chr1.706_chr1_5596293_5597096_+_1.R fitVsDatCorrelation=0.988180029639578 cont.fitVsDatCorrelation=0.304003401953816 fstatistic=5697.60537259342,36,324 cont.fstatistic=138.762453748834,36,324 residuals=-1.1472517730903,-0.0997105381023495,0.0025158819614025,0.0993180466664252,1.04496230168206 cont.residuals=-1.9794803892787,-1.11385842703693,-0.537854128922746,1.25605917349676,2.84669466346521 predictedValues: Include Exclude Both chr1.706_chr1_5596293_5597096_+_1.R.tl.Lung 1124.00623542454 58.7913572600657 57.8748099433445 chr1.706_chr1_5596293_5597096_+_1.R.tl.cerebhem 794.706917537925 57.9625182086543 54.261949716548 chr1.706_chr1_5596293_5597096_+_1.R.tl.cortex 485.52591619322 57.4136078735335 59.0911473791122 chr1.706_chr1_5596293_5597096_+_1.R.tl.heart 655.736600505946 56.5182059733617 53.5230961647601 chr1.706_chr1_5596293_5597096_+_1.R.tl.kidney 1230.32782610455 62.7914216508916 55.9917101877471 chr1.706_chr1_5596293_5597096_+_1.R.tl.liver 818.806993098356 59.2923146087375 58.8825237918789 chr1.706_chr1_5596293_5597096_+_1.R.tl.stomach 718.634354836737 52.8155368145514 53.6019471458593 chr1.706_chr1_5596293_5597096_+_1.R.tl.testicle 927.132592756407 56.3810752914219 54.0639882726616 diffExp=1065.21487816447,736.744399329271,428.112308319686,599.218394532584,1167.53640445366,759.514678489619,665.818818022185,870.751517464985 diffExpScore=0.99984111628896 diffExp1.5=1,1,1,1,1,1,1,1 diffExp1.5Score=0.888888888888889 diffExp1.4=1,1,1,1,1,1,1,1 diffExp1.4Score=0.888888888888889 diffExp1.3=1,1,1,1,1,1,1,1 diffExp1.3Score=0.888888888888889 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 163.895115362780 222.716238861318 148.368185963948 cerebhem 167.832830112353 163.220200912948 280.819426552836 cortex 182.513308456045 178.204275718455 260.783683858948 heart 217.213599784639 153.211985061724 54.4696537170009 kidney 208.806858865469 117.038032228525 139.468242111926 liver 241.076013945557 73.9167977610337 149.652809800113 stomach 147.119462352994 143.824487633898 203.357304487662 testicle 238.709687712090 227.793978935118 349.886435373635 cont.diffExp=-58.8211234985375,4.61262919940478,4.30903273758986,64.0016147229147,91.7688266369442,167.159216184523,3.29497471909525,10.9157087769722 cont.diffExpScore=1.40466934186416 cont.diffExp1.5=0,0,0,0,1,1,0,0 cont.diffExp1.5Score=0.666666666666667 cont.diffExp1.4=0,0,0,1,1,1,0,0 cont.diffExp1.4Score=0.75 cont.diffExp1.3=-1,0,0,1,1,1,0,0 cont.diffExp1.3Score=1.33333333333333 cont.diffExp1.2=-1,0,0,1,1,1,0,0 cont.diffExp1.2Score=1.33333333333333 tran.correlation=0.626029657872746 cont.tran.correlation=-0.253293486289976 tran.covariance=0.00801190472144475 cont.tran.covariance=-0.0228958006809359 tran.mean=451.052717133681 cont.tran.mean=177.943304606559 weightedLogRatios: wLogRatio Lung 16.3741689154186 cerebhem 14.0566902254488 cortex 10.9261620790906 heart 12.8936875433356 kidney 16.7428197338729 liver 14.1642948082304 stomach 13.7630115870591 testicle 15.2097213911372 cont.weightedLogRatios: wLogRatio Lung -1.61081285942156 cerebhem 0.142379642221535 cortex 0.124119034136222 heart 1.81732248148471 kidney 2.92463072069878 liver 5.78558166247779 stomach 0.112801175931548 testicle 0.255181768805849 varWeightedLogRatios=3.54493315789647 cont.varWeightedLogRatios=5.23344744200777 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 6.92963854272368 0.125591240145726 55.1761295985537 8.5842121594054e-167 *** df.mm.trans1 0.00207146130309171 0.106374468459743 0.0194732940440087 0.984475527661811 df.mm.trans2 -2.86340368200972 0.106374468459743 -26.9181479679343 1.24848754375733e-84 *** df.mm.exp2 -0.296420494288069 0.148139344984043 -2.00095723604015 0.0462308467823057 * df.mm.exp3 -0.88393431794378 0.148139344984043 -5.96691120808583 6.33622322370809e-09 *** df.mm.exp4 -0.500158472413691 0.148139344984043 -3.37627031135831 0.000824154641386639 *** df.mm.exp5 0.189283548743205 0.148139344984043 1.27773987905505 0.202255884564706 df.mm.exp6 -0.325583454881288 0.148139344984043 -2.19781891783280 0.0286691698204565 * df.mm.exp7 -0.477794516151546 0.148139344984043 -3.22530463600344 0.00138674751426090 ** df.mm.exp8 -0.166305373955824 0.148139344984043 -1.12262798228072 0.2624267346493 df.mm.trans1:exp2 -0.0502606941823404 0.128292436056168 -0.391766621068257 0.69548820590277 df.mm.trans2:exp2 0.282222199422885 0.128292436056168 2.19983506509553 0.0285243609738292 * df.mm.trans1:exp3 0.0445124067000786 0.128292436056168 0.346960491736165 0.728846245377961 df.mm.trans2:exp3 0.860220805411761 0.128292436056168 6.70515606263135 8.95581632178733e-11 *** df.mm.trans1:exp4 -0.0387369208623727 0.128292436056168 -0.301942359605777 0.762889723211717 df.mm.trans2:exp4 0.460726429550153 0.128292436056168 3.59122052486743 0.000380141572170077 *** df.mm.trans1:exp5 -0.0989021885690222 0.128292436056168 -0.770912078758264 0.441320851982649 df.mm.trans2:exp5 -0.123459941243276 0.128292436056168 -0.962332192283136 0.336600412094589 df.mm.trans1:exp6 0.00877727133024 0.128292436056168 0.0684161249101015 0.945496588415457 df.mm.trans2:exp6 0.334068291881513 0.128292436056168 2.60395937711599 0.00963968260406352 ** df.mm.trans1:exp7 0.0304926197302666 0.128292436056168 0.237680573131502 0.8122790809129 df.mm.trans2:exp7 0.370605062701623 0.128292436056168 2.88875224521707 0.00412817736716608 ** df.mm.trans1:exp8 -0.0262526144185400 0.128292436056168 -0.204631038474055 0.837988889249827 df.mm.trans2:exp8 0.124444072945715 0.128292436056168 0.970003195599406 0.332768450269734 df.mm.trans1:probe2 0.599829937795273 0.064146218028084 9.3509790013288 1.47340961246294e-18 *** df.mm.trans1:probe3 0.719367350918497 0.064146218028084 11.2144935903088 6.98738350506197e-25 *** df.mm.trans1:probe4 -0.122174792071656 0.064146218028084 -1.90462970113321 0.0577136088628993 . df.mm.trans1:probe5 -0.135830510881582 0.064146218028084 -2.11751394013774 0.0349777010635767 * df.mm.trans1:probe6 -0.224690820280687 0.064146218028084 -3.50279139110453 0.000525080215383592 *** df.mm.trans2:probe2 -0.153427594433459 0.064146218028084 -2.39184162605325 0.0173338348766976 * df.mm.trans2:probe3 0.260824230057333 0.064146218028084 4.06608897726661 6.00740526503877e-05 *** df.mm.trans2:probe4 0.0141966907889662 0.064146218028084 0.221317658708277 0.824984515884018 df.mm.trans2:probe5 -0.0558191211513338 0.064146218028084 -0.870185692426878 0.384843166257725 df.mm.trans2:probe6 0.00406577686611166 0.064146218028084 0.0633829552403481 0.94950064449138 df.mm.trans3:probe2 0.0930378285173783 0.064146218028084 1.45040239904160 0.147913712531984 df.mm.trans3:probe3 -0.1231101091144 0.064146218028084 -1.91921071730996 0.0558358382458748 . cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.85193127752835 0.7804879855778 7.49778521343431 6.27006331398558e-13 *** df.mm.trans1 -0.733536313321121 0.661065170697568 -1.10962783373851 0.267982323757211 df.mm.trans2 -0.365368247777228 0.661065170697568 -0.552696260478652 0.580852513915463 df.mm.exp2 -0.925071457530225 0.920613402791887 -1.00484248298452 0.315722553441009 df.mm.exp3 -0.679365909128035 0.920613402791888 -0.737949183737455 0.461079466013368 df.mm.exp4 0.909631706856536 0.920613402791888 0.988071327332354 0.323855014264724 df.mm.exp5 -0.339356517045367 0.920613402791887 -0.368620004896976 0.712651724990461 df.mm.exp6 -0.725693854562353 0.920613402791887 -0.78827209376008 0.431113916279884 df.mm.exp7 -0.860554151361184 0.920613402791887 -0.934761702090622 0.350607259658341 df.mm.exp8 -0.459347139359488 0.920613402791888 -0.498957692736663 0.618147782462004 df.mm.trans1:exp2 0.948813199918613 0.79727459388221 1.19007078263777 0.2348898440497 df.mm.trans2:exp2 0.614273182797019 0.79727459388221 0.770466270354742 0.441584786629796 df.mm.trans1:exp3 0.786962319778543 0.79727459388221 0.98706559298039 0.324347021892783 df.mm.trans2:exp3 0.456397928100683 0.79727459388221 0.572447600366043 0.567415773667049 df.mm.trans1:exp4 -0.627977189407285 0.79727459388221 -0.787654835894674 0.431474462633736 df.mm.trans2:exp4 -1.28370771084351 0.79727459388221 -1.61011992692842 0.108345475457331 df.mm.trans1:exp5 0.581539538726783 0.79727459388221 0.729409344270037 0.466278269798932 df.mm.trans2:exp5 -0.304043028902686 0.79727459388221 -0.381352963252214 0.703191313513914 df.mm.trans1:exp6 1.11157946612393 0.79727459388221 1.39422411632516 0.164205271838874 df.mm.trans2:exp6 -0.377264529081843 0.79727459388221 -0.473192714250193 0.636394333771583 df.mm.trans1:exp7 0.752572394411087 0.79727459388221 0.943931237977303 0.345908130234265 df.mm.trans2:exp7 0.423249381969991 0.79727459388221 0.530870273827541 0.595872375965882 df.mm.trans1:exp8 0.835368574424711 0.79727459388221 1.04778025141502 0.295520842448694 df.mm.trans2:exp8 0.481890268951601 0.79727459388221 0.604421955307905 0.545986153729777 df.mm.trans1:probe2 -0.288621283460981 0.398637296941105 -0.724019768535662 0.46957604073006 df.mm.trans1:probe3 0.0951422454028057 0.398637296941105 0.238668699925642 0.811513374059519 df.mm.trans1:probe4 -0.360836893401317 0.398637296941105 -0.90517594858824 0.366044775205535 df.mm.trans1:probe5 0.144637088124772 0.398637296941105 0.362828790067130 0.716969361640514 df.mm.trans1:probe6 0.237164310310561 0.398637296941105 0.59493758394012 0.552300455099264 df.mm.trans2:probe2 -0.115195541028351 0.398637296941105 -0.288973314620309 0.772786602787733 df.mm.trans2:probe3 0.00509451116432195 0.398637296941105 0.0127798156454854 0.98981132547302 df.mm.trans2:probe4 -0.0337690258514403 0.398637296941105 -0.0847111550037159 0.93254334575041 df.mm.trans2:probe5 -0.0156736642418236 0.398637296941105 -0.0393181078692173 0.96866098534218 df.mm.trans2:probe6 -0.566437140440415 0.398637296941105 -1.42093362760309 0.156297743238516 df.mm.trans3:probe2 0.410188742053525 0.398637296941105 1.02897733152682 0.304257861814382 df.mm.trans3:probe3 0.32982189101754 0.398637296941105 0.827373388161088 0.408634409815973