fitVsDatCorrelation=0.736950731637842 cont.fitVsDatCorrelation=0.259967139552475 fstatistic=10675.0066979331,50,646 cont.fstatistic=5224.38470070323,50,646 residuals=-0.367753035332016,-0.0764445444955947,-0.00706122956223944,0.0653068438573207,1.25042979429093 cont.residuals=-0.429330053710192,-0.115679986742469,-0.0303682661574447,0.0806314695928594,1.83792193068795 predictedValues: Include Exclude Both Lung 48.7124025217786 45.5044502719844 53.1799473443875 cerebhem 51.3745060202097 42.9520341361377 52.024823506338 cortex 47.9139784387298 41.0481028107238 51.9548804876231 heart 50.6794770252907 47.2918553969613 56.6793818059579 kidney 50.7036227749965 44.1193776367399 51.9953515335073 liver 51.5088032649642 45.6009985477698 53.2188760870022 stomach 49.1830097130915 44.1992520207815 64.2880444318978 testicle 50.1222694495431 43.2838718639486 54.399772659319 diffExp=3.20795224979421,8.42247188407197,6.86587562800602,3.38762162832936,6.58424513825657,5.90780471719448,4.98375769230998,6.83839758559448 diffExpScore=0.978812718350147 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 48.1436061882081 51.4670847608932 46.8058980498265 cerebhem 48.5801409716182 57.6846788873098 51.7714363249049 cortex 49.9058326256512 52.7945193155196 45.8156863106886 heart 46.7176834008091 50.5246856422005 50.7021628722292 kidney 49.4847376044232 53.236988409515 52.2649412053445 liver 50.5960517546025 49.2070525522718 49.9849023989205 stomach 49.0770092901347 51.2229165504965 49.8505215560743 testicle 47.9152488684145 51.2787519966276 49.4158770356911 cont.diffExp=-3.32347857268503,-9.10453791569157,-2.88868668986841,-3.80700224139144,-3.75225080509173,1.38899920233067,-2.14590726036183,-3.36350312821309 cont.diffExpScore=1.06350818227812 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=0.415523096711061 cont.tran.correlation=-0.0318171987280468 tran.covariance=0.000482951966675327 cont.tran.covariance=-3.24566855143217e-05 tran.mean=47.1373757433532 cont.tran.mean=50.4898118011685 weightedLogRatios: wLogRatio Lung 0.262403150268169 cerebhem 0.689304201821361 cortex 0.586492587925265 heart 0.269185969530874 kidney 0.536425295950023 liver 0.472776164255801 stomach 0.410494368915902 testicle 0.563436312001881 cont.weightedLogRatios: wLogRatio Lung -0.260846138882091 cerebhem -0.681799779120657 cortex -0.221604640880851 heart -0.304214364955371 kidney -0.287840278137097 liver 0.108839809126400 stomach -0.167538627705840 testicle -0.264814048366676 varWeightedLogRatios=0.0230946364948623 cont.varWeightedLogRatios=0.0466764350659314 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.81245954525394 0.0691657851675444 55.1205995279138 2.04909129973921e-246 *** df.mm.trans1 0.0950350737212942 0.060069447583447 1.58208669372685 0.114119221096472 df.mm.trans2 -0.0507889174680873 0.0545869633827773 -0.930422106684024 0.352500133242511 df.mm.exp2 0.0174426824217548 0.0722823877384133 0.241313035823873 0.809389081394507 df.mm.exp3 -0.0962861566709114 0.0722823877384133 -1.3320832319398 0.183302588755769 df.mm.exp4 0.0143862153109358 0.0722823877384133 0.199027948039001 0.842303507096347 df.mm.exp5 0.0316797270661260 0.0722823877384133 0.43827726306958 0.661331825170692 df.mm.exp6 0.0572067941770439 0.0722823877384133 0.791434759793391 0.428980820030255 df.mm.exp7 -0.209179983858554 0.0722823877384133 -2.89392741999015 0.00393284527851519 ** df.mm.exp8 -0.0441768773714591 0.0722823877384133 -0.611170698059024 0.541301571194605 df.mm.trans1:exp2 0.0357657055997532 0.0666410687233584 0.536691657035461 0.591665396354506 df.mm.trans2:exp2 -0.075168803900449 0.0548108343019027 -1.37142236307539 0.170719491303001 df.mm.trans1:exp3 0.079759774387966 0.0666410687233584 1.19685617166595 0.231801654899919 df.mm.trans2:exp3 -0.0067793543956794 0.0548108343019027 -0.123686393064885 0.901602058688165 df.mm.trans1:exp4 0.0252011513648002 0.0666410687233584 0.378162473195256 0.705434131199906 df.mm.trans2:exp4 0.0241417456719316 0.0548108343019027 0.440455723387767 0.65975441651134 df.mm.trans1:exp5 0.00838396653608745 0.0666410687233584 0.125807804356967 0.89992320678893 df.mm.trans2:exp5 -0.0625907682780291 0.0548108343019027 -1.14194153537736 0.253901412843568 df.mm.trans1:exp6 -0.00138773350194109 0.0666410687233584 -0.0208239983020362 0.983392484168803 df.mm.trans2:exp6 -0.0550873092685315 0.0548108343019027 -1.00504416636145 0.315251889329131 df.mm.trans1:exp7 0.218794547111334 0.0666410687233583 3.28317884605959 0.00108179556097505 ** df.mm.trans2:exp7 0.180077720842786 0.0548108343019027 3.28544024436671 0.00107329212016496 ** df.mm.trans1:exp8 0.0727086171220389 0.0666410687233584 1.09104818567464 0.275658448077224 df.mm.trans2:exp8 -0.00585316062905117 0.0548108343019027 -0.106788387799599 0.914990013915217 df.mm.trans1:probe2 0.0132611216706511 0.0408091535714938 0.324954587637276 0.745320648980127 df.mm.trans1:probe3 0.137358240239035 0.0408091535714938 3.36586839514808 0.000808246536654212 *** df.mm.trans1:probe4 0.0422649578635194 0.0408091535714938 1.03567347432177 0.300742028103266 df.mm.trans1:probe5 0.235872250873291 0.0408091535714938 5.77988588908282 1.16353295275817e-08 *** df.mm.trans1:probe6 -0.090489731312457 0.0408091535714938 -2.21738809539207 0.0269438448787315 * df.mm.trans1:probe7 0.0147350345989495 0.0408091535714938 0.361071801529406 0.718163820593292 df.mm.trans1:probe8 -0.045275588340839 0.0408091535714938 -1.10944688577087 0.267650274724903 df.mm.trans1:probe9 0.0835623093466737 0.0408091535714938 2.04763642549656 0.0409995082983941 * df.mm.trans1:probe10 -0.0898412180041107 0.0408091535714938 -2.20149672662819 0.0280537030839797 * df.mm.trans1:probe11 -0.0529698638811098 0.0408091535714938 -1.29798977056242 0.194754089474455 df.mm.trans1:probe12 -0.0667637704532988 0.0408091535714938 -1.63599988263258 0.102326694082934 df.mm.trans1:probe13 -0.069120422533601 0.0408091535714938 -1.69374800711092 0.0907952277381446 . df.mm.trans1:probe14 -0.105890975170364 0.0408091535714938 -2.59478489267984 0.0096798376994462 ** df.mm.trans1:probe15 -0.175315184870112 0.0408091535714938 -4.29597699356779 2.00697379183018e-05 *** df.mm.trans1:probe16 -0.144406647433277 0.0408091535714938 -3.53858472414258 0.000431132555538427 *** df.mm.trans1:probe17 -0.182882348907221 0.0408091535714938 -4.48140509914837 8.77147783522804e-06 *** df.mm.trans2:probe2 0.0658369059938935 0.0408091535714938 1.6132877119971 0.107170370691486 df.mm.trans2:probe3 0.0742902402846779 0.0408091535714938 1.82043080493028 0.0691559776720519 . df.mm.trans2:probe4 0.187240326227009 0.0408091535714938 4.588194310352 5.37213828472718e-06 *** df.mm.trans2:probe5 0.159527561845916 0.0408091535714938 3.90911224283147 0.000102420271821341 *** df.mm.trans2:probe6 0.186778984412038 0.0408091535714938 4.5768894491972 5.66097898938749e-06 *** df.mm.trans3:probe2 0.600381031288624 0.0408091535714938 14.7119207027123 1.81737803547807e-42 *** df.mm.trans3:probe3 -0.0311536508661369 0.0408091535714938 -0.7633986039813 0.445504410279683 df.mm.trans3:probe4 -0.00396955654449267 0.0408091535714938 -0.0972712295426166 0.92254117362861 df.mm.trans3:probe5 0.112328252971117 0.0408091535714938 2.75252591981181 0.0060798160347809 ** df.mm.trans3:probe6 0.0242680881580225 0.0408091535714938 0.594672666158271 0.552270516217898 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.93420910159736 0.098806183379964 39.8174382110092 4.8240367600035e-176 *** df.mm.trans1 -0.101545011865190 0.0858116891044601 -1.18334708155643 0.237106904668256 df.mm.trans2 0.0110286436736561 0.0779797337815077 0.141429614322067 0.887574652594151 df.mm.exp2 0.0222462674678306 0.103258378990753 0.21544273389981 0.829490156675458 df.mm.exp3 0.082797147571141 0.103258378990753 0.801844347939604 0.422937854683815 df.mm.exp4 -0.128505366672782 0.103258378990753 -1.24450304109742 0.213765798130576 df.mm.exp5 -0.0490296804040376 0.103258378990753 -0.474825199497158 0.635072049922063 df.mm.exp6 -0.0609320961171962 0.103258378990753 -0.590093479219276 0.555334327917744 df.mm.exp7 -0.0485728462755359 0.103258378990753 -0.470401014913139 0.63822731301214 df.mm.exp8 -0.0626830837998485 0.103258378990753 -0.607050821565403 0.544030482123365 df.mm.trans1:exp2 -0.0132197820347808 0.0951995215693248 -0.138863954533155 0.889600932273359 df.mm.trans2:exp2 0.0918028677554686 0.0782995426441552 1.17245726673886 0.241445696513934 df.mm.trans1:exp3 -0.0468476053402642 0.0951995215693248 -0.492099167810938 0.62281642277925 df.mm.trans2:exp3 -0.057332235571091 0.0782995426441552 -0.732216736330716 0.464301851997405 df.mm.trans1:exp4 0.0984397792389116 0.0951995215693248 1.03403649111017 0.301506041030269 df.mm.trans2:exp4 0.110024935634249 0.0782995426441552 1.40517979950758 0.160448518366558 df.mm.trans1:exp5 0.0765056312295423 0.0951995215693248 0.803634618833987 0.421903626643029 df.mm.trans2:exp5 0.0828406335363189 0.0782995426441552 1.05799639102365 0.290452542300621 df.mm.trans1:exp6 0.110617300819539 0.0951995215693248 1.16195227660873 0.245683962239534 df.mm.trans2:exp6 0.0160265814189252 0.0782995426441552 0.204682950598583 0.837884313530181 df.mm.trans1:exp7 0.067775188871259 0.0951995215693247 0.71192783066567 0.47676648475357 df.mm.trans2:exp7 0.043817394577808 0.0782995426441552 0.559612394888986 0.575937821515766 df.mm.trans1:exp8 0.0579285455568303 0.0951995215693248 0.608496183614183 0.543072327310958 df.mm.trans2:exp8 0.0590170865948157 0.0782995426441552 0.75373475504229 0.45128313602628 df.mm.trans1:probe2 0.057123893392639 0.0582975629004818 0.97986760596071 0.327518287892287 df.mm.trans1:probe3 0.115410378323248 0.0582975629004817 1.97967758138126 0.0481637914082133 * df.mm.trans1:probe4 0.0117866978952197 0.0582975629004817 0.202181657496393 0.839838366224182 df.mm.trans1:probe5 0.116792516217831 0.0582975629004818 2.00338591198407 0.0455530863691455 * df.mm.trans1:probe6 0.0399826299620945 0.0582975629004817 0.68583707401882 0.493061908515086 df.mm.trans1:probe7 0.00307079937251388 0.0582975629004817 0.0526745753978766 0.958007480937007 df.mm.trans1:probe8 0.0515605615497179 0.0582975629004818 0.88443768460331 0.376789040701702 df.mm.trans1:probe9 0.0605221454258468 0.0582975629004817 1.03815909987803 0.299584410936758 df.mm.trans1:probe10 0.0603450006601061 0.0582975629004817 1.03512046915442 0.300999981970799 df.mm.trans1:probe11 0.0616860298721845 0.0582975629004818 1.05812364708087 0.290394574011431 df.mm.trans1:probe12 0.0883854102838488 0.0582975629004817 1.51610815077689 0.129981162239273 df.mm.trans1:probe13 0.0438132606703405 0.0582975629004817 0.751545321802439 0.45259824117769 df.mm.trans1:probe14 0.0741096487368382 0.0582975629004818 1.27123064927000 0.204104135758026 df.mm.trans1:probe15 0.0653885166198811 0.0582975629004818 1.12163379336293 0.262434922802666 df.mm.trans1:probe16 0.0590257145207959 0.0582975629004817 1.01249025832447 0.311682770628865 df.mm.trans1:probe17 0.0460545522320397 0.0582975629004817 0.789991038058628 0.429822883394269 df.mm.trans2:probe2 -0.0207101191639037 0.0582975629004817 -0.355248455227148 0.722519424333099 df.mm.trans2:probe3 -0.00790290621891976 0.0582975629004818 -0.135561519654099 0.892210157006657 df.mm.trans2:probe4 0.0401621448096909 0.0582975629004818 0.688916359646982 0.491123249542349 df.mm.trans2:probe5 -0.00588615958627407 0.0582975629004818 -0.100967506932017 0.919607582255993 df.mm.trans2:probe6 -0.0572062333081277 0.0582975629004818 -0.981280013467851 0.326822027370384 df.mm.trans3:probe2 -0.00561345275422761 0.0582975629004817 -0.0962896641804768 0.923320382995633 df.mm.trans3:probe3 0.0828836387994955 0.0582975629004818 1.42173419737947 0.155586021459933 df.mm.trans3:probe4 -0.0532599023821703 0.0582975629004818 -0.913587116378927 0.361274679200745 df.mm.trans3:probe5 -0.0528791547702994 0.0582975629004817 -0.907056009537963 0.36471539541583 df.mm.trans3:probe6 0.0427678008038431 0.0582975629004818 0.73361215591209 0.463451299393693