689437710331 df.mm.trans3:probe3 -0.060364267540042 0.0493244125169195 -1.22382131808129 0.221613840601007 df.mm.trans3:probe4 0.01127494139428 0.0493244125169195 0.228587444207519 0.819285933354231 df.mm.trans3:probe5 -0.0356320009659056 0.0493244125169195 -0.722400919700421 0.470396196210478 df.mm.trans3:probe6 0.0135444394655845 0.0493244125169195 0.274599103657614 0.783741182548812 df.mm.trans3:probe7 -0.105205765947501 0.0493244125169195 -2.13293500275168 0.0334314966775965 * df.mm.trans3:probe8 -0.146054322380699 0.0493244125169195 -2.96109603597607 0.00321573698468127 ** df.mm.trans3:probe9 -0.0572311221505026 0.0493244125169195 -1.16030012787017 0.246497462478375 df.mm.trans3:probe10 0.13060851165613 0.0493244125169195 2.64794865243104 0.00836195341711203 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.676867375707 0.679983144727496 6.8779166248029 1.87955622121121e-11 *** df.mm.trans1 0.074040593196381 0.544362067442733 0.136013505761347 0.891867039381014 df.mm.trans2 -0.102092586214221 0.544362067442733 -0.187545371582969 0.851311487438028 df.mm.exp2 -0.244094905310406 0.728937893964566 -0.334863789263056 0.737872612909787 df.mm.exp3 -0.290517381360199 0.728937893964565 -0.398548880179799 0.690401032678533 df.mm.exp4 0.00381037441394618 0.728937893964565 0.00522729637942435 0.99583138927623 df.mm.exp5 -1.36756578089635 0.728937893964565 -1.87610740533518 0.061240869590939 . df.mm.exp6 -0.567549674386043 0.728937893964565 -0.778598120752428 0.436596179730105 df.mm.exp7 -0.561451408455876 0.728937893964566 -0.770232159837706 0.441537196708420 df.mm.exp8 -0.674686231712158 0.728937893964566 -0.925574369638896 0.355127527051136 df.mm.trans1:exp2 0.277256559707836 0.571825930080392 0.484861817422056 0.627993280558356 df.mm.trans2:exp2 0.252612445547325 0.571825930080392 0.441764586491926 0.658856466680528 df.mm.trans1:exp3 0.384081200506283 0.571825930080392 0.67167503308618 0.502110399348168 df.mm.trans2:exp3 0.18510900985159 0.571825930080392 0.323715662606566 0.746292853973808 df.mm.trans1:exp4 0.0831126305830255 0.571825930080392 0.145346033138688 0.884498055046784 df.mm.trans2:exp4 0.169423717889009 0.571825930080392 0.296285476010487 0.767138903095841 df.mm.trans1:exp5 0.464991734811505 0.571825930080392 0.813170075631464 0.416519555468031 df.mm.trans2:exp5 1.12457071940121 0.571825930080392 1.96663120758288 0.0497954952937312 * df.mm.trans1:exp6 0.355518672871974 0.571825930080392 0.62172534362335 0.534414614500232 df.mm.trans2:exp6 0.192027951304831 0.571825930080392 0.335815396265494 0.737155301861068 df.mm.trans1:exp7 0.645428242154021 0.571825930080392 1.12871454091507 0.259576266466224 df.mm.trans2:exp7 -0.00256296679199706 0.571825930080392 -0.00448207515115087 0.996425676341872 df.mm.trans1:exp8 0.379968262296647 0.571825930080392 0.664482392820535 0.506697409503201 df.mm.trans2:exp8 0.456788918916604 0.571825930080392 0.798825122974722 0.424782825161423 df.mm.trans1:probe2 0.26821786569759 0.391502451089253 0.685098815987853 0.493608857022767 df.mm.trans1:probe3 -0.0949147784142656 0.391502451089253 -0.242437252053442 0.808543857469751 df.mm.trans1:probe4 0.695359317048937 0.391502451089253 1.77613017521163 0.076338330874104 . df.mm.trans1:probe5 0.504645381839994 0.391502451089253 1.28899673663843 0.198013674772905 df.mm.trans1:probe6 0.437009134538723 0.391502451089253 1.11623601160825 0.26487383885539 df.mm.trans2:probe2 -0.0192893160154890 0.391502451089253 -0.0492699750967626 0.960724429938257 df.mm.trans2:probe3 0.363535910164491 0.391502451089253 0.928566115366704 0.353575882079367 df.mm.trans2:probe4 0.210764256452221 0.391502451089253 0.53834722072831 0.590584331337904 df.mm.trans2:probe5 -0.191006946481892 0.391502451089253 -0.487881866257707 0.62585399454908 df.mm.trans2:probe6 0.135054223094424 0.391502451089253 0.344963927348784 0.730271037017066 df.mm.trans3:probe2 0.723177776323802 0.391502451089253 1.8471858204508 0.0653290686187772 . df.mm.trans3:probe3 -0.372191849953584 0.391502451089253 -0.950675657120555 0.342242547041081 df.mm.trans3:probe4 -0.0331090778785178 0.391502451089253 -0.0845692735419676 0.932638724051532 df.mm.trans3:probe5 0.0306458556795735 0.391502451089253 0.078277557635487 0.937639552939328 df.mm.trans3:probe6 0.228779105735814 0.391502451089253 0.584361873340247 0.5592485802676 df.mm.trans3:probe7 -0.160164606159956 0.391502451089253 -0.409102435283203 0.682645084073182 df.mm.trans3:probe8 -0.129507885152707 0.391502451089253 -0.3307971247495 0.740940594192834 df.mm.trans3:probe9 0.292526455662203 0.391502451089253 0.747189333932201 0.455311364103602 df.mm.trans3:probe10 -0.324575147495747 0.391502451089253 -0.829050103243801 0.407483880688813