fitVsDatCorrelation=0.831739681724921 cont.fitVsDatCorrelation=0.225209070555291 fstatistic=9592.5550385072,60,876 cont.fstatistic=3104.61656183330,60,876 residuals=-1.15743347057676,-0.0922507830760678,-0.006462053210297,0.0805894502614319,0.756313409087003 cont.residuals=-0.551727966814167,-0.196766801987576,-0.0510464931880256,0.132572707751204,1.59609504444945 predictedValues: Include Exclude Both Lung 67.3643063136665 66.4980586504216 55.5495087822639 cerebhem 62.970638989638 68.6194791702613 58.3754212102884 cortex 68.5933760707736 64.3653856376711 73.1457827011438 heart 61.4032244771046 61.5515924178242 52.9733223945313 kidney 64.231917262733 66.3657680828755 54.3193142118626 liver 67.492542745947 64.1919134485833 62.5332245888396 stomach 61.82244746499 60.6939019069607 56.53816071391 testicle 65.3627879137613 61.4649740778288 51.0618907101516 diffExp=0.866247663244906,-5.64884018062328,4.22799043310246,-0.148367940719574,-2.13385082014251,3.30062929736363,1.12854555802929,3.89781383593251 diffExpScore=3.28994353230808 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 56.9572776680519 57.0053759066666 61.1322257508768 cerebhem 63.5256534922153 56.5684307750682 70.3850141335733 cortex 60.4124228017686 59.756873150854 63.575234935738 heart 63.0677020827345 57.7864278991885 60.181082902527 kidney 61.6156295322677 61.473545415148 60.1204095047284 liver 57.2905218393943 63.4011948521427 59.3353470736576 stomach 59.8595820127092 62.1628592501701 59.7602039756913 testicle 60.9051500715157 58.2853694978908 63.644806791443 cont.diffExp=-0.0480982386147417,6.95722271714705,0.655549650914608,5.28127418354603,0.142084117119772,-6.11067301274832,-2.30327723746089,2.61978057362496 cont.diffExpScore=2.943417586631 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=0.276997483078529 cont.tran.correlation=-0.395425605965814 tran.covariance=0.000549260265643291 cont.tran.covariance=-0.000652788641887161 tran.mean=64.56201966444 cont.tran.mean=60.0046260154866 weightedLogRatios: wLogRatio Lung 0.0544058465730866 cerebhem -0.359577945191466 cortex 0.266973962312363 heart -0.00993989101927556 kidney -0.136569289309953 liver 0.209932986915415 stomach 0.0758128736664146 testicle 0.255116763345608 cont.weightedLogRatios: wLogRatio Lung -0.00341248446221879 cerebhem 0.474810213084127 cortex 0.044686743062555 heart 0.358606978037278 kidney 0.00951103782346893 liver -0.415404082924217 stomach -0.155211125294668 testicle 0.179706309335364 varWeightedLogRatios=0.0459042217089989 cont.varWeightedLogRatios=0.079238685086527 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.161750466091 0.076766770600958 54.2129157382981 4.04805570900812e-282 *** df.mm.trans1 0.117945370247717 0.0661533408789633 1.78290874928773 0.0749473577594248 . df.mm.trans2 0.0499710488207987 0.0583085480036035 0.85701068765613 0.391673363365792 df.mm.exp2 -0.0856632927300321 0.0746947211429786 -1.14684533818739 0.251758690659456 df.mm.exp3 -0.289695881695672 0.0746947211429786 -3.87839832939659 0.000113015548859354 *** df.mm.exp4 -0.122463740350781 0.0746947211429786 -1.63952336225158 0.101463346737932 df.mm.exp5 -0.0272116132902718 0.0746947211429786 -0.364304369490638 0.715718654535309 df.mm.exp6 -0.151817029454172 0.0746947211429786 -2.03250011689003 0.0424042415282401 * df.mm.exp7 -0.194819443219822 0.0746947211429786 -2.60820899039042 0.00925672730509779 ** df.mm.exp8 -0.0246312290415314 0.0746947211429786 -0.329758631729583 0.741661183069837 df.mm.trans1:exp2 0.0182165649786577 0.0688651302302786 0.264525238211896 0.791437443666034 df.mm.trans2:exp2 0.117066986065199 0.0501067422108273 2.33635197380489 0.0196975696906558 * df.mm.trans1:exp3 0.307776555304975 0.0688651302302786 4.46926556699739 8.87820826972022e-06 *** df.mm.trans2:exp3 0.257099126199188 0.0501067422108273 5.13102857730057 3.54976155580426e-07 *** df.mm.trans1:exp4 0.0298107923133582 0.0688651302302786 0.432886603331377 0.665203709443628 df.mm.trans2:exp4 0.0451667105762905 0.0501067422108273 0.90140984193801 0.367618209861645 df.mm.trans1:exp5 -0.0204034436539698 0.0688651302302786 -0.296281203357092 0.767085564807357 df.mm.trans2:exp5 0.0252202419062644 0.0501067422108273 0.503330306331804 0.614858596817891 df.mm.trans1:exp6 0.153718845666345 0.0688651302302786 2.23217243839261 0.0258556953196543 * df.mm.trans2:exp6 0.116521519462876 0.0501067422108273 2.32546588186884 0.0202746123510901 * df.mm.trans1:exp7 0.108970671595770 0.0688651302302786 1.58237806610373 0.113924239903507 df.mm.trans2:exp7 0.103489919411834 0.0501067422108273 2.06538910425255 0.0391798610439879 * df.mm.trans1:exp8 -0.00553096430246013 0.0688651302302786 -0.080315891133366 0.936004364287678 df.mm.trans2:exp8 -0.0540740395869193 0.0501067422108273 -1.07917691713820 0.280805915622987 df.mm.trans1:probe2 0.331090489149048 0.0479735532740048 6.9015210788744 9.86643583595982e-12 *** df.mm.trans1:probe3 -0.0311437268116239 0.0479735532740048 -0.649185325792818 0.516388760201473 df.mm.trans1:probe4 0.0498982257217668 0.0479735532740048 1.04011944741239 0.298571395618933 df.mm.trans1:probe5 -0.154461050808636 0.0479735532740048 -3.21971253466299 0.00133043545449626 ** df.mm.trans1:probe6 0.179955347239551 0.0479735532740048 3.75113651081297 0.000187612261749228 *** df.mm.trans1:probe7 -0.322686576157209 0.0479735532740048 -6.72634303976107 3.13782041367924e-11 *** df.mm.trans1:probe8 0.0175596712458752 0.0479735532740048 0.366028156088037 0.714432441457773 df.mm.trans1:probe9 -0.184120263785916 0.0479735532740048 -3.83795343935226 0.000132978538121534 *** df.mm.trans1:probe10 0.825510280674305 0.0479735532740048 17.2076117847543 2.17691166395828e-57 *** df.mm.trans1:probe11 -0.0316354020013627 0.0479735532740048 -0.659434205773221 0.509790298513924 df.mm.trans1:probe12 -0.148030670320234 0.0479735532740048 -3.08567242194350 0.00209474791772632 ** df.mm.trans1:probe13 -0.168193291696709 0.0479735532740048 -3.50595860048263 0.000478061664260003 *** df.mm.trans1:probe14 -0.235144261135080 0.0479735532740048 -4.90153939175685 1.13284239338178e-06 *** df.mm.trans1:probe15 0.0735827720995794 0.0479735532740048 1.53381951258239 0.125435123459582 df.mm.trans1:probe16 -0.283722393936455 0.0479735532740048 -5.91414174213763 4.77916762747193e-09 *** df.mm.trans1:probe17 -0.338750905529811 0.0479735532740048 -7.06120106624182 3.361216722027e-12 *** df.mm.trans1:probe18 -0.367097318347015 0.0479735532740048 -7.652076890163 5.21184699323933e-14 *** df.mm.trans1:probe19 -0.435949270948875 0.0479735532740048 -9.08728333002385 6.63247662787501e-19 *** df.mm.trans1:probe20 -0.329687612986260 0.0479735532740048 -6.87227838019884 1.19897481370520e-11 *** df.mm.trans1:probe21 -0.425998176180642 0.0479735532740048 -8.87985456794329 3.72935913211407e-18 *** df.mm.trans1:probe22 -0.317133639725003 0.0479735532740048 -6.61059308893941 6.64541300460642e-11 *** df.mm.trans2:probe2 -0.0384868224736202 0.0479735532740048 -0.802250820442665 0.422625465850094 df.mm.trans2:probe3 -0.0525953397360307 0.0479735532740048 -1.09634029890653 0.273231179021239 df.mm.trans2:probe4 -0.115516462784065 0.0479735532740048 -2.40791967449822 0.0162494551819317 * df.mm.trans2:probe5 0.174597044015018 0.0479735532740048 3.63944365383554 0.000289225064825159 *** df.mm.trans2:probe6 -0.215327354369995 0.0479735532740048 -4.48845957146713 8.13125204241643e-06 *** df.mm.trans3:probe2 -0.217609802100702 0.0479735532740048 -4.53603677963578 6.53028762019501e-06 *** df.mm.trans3:probe3 -0.362914005021439 0.0479735532740048 -7.5648764841042 9.81248154938047e-14 *** df.mm.trans3:probe4 -0.454686548637446 0.0479735532740048 -9.47785847840928 2.35473631916547e-20 *** df.mm.trans3:probe5 -0.20388481352409 0.0479735532740048 -4.24994188693061 2.36752308942833e-05 *** df.mm.trans3:probe6 -0.345144271115201 0.0479735532740048 -7.19446961003455 1.34643787045211e-12 *** df.mm.trans3:probe7 -0.405434297645206 0.0479735532740048 -8.4512042568441 1.1929935952885e-16 *** df.mm.trans3:probe8 -0.433156540354752 0.0479735532740048 -9.02906936829847 1.08033709567605e-18 *** df.mm.trans3:probe9 -0.396743744251072 0.0479735532740048 -8.27005125063466 4.94597259016153e-16 *** df.mm.trans3:probe10 -0.386998784487764 0.0479735532740048 -8.06691933527185 2.36369937004080e-15 *** df.mm.trans3:probe11 -0.229741523943881 0.0479735532740048 -4.78892031681901 1.96823456249643e-06 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.96930986009701 0.134724911454352 29.4623304424432 3.96152369868091e-133 *** df.mm.trans1 0.0726622778417388 0.116098448880389 0.625867774655625 0.531564700844494 df.mm.trans2 0.0496422172392091 0.102330916167512 0.485114558712114 0.627716375937265 df.mm.exp2 -0.0394933835691905 0.131088485464695 -0.30127271231482 0.763278044790392 df.mm.exp3 0.0668470723657302 0.131088485464695 0.509938551267598 0.610222962232555 df.mm.exp4 0.13119676060803 0.131088485464695 1.00082596990080 0.317187323262244 df.mm.exp5 0.170765218379767 0.131088485464695 1.30267138089529 0.193029322815783 df.mm.exp6 0.142004807885574 0.131088485464695 1.08327445680818 0.278984692237679 df.mm.exp7 0.159011372570259 0.131088485464695 1.21300793129603 0.225453781794393 df.mm.exp8 0.0489432191837374 0.131088485464695 0.373360169737554 0.708970731305002 df.mm.trans1:exp2 0.148635727675956 0.120857611958095 1.22984167292245 0.219086588326538 df.mm.trans2:exp2 0.0317988754751662 0.0879368293699654 0.361610439027576 0.717730364298449 df.mm.trans1:exp3 -0.00795378525977565 0.120857611958095 -0.0658112065174138 0.947543149922536 df.mm.trans2:exp3 -0.0197084338956022 0.0879368293699654 -0.224120360454269 0.822715910143815 df.mm.trans1:exp4 -0.0292894472032614 0.120857611958095 -0.242346731237888 0.808568232287544 df.mm.trans2:exp4 -0.117588401474240 0.0879368293699654 -1.33719173543915 0.181507171908422 df.mm.trans1:exp5 -0.0921511260626311 0.120857611958095 -0.762476806960101 0.445980734996446 df.mm.trans2:exp5 -0.0953038695014115 0.0879368293699654 -1.08377650393161 0.278762103272088 df.mm.trans1:exp6 -0.136171082984636 0.120857611958095 -1.12670671526963 0.260175046566636 df.mm.trans2:exp6 -0.0356676779109722 0.0879368293699654 -0.405605684973155 0.685131395562779 df.mm.trans1:exp7 -0.109311325130484 0.120857611958095 -0.904463718581383 0.365998232726812 df.mm.trans2:exp7 -0.0723992468749398 0.0879368293699654 -0.823309725784445 0.410555958444293 df.mm.trans1:exp8 0.0180730457788758 0.120857611958095 0.149539987478342 0.881161979289675 df.mm.trans2:exp8 -0.0267376868690461 0.0879368293699654 -0.304055616521674 0.76115772835403 df.mm.trans1:probe2 0.0467072095076358 0.0841931042089486 0.554762886420233 0.579198468231877 df.mm.trans1:probe3 0.0869567750357785 0.0841931042089486 1.03282538223049 0.301970674167407 df.mm.trans1:probe4 -0.0575342880362035 0.0841931042089486 -0.683361049301807 0.494559424880172 df.mm.trans1:probe5 -0.0163368448086019 0.0841931042089486 -0.194040176592817 0.846189409555762 df.mm.trans1:probe6 0.0993271162326235 0.0841931042089486 1.17975358155361 0.238418518320339 df.mm.trans1:probe7 -0.0688018041552734 0.0841931042089486 -0.817190490856859 0.414041766740261 df.mm.trans1:probe8 -0.0265107321378268 0.0841931042089486 -0.314880088896984 0.752927686055848 df.mm.trans1:probe9 0.00776076312249224 0.0841931042089486 0.0921781325847275 0.926577586895986 df.mm.trans1:probe10 0.0203476255484732 0.0841931042089486 0.241678053560954 0.809086197425143 df.mm.trans1:probe11 -0.0311497633940124 0.0841931042089486 -0.369979984544881 0.711486832678685 df.mm.trans1:probe12 0.00499203847196169 0.0841931042089486 0.0592927237790468 0.95273247959179 df.mm.trans1:probe13 -0.0368875871351795 0.0841931042089486 -0.438130741012146 0.661399526377491 df.mm.trans1:probe14 0.0696277678099668 0.0841931042089486 0.827000838894907 0.408461794744693 df.mm.trans1:probe15 0.0414794953541036 0.0841931042089486 0.492670934797233 0.622368577301113 df.mm.trans1:probe16 -0.0183481067194782 0.0841931042089486 -0.21792885405368 0.827535298466024 df.mm.trans1:probe17 -0.0146277419841969 0.0841931042089486 -0.173740380778621 0.862109640541173 df.mm.trans1:probe18 -0.0731229953670804 0.0841931042089486 -0.86851525495016 0.385350201658355 df.mm.trans1:probe19 0.0158775458377659 0.0841931042089486 0.188584872679850 0.850461869005509 df.mm.trans1:probe20 -0.0041218874775269 0.0841931042089486 -0.0489575425001231 0.96096429121853 df.mm.trans1:probe21 -0.0200879918452082 0.0841931042089486 -0.238594265337388 0.811476014960623 df.mm.trans1:probe22 -0.0146785628274779 0.0841931042089486 -0.174344003174523 0.861635402351447 df.mm.trans2:probe2 0.0844009481750014 0.0841931042089486 1.00246865783137 0.316394120821344 df.mm.trans2:probe3 0.144717719206441 0.0841931042089486 1.71887853009059 0.0859897880056905 . df.mm.trans2:probe4 0.076103356943767 0.0841931042089486 0.90391437230887 0.366289312547677 df.mm.trans2:probe5 0.0121300770811378 0.0841931042089486 0.144074472548650 0.885474799495732 df.mm.trans2:probe6 0.0939374020459007 0.0841931042089486 1.11573748145417 0.264840490802009 df.mm.trans3:probe2 -0.0427163512616336 0.0841931042089486 -0.50736163802229 0.612028799435258 df.mm.trans3:probe3 0.0403604094548919 0.0841931042089486 0.479379039816923 0.631788652333429 df.mm.trans3:probe4 0.0166162891648022 0.0841931042089486 0.197359265000662 0.843592187702876 df.mm.trans3:probe5 0.0146625838206090 0.0841931042089486 0.174154213202779 0.86178450617478 df.mm.trans3:probe6 0.0594714618526901 0.0841931042089486 0.70636974858529 0.480146054412063 df.mm.trans3:probe7 0.0116963878395158 0.0841931042089486 0.138923347100827 0.889542651572206 df.mm.trans3:probe8 -0.0294216726859004 0.0841931042089486 -0.349454660952782 0.726831991545869 df.mm.trans3:probe9 -0.0160926862719574 0.0841931042089486 -0.191140193999962 0.84846004878072 df.mm.trans3:probe10 0.0316853058280704 0.0841931042089486 0.376340866936495 0.706754630722617 df.mm.trans3:probe11 0.149411053820551 0.0841931042089486 1.77462341155335 0.0763073240601281 .