chr3.15226_chr3_143039973_143044336_+_1.R fitVsDatCorrelation=0.830450116008823 cont.fitVsDatCorrelation=0.298268682855780 fstatistic=8713.14366243678,41,439 cont.fstatistic=2961.15163388824,41,439 residuals=-0.416629287072071,-0.0879960047707991,-0.0112784384877633,0.0750223170254007,0.83396001392572 cont.residuals=-0.598098310347566,-0.185563333524546,0.000334135850940374,0.147448811924382,1.25259983125847 predictedValues: Include Exclude Both chr3.15226_chr3_143039973_143044336_+_1.R.tl.Lung 75.290914209234 82.6009524007315 74.2888890858707 chr3.15226_chr3_143039973_143044336_+_1.R.tl.cerebhem 81.7646324091685 80.4971313378813 58.5910081294445 chr3.15226_chr3_143039973_143044336_+_1.R.tl.cortex 65.6387653965831 72.6112213519978 56.1432179480692 chr3.15226_chr3_143039973_143044336_+_1.R.tl.heart 64.770820913658 83.7017615346953 63.7875181708326 chr3.15226_chr3_143039973_143044336_+_1.R.tl.kidney 77.5131680051661 78.1161477519424 60.2622527600385 chr3.15226_chr3_143039973_143044336_+_1.R.tl.liver 71.1138777254205 80.002189825447 54.8499343828861 chr3.15226_chr3_143039973_143044336_+_1.R.tl.stomach 74.4913206440711 87.0126515073516 57.3278855013286 chr3.15226_chr3_143039973_143044336_+_1.R.tl.testicle 64.4722171769639 77.591195994633 56.0154763834496 diffExp=-7.31003819149745,1.26750107128727,-6.9724559554147,-18.9309406210374,-0.602979746776256,-8.88831210002648,-12.5213308632805,-13.1189788176692 diffExpScore=1.02254785132150 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=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,0,0,-1,0,0,0,-1 diffExp1.2Score=0.666666666666667 cont.predictedValues: Include Exclude Both Lung 69.6060010585677 72.9064171836631 75.1737630649352 cerebhem 77.909117943182 62.4646215902072 70.0308502360221 cortex 69.5296751422499 67.6606243487135 68.1580937628927 heart 68.185648143788 75.5395241584937 72.1680516702661 kidney 73.0358311618939 71.2405015999506 76.9327415328016 liver 75.0437893225106 76.5140995113773 62.7113519016097 stomach 74.9420572812392 76.3887399601676 68.0541156458066 testicle 66.7469300831959 75.6399801256096 75.5607577028689 cont.diffExp=-3.30041612509538,15.4444963529748,1.86905079353635,-7.35387601470563,1.79532956194330,-1.47031018886670,-1.44668267892835,-8.89305004241375 cont.diffExpScore=9.54508308845817 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=0,1,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.299272896387055 cont.tran.correlation=-0.394119624133357 tran.covariance=0.00156503228257948 cont.tran.covariance=-0.00157507375944090 tran.mean=76.0743105115591 cont.tran.mean=72.0845974134256 weightedLogRatios: wLogRatio Lung -0.40471780594887 cerebhem 0.068680260272685 cortex -0.427499981709725 heart -1.10229907545994 kidney -0.0337414746115035 liver -0.509146024648234 stomach -0.6818247431564 testicle -0.788821319397118 cont.weightedLogRatios: wLogRatio Lung -0.197626825447081 cerebhem 0.937917387354215 cortex 0.115213348226358 heart -0.437694418877504 kidney 0.106486273363591 liver -0.0839727846965171 stomach -0.0827186308013444 testicle -0.533257734754028 varWeightedLogRatios=0.147519439036957 cont.varWeightedLogRatios=0.204190868874197 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.32613489284599 0.0793523717822689 54.5180288336719 1.4375827172809e-197 *** df.mm.trans1 -0.0902202939915924 0.0640254507923158 -1.40913172613570 0.159504153787045 df.mm.trans2 0.131123421225641 0.0640254507923158 2.04798903565671 0.0411554743898210 * df.mm.exp2 0.294065814063372 0.0862428523529902 3.40974128336766 0.000710333039328957 *** df.mm.exp3 0.0139607642264512 0.0862428523529902 0.161877348041668 0.871476917621292 df.mm.exp4 0.0151384215083999 0.0862428523529902 0.175532477131423 0.860742188589584 df.mm.exp5 0.182519429797113 0.0862428523529902 2.11634268600098 0.0348778685118422 * df.mm.exp6 0.214316242744254 0.0862428523529902 2.48503194058404 0.0133254632488166 * df.mm.exp7 0.300529703850717 0.0862428523529902 3.48469114426614 0.000542220281236138 *** df.mm.exp8 0.0646410623670847 0.0862428523529902 0.749523706643075 0.453943068149855 df.mm.trans1:exp2 -0.211580496881902 0.0687979961876914 -3.07538749100595 0.00223359091322664 ** df.mm.trans2:exp2 -0.319865476563745 0.0687979961876914 -4.64934292113833 4.41164464254653e-06 *** df.mm.trans1:exp3 -0.151153773180506 0.0687979961876915 -2.19706650711360 0.0285375553179565 * df.mm.trans2:exp3 -0.142862500998051 0.0687979961876914 -2.07655031998753 0.0384242873255516 * df.mm.trans1:exp4 -0.165642680399263 0.0687979961876915 -2.4076672225651 0.0164663903932224 * df.mm.trans2:exp4 -0.00189960915533073 0.0687979961876914 -0.0276114023749806 0.977984634510663 df.mm.trans1:exp5 -0.153431064420503 0.0687979961876915 -2.23016763456191 0.0262411282102206 * df.mm.trans2:exp5 -0.238343847671268 0.0687979961876914 -3.46440101280028 0.000583625952917193 *** df.mm.trans1:exp6 -0.271393205263575 0.0687979961876914 -3.94478357368394 9.29626614182993e-05 *** df.mm.trans2:exp6 -0.246283446362573 0.0687979961876914 -3.57980551774611 0.000382217119055613 *** df.mm.trans1:exp7 -0.311206552967629 0.0687979961876915 -4.52348280782205 7.83928537749882e-06 *** df.mm.trans2:exp7 -0.24849738687947 0.0687979961876914 -3.6119858229814 0.000338972348079645 *** df.mm.trans1:exp8 -0.219766139097266 0.0687979961876915 -3.19436831412517 0.00150233822007869 ** df.mm.trans2:exp8 -0.127208306027335 0.0687979961876914 -1.84901178924298 0.0651282145960285 . df.mm.trans1:probe2 0.0830997243059327 0.0450388607416256 1.84506719170031 0.0657011017418574 . df.mm.trans1:probe3 0.467497309756854 0.0450388607416256 10.3798653442578 1.01629943293516e-22 *** df.mm.trans1:probe4 0.0810675972019039 0.0450388607416256 1.79994777547692 0.0725553125586605 . df.mm.trans1:probe5 0.181439018810699 0.0450388607416256 4.02849929645334 6.61485800338779e-05 *** df.mm.trans1:probe6 0.383124494075521 0.0450388607416256 8.50653164327114 2.84791789905624e-16 *** df.mm.trans2:probe2 -0.0365030709327811 0.0450388607416256 -0.810479446675799 0.418103808313672 df.mm.trans2:probe3 -0.236079417619112 0.0450388607416256 -5.24168270981428 2.47725190168053e-07 *** df.mm.trans2:probe4 -0.0437156213315161 0.0450388607416256 -0.97062005147731 0.332271982474382 df.mm.trans2:probe5 -0.0555156906051471 0.0450388607416256 -1.23261755939219 0.218378179026289 df.mm.trans2:probe6 -0.233505646214999 0.0450388607416256 -5.18453713903979 3.3112481060164e-07 *** df.mm.trans3:probe2 -0.222291885329662 0.0450388607416256 -4.93555746458339 1.13698501958970e-06 *** df.mm.trans3:probe3 -0.107891217229336 0.0450388607416256 -2.39551390627474 0.0170150400616680 * df.mm.trans3:probe4 0.0834467845752685 0.0450388607416256 1.85277298762013 0.0645858196753805 . df.mm.trans3:probe5 -0.117816485367745 0.0450388607416256 -2.61588511404901 0.00920634756376789 ** df.mm.trans3:probe6 -0.192661152078725 0.0450388607416256 -4.2776648633269 2.31966556028181e-05 *** df.mm.trans3:probe7 0.354515133107272 0.0450388607416256 7.87131662012987 2.76846750896855e-14 *** df.mm.trans3:probe8 -0.269914143906587 0.0450388607416256 -5.99291677147437 4.30122789239444e-09 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.27420024099183 0.135956487094642 31.4380014689294 1.82597126759624e-114 *** df.mm.trans1 0.00177202070191131 0.109696473827631 0.0161538529004655 0.98711898949172 df.mm.trans2 0.0316912138145897 0.109696473827631 0.288899111418905 0.772794954058805 df.mm.exp2 0.0289822986757031 0.147762127074246 0.19614159087694 0.844590104452968 df.mm.exp3 0.0222029444997205 0.147762127074246 0.150261402832705 0.880627396258842 df.mm.exp4 0.0556674992531613 0.147762127074246 0.376737262486687 0.706550894936212 df.mm.exp5 0.00185493097429664 0.147762127074246 0.0125534939908154 0.989989726859799 df.mm.exp6 0.304779176250037 0.147762127074246 2.06263392578867 0.0397351068553007 * df.mm.exp7 0.220022167540142 0.147762127074246 1.48902950909462 0.137197614903096 df.mm.exp8 -0.0102689578292270 0.147762127074246 -0.069496548490177 0.944626024407036 df.mm.trans1:exp2 0.083709908389662 0.117873400261983 0.71016792765467 0.477977072377212 df.mm.trans2:exp2 -0.183558619110582 0.117873400261983 -1.55725226134656 0.120131192300596 df.mm.trans1:exp3 -0.0233000883244856 0.117873400261983 -0.197670452135081 0.843394403041462 df.mm.trans2:exp3 -0.0968752158035044 0.117873400261983 -0.821858159586398 0.411603755681685 df.mm.trans1:exp4 -0.0762841800525684 0.117873400261983 -0.64717043780039 0.517859892870935 df.mm.trans2:exp4 -0.0201881435390604 0.117873400261983 -0.171269713898052 0.86409060771757 df.mm.trans1:exp5 0.0462444418574516 0.117873400261983 0.392322964762784 0.695009999224631 df.mm.trans2:exp5 -0.0249700939412941 0.117873400261983 -0.211838242434646 0.832331545553921 df.mm.trans1:exp6 -0.229558161188125 0.117873400261983 -1.94749757517738 0.0521122603854453 . df.mm.trans2:exp6 -0.256480807412979 0.117873400261983 -2.17590064291799 0.0300953162179403 * df.mm.trans1:exp7 -0.146157707902304 0.117873400261983 -1.23995496505112 0.21565441895467 df.mm.trans2:exp7 -0.173363527301074 0.117873400261983 -1.47076038288332 0.142072312057358 df.mm.trans1:exp8 -0.0316735229403464 0.117873400261983 -0.268707977117394 0.788280642969055 df.mm.trans2:exp8 0.0470772765185229 0.117873400261983 0.399388466048233 0.689801217230445 df.mm.trans1:probe2 -0.0974130235867656 0.077166254160338 -1.26237854418018 0.207482796497207 df.mm.trans1:probe3 -0.131948773362926 0.077166254160338 -1.70992844992526 0.0879857022772113 . df.mm.trans1:probe4 -0.00706938158645874 0.077166254160338 -0.0916123461399306 0.927047829951158 df.mm.trans1:probe5 -0.097324483598539 0.077166254160338 -1.26123115159012 0.207895380904248 df.mm.trans1:probe6 -0.129945001367161 0.077166254160338 -1.68396150339445 0.092899945268647 . df.mm.trans2:probe2 -0.0119321381276904 0.077166254160338 -0.154628966476687 0.877184896776349 df.mm.trans2:probe3 -0.0642802036649279 0.077166254160338 -0.833009252093083 0.405292471004606 df.mm.trans2:probe4 -0.000225307828934343 0.077166254160338 -0.0029197714906077 0.997671689014992 df.mm.trans2:probe5 -0.072468505504463 0.077166254160338 -0.939121722221816 0.348184664139928 df.mm.trans2:probe6 -0.0851009392471729 0.077166254160338 -1.10282584237338 0.270706995620524 df.mm.trans3:probe2 0.0257305768766491 0.077166254160338 0.333443383466372 0.73895882048881 df.mm.trans3:probe3 0.0364646540611902 0.077166254160338 0.472546639174982 0.636771490504793 df.mm.trans3:probe4 0.046258611081332 0.077166254160338 0.59946684706523 0.549170863511204 df.mm.trans3:probe5 0.0757822728552119 0.077166254160338 0.982064941207973 0.326608765378118 df.mm.trans3:probe6 0.0568333752289146 0.077166254160338 0.736505559941069 0.461816468016334 df.mm.trans3:probe7 -0.0533536147059494 0.077166254160338 -0.691411230031847 0.489672615457063 df.mm.trans3:probe8 -0.0906054821476912 0.077166254160338 -1.17415939303505 0.240967744358981