chr14.7316_chr14_46752103_46760372_-_0.R fitVsDatCorrelation=0.945001635368277 cont.fitVsDatCorrelation=0.341796657437548 fstatistic=8204.49581495486,38,370 cont.fstatistic=985.18727237062,38,370 residuals=-0.891303450658913,-0.07581623727424,-0.000194362886833931,0.0783145821496572,0.740653165775088 cont.residuals=-0.796706739620444,-0.304352986706983,-0.0417283739775606,0.200280013404065,1.51906190934486 predictedValues: Include Exclude Both chr14.7316_chr14_46752103_46760372_-_0.R.tl.Lung 49.8856925434278 89.059163780896 104.435791469020 chr14.7316_chr14_46752103_46760372_-_0.R.tl.cerebhem 47.3374054602903 83.1333730879063 110.567537109535 chr14.7316_chr14_46752103_46760372_-_0.R.tl.cortex 48.9569480517115 102.701958981046 120.263365810063 chr14.7316_chr14_46752103_46760372_-_0.R.tl.heart 50.0672994288178 92.7651688830583 110.583866134625 chr14.7316_chr14_46752103_46760372_-_0.R.tl.kidney 55.1704683756762 98.3790168182555 107.137929836280 chr14.7316_chr14_46752103_46760372_-_0.R.tl.liver 50.7275123840031 75.1857688305052 91.9147826039662 chr14.7316_chr14_46752103_46760372_-_0.R.tl.stomach 48.8184425912243 81.346539600855 101.377828730045 chr14.7316_chr14_46752103_46760372_-_0.R.tl.testicle 47.5267825870302 92.57248785556 108.654176553032 diffExp=-39.1734712374682,-35.795967627616,-53.7450109293342,-42.6978694542405,-43.2085484425793,-24.4582564465021,-32.5280970096307,-45.0457052685297 diffExpScore=0.996851910003528 diffExp1.5=-1,-1,-1,-1,-1,0,-1,-1 diffExp1.5Score=0.875 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 71.5392650558701 72.0675169117152 89.8928607349433 cerebhem 78.0371183449815 64.6669546388327 63.9001464711036 cortex 87.9520014715677 63.6339422455278 63.1989612760029 heart 92.1705996962357 64.2635627919611 87.7457362132231 kidney 77.6623152053351 55.6235725549424 93.7298751311848 liver 65.2522063513574 70.9640035761074 79.6971154759779 stomach 72.101621012496 63.944810534552 64.0203452651434 testicle 86.1270633351833 85.062356043417 84.7612074115208 cont.diffExp=-0.528251855845141,13.3701637061488,24.3180592260399,27.9070369042745,22.0387426503927,-5.71179722475006,8.156810477944,1.06470729176624 cont.diffExpScore=1.12530741821040 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,1,0,0,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,1,1,1,0,0,0 cont.diffExp1.3Score=0.75 cont.diffExp1.2=0,1,1,1,1,0,0,0 cont.diffExp1.2Score=0.8 tran.correlation=0.258260862663999 cont.tran.correlation=0.0167166206978774 tran.covariance=0.00119059806138417 cont.tran.covariance=-0.000232953957626928 tran.mean=69.6021268287664 cont.tran.mean=73.1918068606302 weightedLogRatios: wLogRatio Lung -2.43390042225389 cerebhem -2.3307876885114 cortex -3.15721799066967 heart -2.60354779276788 kidney -2.48690344752709 liver -1.62245860279547 stomach -2.11566877675002 testicle -2.79656238597859 cont.weightedLogRatios: wLogRatio Lung -0.0314430688052779 cerebhem 0.801204644155499 cortex 1.39651480099824 heart 1.56641036522426 kidney 1.39696147548873 liver -0.354130576991266 stomach 0.506402661543495 testicle 0.0553490639126727 varWeightedLogRatios=0.20798913774859 cont.varWeightedLogRatios=0.546060577016041 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.26461943932135 0.0828921856638122 51.4477861232597 1.10922127493506e-170 *** df.mm.trans1 -0.333340286512672 0.0682650149894496 -4.88303249569622 1.55709298891972e-06 *** df.mm.trans2 0.311276792263313 0.0682650149894497 4.55982895940798 6.9692838242182e-06 *** df.mm.exp2 -0.178342213619584 0.0933163812966172 -1.91115655302472 0.056756889106181 . df.mm.exp3 -0.0173742634055709 0.0933163812966173 -0.186186639089066 0.852400436047678 df.mm.exp4 -0.0127975823004345 0.0933163812966172 -0.137141862153397 0.890993258448983 df.mm.exp5 0.174675583639142 0.0933163812966172 1.87186409515726 0.0620141300478982 . df.mm.exp6 -0.0248941916556873 0.0933163812966172 -0.266771935535714 0.789793379982896 df.mm.exp7 -0.082490659338647 0.0933163812966172 -0.883989050930303 0.377276161655295 df.mm.exp8 -0.0493474628715618 0.0933163812966173 -0.528818865304099 0.597248186161278 df.mm.trans1:exp2 0.125908770635399 0.0773738558886544 1.62727796345821 0.104529322866176 df.mm.trans2:exp2 0.109487525940726 0.0773738558886544 1.41504549157128 0.157896219976978 df.mm.trans1:exp3 -0.00141867494650690 0.0773738558886544 -0.0183353269681746 0.985381228442281 df.mm.trans2:exp3 0.159904544490128 0.0773738558886544 2.06664825804003 0.0394625711640122 * df.mm.trans1:exp4 0.0164314322062306 0.0773738558886544 0.212364137957353 0.831939903744468 df.mm.trans2:exp4 0.0535679058656584 0.0773738558886544 0.692325660268836 0.489167095706676 df.mm.trans1:exp5 -0.0739820057783836 0.0773738558886544 -0.956162839872529 0.339614276573764 df.mm.trans2:exp5 -0.075148956496656 0.0773738558886544 -0.971244816915933 0.332060870288668 df.mm.trans1:exp6 0.0416283665752017 0.0773738558886544 0.538015924075277 0.590889527544917 df.mm.trans2:exp6 -0.144444750031803 0.0773738558886545 -1.86684182108835 0.0627143767385991 . df.mm.trans1:exp7 0.0608645836864547 0.0773738558886544 0.78662983752603 0.432002118839996 df.mm.trans2:exp7 -0.00809195553466178 0.0773738558886545 -0.10458255494345 0.916763726005453 df.mm.trans1:exp8 0.000906619881270963 0.0773738558886544 0.0117173930503818 0.990657402192465 df.mm.trans2:exp8 0.0880385425280569 0.0773738558886545 1.13783320628029 0.255926394075092 df.mm.trans1:probe2 -0.055158314864394 0.0451765988362675 -1.22094881609621 0.222882862215661 df.mm.trans1:probe3 -0.0201229637073871 0.0451765988362675 -0.445428921737077 0.656270312932988 df.mm.trans1:probe4 -0.0197813730864866 0.0451765988362675 -0.437867692479015 0.661737697712114 df.mm.trans1:probe5 -0.0339747432315332 0.0451765988362675 -0.752042962655668 0.452503352770421 df.mm.trans1:probe6 -0.107956656256551 0.0451765988362675 -2.38965878435903 0.0173639667746863 * df.mm.trans2:probe2 -0.135714098517328 0.0451765988362675 -3.00407959016998 0.00284518771264797 ** df.mm.trans2:probe3 0.0163017500280405 0.0451765988362675 0.360845004891196 0.71842124733597 df.mm.trans2:probe4 -0.284345764344929 0.0451765988362675 -6.29409410335374 8.75327253191157e-10 *** df.mm.trans2:probe5 -0.247614292374758 0.0451765988362675 -5.48102997465969 7.83846284665469e-08 *** df.mm.trans2:probe6 -0.30117612717186 0.0451765988362675 -6.66664013958655 9.5336570967865e-11 *** df.mm.trans3:probe2 0.062259905813504 0.0451765988362675 1.37814504449862 0.168991327212614 df.mm.trans3:probe3 0.410943027906173 0.0451765988362675 9.09636932597657 5.83594704487793e-18 *** df.mm.trans3:probe4 1.33310633644651 0.0451765988362675 29.5087804479938 3.00952532960836e-99 *** df.mm.trans3:probe5 0.223773238767543 0.0451765988362675 4.95329981742448 1.11184219659301e-06 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.09391600502049 0.238178256707243 17.1884539823991 4.30754665361554e-49 *** df.mm.trans1 0.217121406994921 0.196149276727048 1.10691923323815 0.269047971460958 df.mm.trans2 0.137291245223126 0.196149276727048 0.699932457126385 0.484409320450332 df.mm.exp2 0.319881909534833 0.268130618603772 1.19300776315866 0.233630781461362 df.mm.exp3 0.434419023262991 0.268130618603772 1.62017685829812 0.106046218303400 df.mm.exp4 0.162959378763699 0.268130618603772 0.607761171075024 0.543718725565061 df.mm.exp5 -0.218671112555897 0.268130618603772 -0.815539507179659 0.415288232212010 df.mm.exp6 0.0129678729977628 0.268130618603772 0.0483640140215615 0.961452233536602 df.mm.exp7 0.227664625032723 0.268130618603772 0.84908104198705 0.396385212862686 df.mm.exp8 0.410138946011899 0.268130618603772 1.52962368918403 0.126964363458873 df.mm.trans1:exp2 -0.232943780407170 0.222322164178650 -1.04777578640331 0.295425870255657 df.mm.trans2:exp2 -0.428235000474008 0.222322164178650 -1.92619121919799 0.0548463065615176 . df.mm.trans1:exp3 -0.227874255999663 0.222322164178650 -1.02497318178565 0.306045477768005 df.mm.trans2:exp3 -0.558875426671616 0.222322164178650 -2.5138088626311 0.0123673571154862 * df.mm.trans1:exp4 0.0904353650488658 0.222322164178650 0.406776199678389 0.68440756722851 df.mm.trans2:exp4 -0.277569997729579 0.222322164178650 -1.24850348931713 0.212636141592726 df.mm.trans1:exp5 0.300794787898313 0.222322164178650 1.35296806330387 0.176891951157558 df.mm.trans2:exp5 -0.040325223722895 0.222322164178650 -0.181381932259760 0.856167119392069 df.mm.trans1:exp6 -0.104954474139191 0.222322164178650 -0.47208281966369 0.637145968083411 df.mm.trans2:exp6 -0.0283985309084033 0.222322164178650 -0.127735941278366 0.898427341081989 df.mm.trans1:exp7 -0.219834558744735 0.222322164178650 -0.988810807761317 0.323401898747999 df.mm.trans2:exp7 -0.347247663598038 0.222322164178650 -1.56191203374128 0.119163589443349 df.mm.trans1:exp8 -0.224561720103812 0.222322164178650 -1.01007347123233 0.313120170775121 df.mm.trans2:exp8 -0.244357772466424 0.222322164178650 -1.09911566113610 0.272432274306157 df.mm.trans1:probe2 -0.171245323700734 0.129808177557588 -1.31921830290517 0.187911942266934 df.mm.trans1:probe3 -0.045070363765499 0.129808177557588 -0.347207430329296 0.7286328949575 df.mm.trans1:probe4 -0.0623173189550639 0.129808177557588 -0.48007236622221 0.631459618508898 df.mm.trans1:probe5 -0.00656226237952922 0.129808177557588 -0.0505535360175437 0.959708567805154 df.mm.trans1:probe6 -0.163505196917626 0.129808177557588 -1.25959088243951 0.208610947479354 df.mm.trans2:probe2 0.124120245655105 0.129808177557588 0.956182021737733 0.339604600121705 df.mm.trans2:probe3 0.169445113289752 0.129808177557588 1.30535006713718 0.192584799755133 df.mm.trans2:probe4 0.073514115747812 0.129808177557588 0.566328848698292 0.571513590418801 df.mm.trans2:probe5 0.0891357353406483 0.129808177557588 0.68667272754141 0.492719102488469 df.mm.trans2:probe6 0.0541425968122376 0.129808177557588 0.417096964389766 0.676849379386215 df.mm.trans3:probe2 0.08774573595073 0.129808177557588 0.675964624122412 0.499485387626496 df.mm.trans3:probe3 -0.12506504993931 0.129808177557588 -0.963460486792726 0.335945733267136 df.mm.trans3:probe4 0.17485971324261 0.129808177557588 1.34706238491821 0.178784563599332 df.mm.trans3:probe5 0.113908939152032 0.129808177557588 0.877517436075999 0.380775080290513