chr6.20544_chr6_144462726_144533543_-_2.R fitVsDatCorrelation=0.831739681724921 cont.fitVsDatCorrelation=0.253141541780388 fstatistic=9592.5550385072,60,876 cont.fstatistic=3149.14759706765,60,876 residuals=-1.15743347057676,-0.0922507830760678,-0.006462053210297,0.0805894502614319,0.756313409087003 cont.residuals=-0.530707599323337,-0.184409705724116,-0.0338380897528331,0.138043747533550,1.57160482161075 predictedValues: Include Exclude Both chr6.20544_chr6_144462726_144533543_-_2.R.tl.Lung 67.3643063136665 66.4980586504216 55.5495087822639 chr6.20544_chr6_144462726_144533543_-_2.R.tl.cerebhem 62.970638989638 68.6194791702613 58.3754212102884 chr6.20544_chr6_144462726_144533543_-_2.R.tl.cortex 68.5933760707736 64.3653856376711 73.1457827011438 chr6.20544_chr6_144462726_144533543_-_2.R.tl.heart 61.4032244771046 61.5515924178242 52.9733223945313 chr6.20544_chr6_144462726_144533543_-_2.R.tl.kidney 64.231917262733 66.3657680828755 54.3193142118626 chr6.20544_chr6_144462726_144533543_-_2.R.tl.liver 67.492542745947 64.1919134485833 62.5332245888396 chr6.20544_chr6_144462726_144533543_-_2.R.tl.stomach 61.82244746499 60.6939019069607 56.53816071391 chr6.20544_chr6_144462726_144533543_-_2.R.tl.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 60.218774813727 61.5085827936002 65.5431200871112 cerebhem 61.1423785947026 61.4754420595886 62.9527916343105 cortex 62.8592815480212 62.799745817477 53.8207162382365 heart 63.5066191255451 61.2422206543434 63.6117983034138 kidney 60.1625907544881 63.0089387982062 64.1766178135519 liver 59.888962034576 55.815185811487 64.4038992876241 stomach 59.1006955095924 69.1484625002405 57.0259645151867 testicle 61.368275509983 59.8798992238614 62.1639726402763 cont.diffExp=-1.28980797987315,-0.33306346488601,0.0595357305442761,2.26439847120171,-2.84634804371809,4.07377622308903,-10.0477669906481,1.48837628612164 cont.diffExpScore=2.93583638505299 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=-0.213559818453218 tran.covariance=0.000549260265643291 cont.tran.covariance=-0.000281831136185152 tran.mean=64.56201966444 cont.tran.mean=61.44537847184 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 -0.0870712761602985 cerebhem -0.0223599871527727 cortex 0.00392336690286775 heart 0.150057754497891 kidney -0.190458104552802 liver 0.285819333934191 stomach -0.652821228514701 testicle 0.100777128017738 varWeightedLogRatios=0.0459042217089989 cont.varWeightedLogRatios=0.0805258518954867 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) 4.06358291255719 0.133773397367432 30.3766144280231 5.19780561910826e-139 *** df.mm.trans1 0.0115870745787174 0.115278486867523 0.100513763613441 0.919959455490768 df.mm.trans2 0.0845091302038472 0.101608189336893 0.831715738223104 0.405796071369166 df.mm.exp2 0.0550052399892211 0.130162654159956 0.422588493944089 0.672699228632395 df.mm.exp3 0.260738522251879 0.130162654159956 2.00317459669699 0.0454662012851951 * df.mm.exp4 0.0787293568541761 0.130162654159956 0.60485365301038 0.545432879749025 df.mm.exp5 0.0442357568995922 0.130162654159956 0.339849837767069 0.734051081518546 df.mm.exp6 -0.085088637158128 0.130162654159956 -0.653710065358403 0.513470172158198 df.mm.exp7 0.237539181974168 0.130162654159956 1.82494113620531 0.0683503431749193 . df.mm.exp8 0.0450056263840536 0.130162654159956 0.345764510369822 0.729602716539958 df.mm.trans1:exp2 -0.0397841978898904 0.120004037670695 -0.331523827548726 0.740328140498306 df.mm.trans2:exp2 -0.0555441837236331 0.0873157628500372 -0.636130085916205 0.524857800484501 df.mm.trans1:exp3 -0.21782409802047 0.120004037670695 -1.81513974236604 0.0698442877923049 . df.mm.trans2:exp3 -0.239964218973051 0.0873157628500372 -2.74823481053683 0.00611488249997585 ** df.mm.trans1:exp4 -0.0255693958647639 0.120004037670695 -0.213071129614232 0.831321057532502 df.mm.trans2:exp4 -0.0830692479154923 0.0873157628500372 -0.951365998578766 0.341681025152774 df.mm.trans1:exp5 -0.0451691914565628 0.120004037670695 -0.376397264069665 0.706712724277744 df.mm.trans2:exp5 -0.0201358775817973 0.0873157628500371 -0.230609879872208 0.817671736312657 df.mm.trans1:exp6 0.0795966744123459 0.120004037670695 0.663283302439941 0.50732362943699 df.mm.trans2:exp6 -0.0120421060153910 0.0873157628500371 -0.13791445693572 0.890339718499747 df.mm.trans1:exp7 -0.256280666953914 0.120004037670695 -2.13560036752411 0.0329887519904617 * df.mm.trans2:exp7 -0.120460081075155 0.0873157628500372 -1.37959146370905 0.168064514917273 df.mm.trans1:exp8 -0.0260967879384423 0.120004037670695 -0.217465915689061 0.827895907617916 df.mm.trans2:exp8 -0.0718414724970176 0.0873157628500372 -0.822777814131953 0.410858265890957 df.mm.trans1:probe2 -0.0126641958027145 0.0835984782870494 -0.151488353163916 0.879625376538306 df.mm.trans1:probe3 0.121932458858355 0.0835984782870494 1.45854878410202 0.145047777912627 df.mm.trans1:probe4 0.0590003079658794 0.0835984782870494 0.705758157024006 0.480526183617456 df.mm.trans1:probe5 0.0777429090269698 0.0835984782870494 0.929956030539533 0.35265004189553 df.mm.trans1:probe6 0.0158823534431394 0.0835984782870494 0.189983762486737 0.849365868392643 df.mm.trans1:probe7 0.0308711311056529 0.0835984782870494 0.369278624900942 0.712009297931445 df.mm.trans1:probe8 -0.0128440220005033 0.0835984782870494 -0.153639423392387 0.87792943584308 df.mm.trans1:probe9 0.0806547106955932 0.0835984782870494 0.964786828040718 0.334917853011765 df.mm.trans1:probe10 0.0710237633429864 0.0835984782870494 0.849582011518373 0.395789638950032 df.mm.trans1:probe11 -0.0352181136202008 0.0835984782870494 -0.421276969890212 0.673656189179949 df.mm.trans1:probe12 -0.0169343087996406 0.0835984782870494 -0.202567189578426 0.839520373769184 df.mm.trans1:probe13 0.166767423809952 0.0835984782870494 1.99486195475148 0.0463673725586614 * df.mm.trans1:probe14 0.000574018171718987 0.0835984782870494 0.00686637105699459 0.994523034927804 df.mm.trans1:probe15 -0.0378106689728991 0.0835984782870494 -0.4522889620439 0.651172803425538 df.mm.trans1:probe16 0.0110667608225084 0.0835984782870494 0.132379931420628 0.894714187456686 df.mm.trans1:probe17 -0.0310528248913085 0.0835984782870494 -0.371452035103838 0.710390696619917 df.mm.trans1:probe18 0.106470630225126 0.0835984782870494 1.2735953142537 0.203144699801128 df.mm.trans1:probe19 0.0606353906540978 0.0835984782870494 0.72531691840007 0.468451337118068 df.mm.trans1:probe20 0.099568308203205 0.0835984782870494 1.19103015082787 0.23396436479811 df.mm.trans1:probe21 0.0246982534774642 0.0835984782870494 0.295439031708910 0.767728531360528 df.mm.trans1:probe22 -0.0274959979462243 0.0835984782870494 -0.328905483803332 0.742305743019885 df.mm.trans2:probe2 -0.135082556986512 0.0835984782870494 -1.61584947183708 0.106486923560023 df.mm.trans2:probe3 -0.044719800255815 0.0835984782870494 -0.534935577442715 0.59283016009286 df.mm.trans2:probe4 -0.0860921804717095 0.0835984782870494 -1.02982951646677 0.303374293676961 df.mm.trans2:probe5 -0.0628426087960222 0.0835984782870494 -0.751719529872799 0.452421655839903 df.mm.trans2:probe6 -0.162823294617255 0.0835984782870494 -1.94768251711681 0.0517721017020998 . df.mm.trans3:probe2 -0.0548783346885809 0.0835984782870494 -0.656451359080328 0.511706152076585 df.mm.trans3:probe3 0.0496830284593036 0.0835984782870494 0.594305416525748 0.552461306533228 df.mm.trans3:probe4 -0.0843307700736374 0.0835984782870494 -1.00875963057693 0.313368477179649 df.mm.trans3:probe5 0.0707760265757949 0.0835984782870494 0.846618599118198 0.397438961661315 df.mm.trans3:probe6 -0.0197060581591516 0.0835984782870494 -0.235722689729920 0.813702959613532 df.mm.trans3:probe7 0.0714420753352619 0.0835984782870494 0.854585834564519 0.393014119780559 df.mm.trans3:probe8 0.0910152635866556 0.0835984782870494 1.08871914240041 0.276577182608575 df.mm.trans3:probe9 0.0348246006483046 0.0835984782870494 0.41656979124343 0.677095157236353 df.mm.trans3:probe10 0.0708129554848104 0.0835984782870494 0.84706034052034 0.397192842234121 df.mm.trans3:probe11 0.0236816499069164 0.0835984782870494 0.28327848056757 0.777030302031674