chr12.5880_chr12_104790318_104813269_+_2.R fitVsDatCorrelation=0.921664733760001 cont.fitVsDatCorrelation=0.264707731369931 fstatistic=5542.54823559406,36,324 cont.fstatistic=889.667195050202,36,324 residuals=-0.672433417425375,-0.0881327950740863,0.00800892972841049,0.0960805072221079,0.532700073884382 cont.residuals=-0.721550911286418,-0.315482314018546,-0.110352231547598,0.263815073768244,1.68429624404187 predictedValues: Include Exclude Both chr12.5880_chr12_104790318_104813269_+_2.R.tl.Lung 110.883030167898 51.4427669748945 68.804568828662 chr12.5880_chr12_104790318_104813269_+_2.R.tl.cerebhem 92.3950259416134 66.4784738037015 59.6745328238144 chr12.5880_chr12_104790318_104813269_+_2.R.tl.cortex 197.166367270977 50.9912897120692 115.050928214889 chr12.5880_chr12_104790318_104813269_+_2.R.tl.heart 133.263209299888 51.9502181856112 83.2789022302358 chr12.5880_chr12_104790318_104813269_+_2.R.tl.kidney 93.4845256483188 51.1207964405426 67.6970967702194 chr12.5880_chr12_104790318_104813269_+_2.R.tl.liver 83.9578128102998 58.003156371891 66.5207396273319 chr12.5880_chr12_104790318_104813269_+_2.R.tl.stomach 96.5534245262007 55.3213566142428 70.7786446877893 chr12.5880_chr12_104790318_104813269_+_2.R.tl.testicle 101.338591895108 55.1210255746699 69.6657949178635 diffExp=59.4402631930033,25.9165521379119,146.175077558908,81.3129911142766,42.3637292077762,25.9546564384089,41.2320679119579,46.2175663204384 diffExpScore=0.99787058662202 diffExp1.5=1,0,1,1,1,0,1,1 diffExp1.5Score=0.857142857142857 diffExp1.4=1,0,1,1,1,1,1,1 diffExp1.4Score=0.875 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 65.411425188141 75.9840980605966 83.2801528913932 cerebhem 65.260800679893 84.6830026164587 65.1799319403711 cortex 77.5420433050072 66.5324352953871 76.3090203169746 heart 63.4684377012576 75.4067163363934 73.2441881933961 kidney 72.9533157254688 79.4449109769889 75.8027780457052 liver 73.9710148829196 74.025827512362 63.2401827878488 stomach 77.2451053022207 70.5523924984812 77.6458749525522 testicle 82.6256054131419 85.1687935698819 77.3936237762724 cont.diffExp=-10.5726728724556,-19.4222019365657,11.0096080096201,-11.9382786351358,-6.49159525152004,-0.0548126294422957,6.6927128037395,-2.54318815674002 cont.diffExpScore=2.00245372687599 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=-0.475128131592329 cont.tran.correlation=-0.123348876655424 tran.covariance=-0.0131719997449987 cont.tran.covariance=-0.00131048886447791 tran.mean=84.3419419523704 cont.tran.mean=74.3922453165375 weightedLogRatios: wLogRatio Lung 3.32122108467998 cerebhem 1.43577577505923 cortex 6.2316261353273 heart 4.16504835908376 kidney 2.55686496696477 liver 1.57002335084406 stomach 2.39016820724508 testicle 2.62694977091309 cont.weightedLogRatios: wLogRatio Lung -0.637605960701859 cerebhem -1.12250474756833 cortex 0.654519674995272 heart -0.730213902951876 kidney -0.369315151681152 liver -0.00318812156812961 stomach 0.389851547120398 testicle -0.134281682269037 varWeightedLogRatios=2.44170174775102 cont.varWeightedLogRatios=0.351133983214389 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.64882816960971 0.101129054248480 45.9692637705012 5.12624787806024e-144 *** df.mm.trans1 0.146915174555778 0.0829000311307807 1.77219685628355 0.0773015986569096 . df.mm.trans2 -0.714146979172352 0.084844349709469 -8.4171424687418 1.25915511156086e-15 *** df.mm.exp2 0.216370412824340 0.117436889298599 1.84243991914831 0.0663243718912746 . df.mm.exp3 0.0526522379491686 0.117436889298599 0.448344964377361 0.654203926911766 df.mm.exp4 0.00274128263135446 0.117436889298599 0.0233426025478619 0.981391358298563 df.mm.exp5 -0.160731566082422 0.117436889298599 -1.36866334796846 0.172052731930377 df.mm.exp6 -0.124377481741539 0.117436889298599 -1.05910061552543 0.290342883378964 df.mm.exp7 -0.0939774018945657 0.117436889298599 -0.800237493140808 0.424159563765153 df.mm.exp8 -0.0333864943485746 0.117436889298599 -0.284293074756816 0.776367397302201 df.mm.trans1:exp2 -0.398773130848643 0.0965325283649053 -4.13097157614301 4.60253397054653e-05 *** df.mm.trans2:exp2 0.0400379114157009 0.100319546226660 0.399103793045875 0.690079652110692 df.mm.trans1:exp3 0.522919774887376 0.0965325283649053 5.41703178964372 1.18370993927140e-07 *** df.mm.trans2:exp3 -0.0614672785894592 0.100319546226660 -0.612714878619779 0.540494691474801 df.mm.trans1:exp4 0.181109043785615 0.0965325283649053 1.87614524195409 0.0615341674778128 . df.mm.trans2:exp4 0.00707476600165737 0.100319546226660 0.07052230864036 0.943821452852978 df.mm.trans1:exp5 -0.00994837582948997 0.0965325283649053 -0.103057238818855 0.917981299469156 df.mm.trans2:exp5 0.154453087034235 0.100319546226660 1.53961110116334 0.124631211426056 df.mm.trans1:exp6 -0.153783937445146 0.0965325283649053 -1.59307893463458 0.112117548713438 df.mm.trans2:exp6 0.244405042193325 0.100319546226660 2.43626542768766 0.0153781239869413 * df.mm.trans1:exp7 -0.044401984341705 0.0965325283649053 -0.459969142980072 0.645846879674202 df.mm.trans2:exp7 0.166666562605550 0.100319546226660 1.66135682301619 0.0976090614482963 . df.mm.trans1:exp8 -0.0566220639802556 0.0965325283649053 -0.586559421361232 0.557908081429333 df.mm.trans2:exp8 0.102447858278759 0.100319546226660 1.02121532774172 0.30791432976053 df.mm.trans1:probe2 -0.376028888452995 0.0528730433184659 -7.11192064712619 7.36450355014793e-12 *** df.mm.trans1:probe3 0.352151590897321 0.0528730433184659 6.66032383981067 1.17193037882936e-10 *** df.mm.trans1:probe4 -0.521430729340706 0.0528730433184659 -9.86193902628254 3.10334058315523e-20 *** df.mm.trans1:probe5 -0.240099299792878 0.0528730433184659 -4.54105314775825 7.90440807910249e-06 *** df.mm.trans2:probe2 0.208656746404293 0.0528730433184659 3.94637292102722 9.7331489607027e-05 *** df.mm.trans2:probe3 0.0936577574869625 0.0528730433184659 1.77137065711995 0.0774390676156365 . df.mm.trans2:probe4 -0.0235253581172837 0.0528730433184659 -0.444940495964746 0.656659852065654 df.mm.trans2:probe5 -0.109563493295551 0.0528730433184659 -2.07219948803828 0.039037511028005 * df.mm.trans2:probe6 -0.111338868662789 0.0528730433184659 -2.10577756971867 0.03599280756446 * df.mm.trans3:probe2 -0.297151828785127 0.0528730433184659 -5.62010071928935 4.1179148256519e-08 *** df.mm.trans3:probe3 0.291495030863019 0.0528730433184659 5.51311240223644 7.20941579837863e-08 *** df.mm.trans3:probe4 0.604351938460624 0.0528730433184659 11.4302468806359 1.19777164145389e-25 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.18868339469071 0.25135270324146 16.6645647358202 1.82187234586232e-45 *** df.mm.trans1 -0.0397984201912526 0.206045108187453 -0.193153919262404 0.846959450408753 df.mm.trans2 0.225234168413109 0.210877643548805 1.06807988093333 0.286279622172472 df.mm.exp2 0.351144072520828 0.29188525300497 1.20302094369546 0.229846548430010 df.mm.exp3 0.124707945611434 0.291885253004970 0.427249901553985 0.669481110049023 df.mm.exp4 0.0906294202595157 0.29188525300497 0.310496742560586 0.756382876626604 df.mm.exp5 0.247737859642475 0.29188525300497 0.848750860456306 0.396646573985563 df.mm.exp6 0.372136713285737 0.29188525300497 1.27494181173792 0.203243340296301 df.mm.exp7 0.162169954779741 0.29188525300497 0.555594889122335 0.578871250084732 df.mm.exp8 0.421039559976897 0.29188525300497 1.4424831526851 0.150132103941957 df.mm.trans1:exp2 -0.353449452626793 0.239928200016925 -1.47314676891612 0.141682271020960 df.mm.trans2:exp2 -0.242753250841507 0.249340699558718 -0.973580531662625 0.330991146857412 df.mm.trans1:exp3 0.0454153976374399 0.239928200016926 0.189287451972032 0.849986049626126 df.mm.trans2:exp3 -0.257542450406228 0.249340699558718 -1.03289375084784 0.302423983421933 df.mm.trans1:exp4 -0.120783622274679 0.239928200016925 -0.50341569797197 0.615014112105917 df.mm.trans2:exp4 -0.0982571554817906 0.249340699558718 -0.39406785837886 0.693790170372494 df.mm.trans1:exp5 -0.138615073950006 0.239928200016926 -0.577735647332109 0.563843885771381 df.mm.trans2:exp5 -0.203198104212942 0.249340699558718 -0.814941582230903 0.41570436537008 df.mm.trans1:exp6 -0.249160327855564 0.239928200016925 -1.03847871087261 0.299821607917563 df.mm.trans2:exp6 -0.398246742886343 0.249340699558718 -1.59719910785186 0.111196131739374 df.mm.trans1:exp7 0.00411665693534781 0.239928200016926 0.0171578702922683 0.986321232607056 df.mm.trans2:exp7 -0.236338447307018 0.249340699558718 -0.947853470072431 0.343910464376814 df.mm.trans1:exp8 -0.187416874864428 0.239928200016925 -0.78113733546622 0.435292100323724 df.mm.trans2:exp8 -0.306928548238442 0.249340699558718 -1.23096048411528 0.219230470603505 df.mm.trans1:probe2 -0.00360571179991392 0.131414087330881 -0.0274377874788665 0.978127451461432 df.mm.trans1:probe3 0.00600019570949305 0.131414087330882 0.0456586948276362 0.96361041439742 df.mm.trans1:probe4 0.243840212010897 0.131414087330881 1.85551044765043 0.0644313649212848 . df.mm.trans1:probe5 0.0400729960303532 0.131414087330882 0.304936836257556 0.760610048293164 df.mm.trans2:probe2 -0.265454483040158 0.131414087330881 -2.01998498358690 0.0442076336317087 * df.mm.trans2:probe3 -0.0590231167088337 0.131414087330882 -0.44913842882173 0.653632073997823 df.mm.trans2:probe4 -0.193483543179998 0.131414087330882 -1.47231965088214 0.141905275243426 df.mm.trans2:probe5 -0.192644158917945 0.131414087330881 -1.4659323275814 0.143636531947953 df.mm.trans2:probe6 -0.123329505704917 0.131414087330881 -0.938480099126599 0.348696805351099 df.mm.trans3:probe2 0.0106947906536776 0.131414087330882 0.0813823758996983 0.935188113346486 df.mm.trans3:probe3 0.0968064052804484 0.131414087330881 0.736651657722996 0.461867258948114 df.mm.trans3:probe4 0.0848632731224216 0.131414087330882 0.645769984375786 0.518885411041765