chr12.5660_chr12_25545036_25545896_+_1.R fitVsDatCorrelation=0.729733739817731 cont.fitVsDatCorrelation=0.269234044369928 fstatistic=4749.94691573474,37,347 cont.fstatistic=2389.43498222947,37,347 residuals=-0.794835696723917,-0.0947063854960009,-0.00441864045117889,0.0670983974218496,1.05544231710371 cont.residuals=-0.525447970725632,-0.145593784045162,-0.0290778238112452,0.106272696806978,1.45435614316853 predictedValues: Include Exclude Both chr12.5660_chr12_25545036_25545896_+_1.R.tl.Lung 56.6249707444857 64.4095860784607 54.8466936977236 chr12.5660_chr12_25545036_25545896_+_1.R.tl.cerebhem 70.7125255792568 107.079137992736 54.0847199868962 chr12.5660_chr12_25545036_25545896_+_1.R.tl.cortex 55.8920131645807 62.1414001623434 53.9071198488552 chr12.5660_chr12_25545036_25545896_+_1.R.tl.heart 61.0041428604758 63.7230002929195 57.9071731981787 chr12.5660_chr12_25545036_25545896_+_1.R.tl.kidney 59.3815627871051 66.2961528067122 57.8991824507985 chr12.5660_chr12_25545036_25545896_+_1.R.tl.liver 59.3378562702617 58.9097286284098 60.9556039454454 chr12.5660_chr12_25545036_25545896_+_1.R.tl.stomach 61.8645473199787 70.3321417961049 63.0704719251512 chr12.5660_chr12_25545036_25545896_+_1.R.tl.testicle 59.2303767388944 68.479892999838 55.2171459183656 diffExp=-7.78461533397505,-36.3666124134793,-6.24938699776269,-2.71885743244376,-6.91459001960713,0.428127641851923,-8.46759447612621,-9.24951626094354 diffExpScore=0.99816472002896 diffExp1.5=0,-1,0,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,-1,0,0,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=0,-1,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,-1,0,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 57.2330555366923 68.4546732693975 68.45545499397 cerebhem 61.2586254636288 60.8281848131897 59.5634066705425 cortex 62.4790976144281 64.1085413834301 60.355114675186 heart 73.6343257086242 67.14853777515 66.7408520507567 kidney 62.1621044420774 62.4877274003602 64.4567461377609 liver 59.1659501965718 62.6307570152149 70.8355874745744 stomach 60.607247293721 57.0067836549885 64.9348015111328 testicle 66.2874118620705 60.7790541168844 69.2333470311602 cont.diffExp=-11.2216177327052,0.430440650439117,-1.62944376900204,6.48578793347419,-0.325622958282807,-3.46480681864313,3.60046363873246,5.5083577451861 cont.diffExpScore=20.2089250182986 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=0,0,0,0,0,0,0,0 cont.diffExp1.2Score=0 tran.correlation=0.920841157762657 cont.tran.correlation=0.188774486145311 tran.covariance=0.0121624027120653 cont.tran.covariance=0.000747510791402822 tran.mean=65.3386897639102 cont.tran.mean=62.8920048466518 weightedLogRatios: wLogRatio Lung -0.528241167123124 cerebhem -1.853185966896 cortex -0.432063279510042 heart -0.180203295105498 kidney -0.455909277151735 liver 0.0295415532474177 stomach -0.537383043904767 testicle -0.602766986557788 cont.weightedLogRatios: wLogRatio Lung -0.74062693823381 cerebhem 0.0289924529784762 cortex -0.106784914509786 heart 0.392145107549818 kidney -0.0215899794601583 liver -0.233833005328787 stomach 0.24949617937337 testicle 0.360086384834419 varWeightedLogRatios=0.313411762645997 cont.varWeightedLogRatios=0.137279158641917 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.94150000538078 0.105603973232031 37.3234063525299 1.54786337015424e-123 *** df.mm.trans1 -0.0481784082973159 0.0879826019286232 -0.547590173980091 0.5843253725679 df.mm.trans2 0.298624379038708 0.0879826019286232 3.39412989037276 0.000768112650451791 *** df.mm.exp2 0.744468549698652 0.121221542746079 6.14138817931133 2.23969560785092e-09 *** df.mm.exp3 -0.0315992694248472 0.121221542746079 -0.260673711198659 0.794498765329172 df.mm.exp4 0.00947544537182871 0.121221542746079 0.0781663486305962 0.937740783791365 df.mm.exp5 0.0222417559875098 0.121221542746079 0.183480225409268 0.854528397148933 df.mm.exp6 -0.148062693463944 0.121221542746079 -1.22142228278755 0.222755356053710 df.mm.exp7 0.0367528391716445 0.121221542746079 0.303187357123727 0.761928770593875 df.mm.exp8 0.0995305452804174 0.121221542746079 0.82106317924779 0.412174000360144 df.mm.trans1:exp2 -0.522295894442836 0.102450902616603 -5.09801164365918 5.65453435939155e-07 *** df.mm.trans2:exp2 -0.236162855385709 0.102450902616603 -2.30513201303349 0.0217487143997772 * df.mm.trans1:exp3 0.0185706950296775 0.102450902616603 0.181264337896306 0.856265926246982 df.mm.trans2:exp3 -0.00425076866301287 0.102450902616603 -0.0414907878256603 0.96692849940791 df.mm.trans1:exp4 0.0650162650914262 0.102450902616603 0.634609002272369 0.526101629683211 df.mm.trans2:exp4 -0.0201923500451457 0.102450902616603 -0.19709294432193 0.843870196838344 df.mm.trans1:exp5 0.0252919642610307 0.102450902616603 0.246869120867383 0.805155500976395 df.mm.trans2:exp5 0.00662763828965343 0.102450902616603 0.0646908726071033 0.948457381474757 df.mm.trans1:exp6 0.194860114307299 0.102450902616603 1.90198533473652 0.0580009287544921 . df.mm.trans2:exp6 0.0588064682585811 0.102450902616603 0.573996585258498 0.566341978315424 df.mm.trans1:exp7 0.0517443680948026 0.102450902616603 0.505065028938231 0.613833779180857 df.mm.trans2:exp7 0.0512135900222621 0.102450902616603 0.499884224679953 0.617473436429076 df.mm.trans1:exp8 -0.0545460815517686 0.102450902616603 -0.532411917890988 0.59478147677968 df.mm.trans2:exp8 -0.0382528501334559 0.102450902616603 -0.373377385230149 0.709095586271885 df.mm.trans1:probe2 0.132826384011100 0.0561146703998786 2.36705273441982 0.0184786539976651 * df.mm.trans1:probe3 0.180209173004655 0.0561146703998786 3.21144491664063 0.00144419766594136 ** df.mm.trans1:probe4 0.43555812045534 0.0561146703998786 7.76192958724537 9.46770292310927e-14 *** df.mm.trans1:probe5 0.279626856611348 0.0561146703998786 4.98313283529422 9.89202098328092e-07 *** df.mm.trans1:probe6 0.403064166576857 0.0561146703998786 7.18286615076916 4.19360191865686e-12 *** df.mm.trans2:probe2 -0.0206465904747812 0.0561146703998786 -0.36793569894738 0.713145512429379 df.mm.trans2:probe3 -0.119272740596705 0.0561146703998786 -2.12551797501003 0.034249346535241 * df.mm.trans2:probe4 -0.248766477281265 0.0561146703998786 -4.43318076197419 1.24741975666632e-05 *** df.mm.trans2:probe5 -0.067504758606869 0.0561146703998786 -1.20297879548830 0.229804664795974 df.mm.trans2:probe6 -0.292428535405869 0.0561146703998786 -5.21126709507505 3.22581401740968e-07 *** df.mm.trans3:probe2 -0.0223524265998132 0.0561146703998786 -0.398334810496571 0.690628380910698 df.mm.trans3:probe3 -0.333617972830768 0.0561146703998786 -5.94528971574409 6.72846715001956e-09 *** df.mm.trans3:probe4 -0.393645881376830 0.0561146703998786 -7.01502617001348 1.21063248926644e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.05145601883613 0.148749229041511 27.236820284329 3.53023820630315e-88 *** df.mm.trans1 -0.00630090061421629 0.123928520920265 -0.050843022795941 0.959479861907195 df.mm.trans2 0.160410312987957 0.123928520920265 1.29437769285703 0.196395710371840 df.mm.exp2 0.0889963015631035 0.170747467873042 0.521215937616575 0.602548822423894 df.mm.exp3 0.148043768496 0.170747467873042 0.86703346374704 0.386522826243258 df.mm.exp4 0.258081000256639 0.170747467873042 1.51147775994273 0.131576896408237 df.mm.exp5 0.0516011343281051 0.170747467873042 0.302207318040422 0.76267508114568 df.mm.exp6 -0.0898790339123071 0.170747467873042 -0.526385749855664 0.598956499279832 df.mm.exp7 -0.072919168289889 0.170747467873042 -0.427058563141373 0.669601528582509 df.mm.exp8 0.0166423917885936 0.170747467873042 0.0974678687532158 0.922411122389542 df.mm.trans1:exp2 -0.0210232636244778 0.144307948957022 -0.145683337448992 0.884255964699419 df.mm.trans2:exp2 -0.207114876147113 0.144307948957022 -1.43522846554209 0.152122729562945 df.mm.trans1:exp3 -0.0603433313271472 0.144307948957022 -0.418156669561694 0.67609123040079 df.mm.trans2:exp3 -0.213637984683957 0.144307948957022 -1.48043116285703 0.139665577601159 df.mm.trans1:exp4 -0.00610132680083054 0.144307948957022 -0.0422799079671463 0.966299879355306 df.mm.trans2:exp4 -0.277345675173868 0.144307948957022 -1.92190158046295 0.055436786349255 . df.mm.trans1:exp5 0.0310128009365503 0.144307948957022 0.214907086967098 0.829966005651175 df.mm.trans2:exp5 -0.142802780610461 0.144307948957022 -0.989569747491808 0.323073980393306 df.mm.trans1:exp6 0.123093619265196 0.144307948957022 0.852992646315388 0.394251771738362 df.mm.trans2:exp6 0.000963695329832836 0.144307948957022 0.00667804744504992 0.994675566189973 df.mm.trans1:exp7 0.130202021052758 0.144307948957022 0.902251206491299 0.367549286148223 df.mm.trans2:exp7 -0.110082381614853 0.144307948957022 -0.762829645979088 0.446083256166480 df.mm.trans1:exp8 0.130225995575114 0.144307948957022 0.902417340945635 0.367461184866651 df.mm.trans2:exp8 -0.135568988977354 0.144307948957022 -0.939442282682083 0.348157180747106 df.mm.trans1:probe2 0.00981372863969111 0.0790407188710651 0.124160417312243 0.90126015257526 df.mm.trans1:probe3 -0.0584714845792629 0.0790407188710651 -0.739764078748377 0.459943334654296 df.mm.trans1:probe4 0.0320629834073168 0.0790407188710651 0.405651465033099 0.685248714973136 df.mm.trans1:probe5 0.0151599673727952 0.0790407188710651 0.19179946221801 0.848011478096861 df.mm.trans1:probe6 0.0211998776147206 0.0790407188710651 0.26821463566523 0.788693483463473 df.mm.trans2:probe2 0.0051267455410491 0.0790407188710651 0.0648620813964519 0.948321161919704 df.mm.trans2:probe3 0.0577943223351504 0.0790407188710651 0.731196820583416 0.465152400577656 df.mm.trans2:probe4 0.0933266214387172 0.0790407188710651 1.18074105058376 0.238514302318507 df.mm.trans2:probe5 -0.0311625170713689 0.0790407188710651 -0.394259028972176 0.693631994248547 df.mm.trans2:probe6 0.0179697310057575 0.0790407188710651 0.227347767864695 0.820287219840841 df.mm.trans3:probe2 0.0557317668041872 0.0790407188710651 0.705101972757857 0.481219794629304 df.mm.trans3:probe3 0.0133786824746737 0.0790407188710651 0.169263167969127 0.865688273390665 df.mm.trans3:probe4 0.0133607925926952 0.0790407188710651 0.169036830427743 0.86586616405553