chr7.22376_chr7_70863864_70864988_-_1.R fitVsDatCorrelation=0.721793837184302 cont.fitVsDatCorrelation=0.343543374947193 fstatistic=5145.21401096742,37,347 cont.fstatistic=2790.14756218892,37,347 residuals=-0.522897319944815,-0.0873432653620884,-0.0054526673818732,0.0642225156303506,0.935991489225167 cont.residuals=-0.483553665038914,-0.144509393225847,-0.0310730921345017,0.0919308105110321,1.30337968102506 predictedValues: Include Exclude Both chr7.22376_chr7_70863864_70864988_-_1.R.tl.Lung 50.1170073254413 52.5744877196256 60.9082407650016 chr7.22376_chr7_70863864_70864988_-_1.R.tl.cerebhem 80.2509757273531 75.985700028288 55.4766982782998 chr7.22376_chr7_70863864_70864988_-_1.R.tl.cortex 49.0083769899314 54.337163787321 65.078691828951 chr7.22376_chr7_70863864_70864988_-_1.R.tl.heart 50.7092848133846 58.6646752844641 57.466350250427 chr7.22376_chr7_70863864_70864988_-_1.R.tl.kidney 48.4101454032512 52.7231300864336 64.5050330339467 chr7.22376_chr7_70863864_70864988_-_1.R.tl.liver 54.4213136794283 56.3189995192421 61.3297308903188 chr7.22376_chr7_70863864_70864988_-_1.R.tl.stomach 52.1207288340629 54.2884964029679 56.7754525727247 chr7.22376_chr7_70863864_70864988_-_1.R.tl.testicle 55.3339521852118 59.9567878352651 57.7682209444852 diffExp=-2.45748039418432,4.26527569906507,-5.32878679738958,-7.9553904710795,-4.31298468318239,-1.89768583981380,-2.16776756890497,-4.62283565005328 diffExpScore=1.29557473753332 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 51.8921907556613 57.2330014951168 65.4076792705265 cerebhem 56.4336104760054 54.2147326015875 50.661210820185 cortex 54.8574564293855 57.0088006986682 51.9106486571745 heart 56.9025708927391 59.3516701937403 56.652553976524 kidney 56.1430695184844 48.5530202911977 56.5191364245797 liver 59.9024804489671 50.4634064323285 60.7352559429074 stomach 66.2450054366631 54.133513859901 55.6542110521877 testicle 52.3430777677329 53.532936596132 56.6851035650346 cont.diffExp=-5.34081073945553,2.21887787441792,-2.15134426928275,-2.44909930100118,7.59004922728671,9.43907401663865,12.1114915767621,-1.18985882839903 cont.diffExpScore=2.00159440899477 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=0,0,0,0,0,0,1,0 cont.diffExp1.2Score=0.5 tran.correlation=0.968634615185973 cont.tran.correlation=-0.220878252730079 tran.covariance=0.0190769374160858 cont.tran.covariance=-0.00117292343853661 tran.mean=56.5763266013545 cont.tran.mean=55.5756589933944 weightedLogRatios: wLogRatio Lung -0.188528419248388 cerebhem 0.237998665850838 cortex -0.407047199141663 heart -0.582765336146529 kidney -0.334755100255036 liver -0.137580527765958 stomach -0.161936428731155 testicle -0.325242799640563 cont.weightedLogRatios: wLogRatio Lung -0.391668198349497 cerebhem 0.160970694726808 cortex -0.154792277233225 heart -0.171188914975022 kidney 0.574491907104952 liver 0.68707526470749 stomach 0.826283931182297 testicle -0.0892141254124491 varWeightedLogRatios=0.0584718153037526 cont.varWeightedLogRatios=0.209356291553823 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.03887681490203 0.101416399236446 39.8246915223805 1.81909743140332e-131 *** df.mm.trans1 -0.184400048392609 0.08684781569886 -2.12325487876409 0.0344398282373595 * df.mm.trans2 -0.0347234239467984 0.0855218169813679 -0.406018314067900 0.684979403153489 df.mm.exp2 0.932518089945264 0.118766725695630 7.85167802247138 5.16799352776137e-14 *** df.mm.exp3 -0.0556204437944683 0.118766725695630 -0.468316723128412 0.639852143058237 df.mm.exp4 0.179524310661888 0.118766725695630 1.51157076706792 0.131553224844285 df.mm.exp5 -0.0892024983345972 0.118766725695630 -0.751073146221119 0.453117678925091 df.mm.exp6 0.144300174551525 0.118766725695630 1.21498823602606 0.225196652136904 df.mm.exp7 0.141548114612243 0.118766725695630 1.19181625815800 0.234147765858829 df.mm.exp8 0.283349055975627 0.118766725695630 2.38576128386145 0.0175796440362012 * df.mm.trans1:exp2 -0.46171958747117 0.104742406740020 -4.40814376756873 1.39201164734532e-05 *** df.mm.trans2:exp2 -0.5642039026249 0.102218122378391 -5.51960737975925 6.66291306510239e-08 *** df.mm.trans1:exp3 0.03325126821305 0.104742406740020 0.317457553706805 0.751087376013808 df.mm.trans2:exp3 0.0885978748617268 0.102218122378391 0.866753104050918 0.386676239334118 df.mm.trans1:exp4 -0.167775702475963 0.104742406740020 -1.60179346358153 0.110111197259942 df.mm.trans2:exp4 -0.0699175266223665 0.102218122378391 -0.68400323734715 0.494429647289578 df.mm.trans1:exp5 0.0545514878021043 0.104742406740020 0.520815680104676 0.602827353498574 df.mm.trans2:exp5 0.0920257809242678 0.102218122378391 0.900288312708455 0.368591211107575 df.mm.trans1:exp6 -0.0619047199021648 0.104742406740020 -0.591018688885178 0.554892667074412 df.mm.trans2:exp6 -0.0754992048171196 0.102218122378391 -0.738608801065987 0.460643848442722 df.mm.trans1:exp7 -0.102345796742354 0.104742406740020 -0.977119009651795 0.329190943972990 df.mm.trans2:exp7 -0.109466740471575 0.102218122378391 -1.07091323851901 0.284952737695532 df.mm.trans1:exp8 -0.184322790338059 0.104742406740020 -1.75977234125967 0.0793275286512577 . df.mm.trans2:exp8 -0.151955933709288 0.102218122378391 -1.48658506117710 0.138032459083701 df.mm.trans1:probe2 0.172542577776508 0.0523712033700102 3.29460785075855 0.00108723464266919 ** df.mm.trans1:probe3 0.244829382579261 0.0523712033700102 4.67488556353203 4.21703540453427e-06 *** df.mm.trans1:probe4 0.038263611402052 0.0523712033700102 0.730623108499417 0.465502402058676 df.mm.trans1:probe5 0.0427220971134997 0.0523712033700102 0.815755498525819 0.415199585344382 df.mm.trans1:probe6 0.174121075573807 0.0523712033700102 3.32474841839352 0.000979505649750002 *** df.mm.trans1:probe7 -0.133525880504205 0.0523712033700102 -2.54960497204590 0.0112139842477283 * df.mm.trans2:probe2 -0.134134119326702 0.0523712033700102 -2.561218965679 0.0108527814593154 * df.mm.trans2:probe3 -0.0177882046004074 0.0523712033700102 -0.339656212875826 0.734320927280585 df.mm.trans2:probe4 0.0224019506480067 0.0523712033700102 0.427753215631378 0.669096142396829 df.mm.trans2:probe5 -0.143031267439322 0.0523712033700102 -2.73110523026911 0.00663470397856826 ** df.mm.trans2:probe6 -0.104750078222378 0.0523712033700102 -2.00014648283529 0.0462633912926848 * df.mm.trans3:probe2 0.452377336935930 0.0523712033700102 8.63790227885003 2.12044300048919e-16 *** df.mm.trans3:probe3 0.416468081075313 0.0523712033700102 7.95223432489998 2.60821299621110e-14 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.70433408464104 0.137614153507509 26.9182637848287 5.66009127770425e-87 *** df.mm.trans1 0.141730080102047 0.117845720528005 1.20267481472410 0.229922169687899 df.mm.trans2 0.331994863524525 0.116046443562608 2.86087925947866 0.0044806575130693 ** df.mm.exp2 0.285197735624791 0.161157194936075 1.76968664500471 0.0776575366721256 . df.mm.exp3 0.282760506914330 0.161157194936075 1.75456334435761 0.0802166310230765 . df.mm.exp4 0.272224393620531 0.161157194936075 1.68918547960898 0.0920821587636425 . df.mm.exp5 0.0603210483689317 0.161157194936075 0.374299443427636 0.708410166366255 df.mm.exp6 0.091782689035755 0.161157194936075 0.56952275120054 0.569369925696852 df.mm.exp7 0.349996479798654 0.161157194936075 2.17177073563166 0.0305498283065962 * df.mm.exp8 0.0849460266853652 0.161157194936075 0.527100429608869 0.598460661224016 df.mm.trans1:exp2 -0.20130113590608 0.142127286596537 -1.41634404431798 0.157571842131800 df.mm.trans2:exp2 -0.339375726127731 0.138702029357538 -2.44679712113590 0.0149087221765943 * df.mm.trans1:exp3 -0.227190698952490 0.142127286596537 -1.59850162761093 0.110841513680130 df.mm.trans2:exp3 -0.286685534005582 0.138702029357538 -2.06691665099276 0.0394832798724778 * df.mm.trans1:exp4 -0.180052182574666 0.142127286596537 -1.26683754320722 0.206063016093630 df.mm.trans2:exp4 -0.235874812762883 0.138702029357538 -1.70058660176384 0.0899165940076735 . df.mm.trans1:exp5 0.0184138854949413 0.142127286596537 0.129559115183938 0.896990318037984 df.mm.trans2:exp5 -0.224795326885042 0.138702029357538 -1.62070683411256 0.105988851585965 df.mm.trans1:exp6 0.0517669133458848 0.142127286596537 0.364229238350534 0.715908677465175 df.mm.trans2:exp6 -0.217664921754386 0.138702029357538 -1.56929875332467 0.117489737399499 df.mm.trans1:exp7 -0.105804719124445 0.142127286596537 -0.744436354609353 0.457116371418986 df.mm.trans2:exp7 -0.405673687124231 0.138702029357538 -2.92478552046640 0.00367361983541835 ** df.mm.trans1:exp8 -0.0762946396695961 0.142127286596537 -0.536805011174083 0.591746313350122 df.mm.trans2:exp8 -0.151779606129306 0.138702029357538 -1.09428540326586 0.274588835247177 df.mm.trans1:probe2 0.168994155662953 0.0710636432982685 2.37806771253832 0.0179445769538834 * df.mm.trans1:probe3 0.152402638625052 0.0710636432982685 2.14459365649728 0.0326794034729492 * df.mm.trans1:probe4 0.136491756423859 0.0710636432982685 1.92069742119716 0.0555890763560936 . df.mm.trans1:probe5 0.131383718058979 0.0710636432982685 1.84881765078571 0.065334608011823 . df.mm.trans1:probe6 0.168992104374898 0.0710636432982685 2.37803884703186 0.0179459586023743 * df.mm.trans1:probe7 0.169672949600640 0.0710636432982685 2.38761962834481 0.0174924820917590 * df.mm.trans2:probe2 -0.00465273604345242 0.0710636432982685 -0.0654728047635264 0.947835261954588 df.mm.trans2:probe3 0.0487897474650403 0.0710636432982685 0.686564116340895 0.492815972160542 df.mm.trans2:probe4 0.0167896463619715 0.0710636432982685 0.236262110732235 0.813368681810735 df.mm.trans2:probe5 0.0229952938102906 0.0710636432982685 0.323587318958228 0.746445421494515 df.mm.trans2:probe6 0.0132936459849112 0.0710636432982685 0.187066766744777 0.851717610906233 df.mm.trans3:probe2 0.0137856339766755 0.0710636432982685 0.193989969228208 0.84629724771487 df.mm.trans3:probe3 -0.00604370395373506 0.0710636432982685 -0.0850463566632576 0.932273583368077