chr2.13198_chr2_26919142_26921434_+_0.R fitVsDatCorrelation=0.792536824549739 cont.fitVsDatCorrelation=0.221074240587488 fstatistic=7752.49160748363,47,577 cont.fstatistic=3023.70732267874,47,577 residuals=-0.623522985698342,-0.106314549734901,-0.00500843310951494,0.090388911455966,0.906619911129207 cont.residuals=-0.507160942794356,-0.200493878538467,-0.0366782639996475,0.142687283296791,1.63018424274302 predictedValues: Include Exclude Both chr2.13198_chr2_26919142_26921434_+_0.R.tl.Lung 81.5573629381438 76.9186065497061 70.2795251120772 chr2.13198_chr2_26919142_26921434_+_0.R.tl.cerebhem 137.133011339108 66.1571453241065 97.7871963249846 chr2.13198_chr2_26919142_26921434_+_0.R.tl.cortex 127.191475269240 66.7824715091537 92.4919112203775 chr2.13198_chr2_26919142_26921434_+_0.R.tl.heart 92.9427048187583 73.6531797561672 78.9683436319443 chr2.13198_chr2_26919142_26921434_+_0.R.tl.kidney 79.9499940661366 75.9079319309397 69.4766092422966 chr2.13198_chr2_26919142_26921434_+_0.R.tl.liver 76.4908703379493 71.6931431928279 69.9601947830579 chr2.13198_chr2_26919142_26921434_+_0.R.tl.stomach 75.2806863549614 72.3598233954675 74.849182159214 chr2.13198_chr2_26919142_26921434_+_0.R.tl.testicle 71.3627382723194 72.3817386867428 68.0631709034551 diffExp=4.6387563884377,70.9758660150011,60.4090037600859,19.2895250625911,4.04206213519682,4.7977271451214,2.92086295949387,-1.01900041442336 diffExpScore=1.00621353477952 diffExp1.5=0,1,1,0,0,0,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,1,1,0,0,0,0,0 diffExp1.4Score=0.666666666666667 diffExp1.3=0,1,1,0,0,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=0,1,1,1,0,0,0,0 diffExp1.2Score=0.75 cont.predictedValues: Include Exclude Both Lung 78.1724883515302 78.8861810403797 77.7057312030543 cerebhem 80.1657903519107 76.5317755642715 86.5644379351544 cortex 77.7340849656964 88.3603978010076 81.553731272142 heart 83.0886014799179 82.6328874877278 73.8204247484475 kidney 71.1398057496071 72.4268020067381 77.1739580102364 liver 85.6183042819464 77.9091755099607 79.0471511528396 stomach 77.143164202856 72.9750282341889 77.6336732843957 testicle 79.8083673224877 72.9363781178686 78.978909702363 cont.diffExp=-0.713692688849534,3.63401478763912,-10.6263128353112,0.455713992190084,-1.28699625713104,7.70912877198575,4.16813596866703,6.87198920461903 cont.diffExpScore=3.16322197514752 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=-0.811508599583124 cont.tran.correlation=0.312021228586363 tran.covariance=-0.0107297190705680 cont.tran.covariance=0.00129677867655801 tran.mean=82.360180233858 cont.tran.mean=78.470577029256 weightedLogRatios: wLogRatio Lung 0.256020699355502 cerebhem 3.32131112328036 cortex 2.91432163889938 heart 1.02715632242177 kidney 0.225962119695613 liver 0.278847847772429 stomach 0.170218170654394 testicle -0.060609801773725 cont.weightedLogRatios: wLogRatio Lung -0.0396564203437765 cerebhem 0.202305917027955 cortex -0.56599639126557 heart 0.0242933566304099 kidney -0.0766232444548475 liver 0.415420380096434 stomach 0.239840088830865 testicle 0.390291671176237 varWeightedLogRatios=1.79110896001324 cont.varWeightedLogRatios=0.101177764461263 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.39779768611276 0.0891906982642589 49.3078064383209 4.70408981392609e-209 *** df.mm.trans1 0.0209187059214001 0.070712612423417 0.295827083804257 0.767468570475926 df.mm.trans2 -0.0746393431176274 0.070712612423417 -1.05553083897817 0.291624368315172 df.mm.exp2 0.0386166795168142 0.0939768694656378 0.410916853651251 0.681286064914694 df.mm.exp3 0.0284391682930647 0.0939768694656378 0.302618808806601 0.762289439447842 df.mm.exp4 -0.0292704278692158 0.0939768694656377 -0.311464172361247 0.75556027642508 df.mm.exp5 -0.0216415004035888 0.0939768694656377 -0.230285393912828 0.817951629935867 df.mm.exp6 -0.129933842662619 0.0939768694656377 -1.38261514137933 0.167317778156724 df.mm.exp7 -0.204174263092309 0.0939768694656377 -2.17260123957379 0.0302166382220991 * df.mm.exp8 -0.162280269299513 0.0939768694656377 -1.72681075909695 0.084736866620278 . df.mm.trans1:exp2 0.481028048593933 0.0720769686416237 6.67381075618855 5.85786374719336e-11 *** df.mm.trans2:exp2 -0.189331582774016 0.0720769686416236 -2.62679724664058 0.00884827919975371 ** df.mm.trans1:exp3 0.415947849643919 0.0720769686416236 5.77088434048978 1.28786734967681e-08 *** df.mm.trans2:exp3 -0.169746329719665 0.0720769686416236 -2.35507032161225 0.0188530864114925 * df.mm.trans1:exp4 0.159947041551648 0.0720769686416236 2.21911443511069 0.0268671310860622 * df.mm.trans2:exp4 -0.0141100612534439 0.0720769686416236 -0.195763799718062 0.844863966267038 df.mm.trans1:exp5 0.00173625306424594 0.0720769686416236 0.0240888746706153 0.980790045698976 df.mm.trans2:exp5 0.0084148793858267 0.0720769686416236 0.116748519595304 0.907099963839959 df.mm.trans1:exp6 0.0657986219860745 0.0720769686416236 0.912893858137043 0.361679639794137 df.mm.trans2:exp6 0.0595811488179337 0.0720769686416236 0.826632278532401 0.408787211951547 df.mm.trans1:exp7 0.124091263289584 0.0720769686416236 1.72164930945671 0.0856690341141132 . df.mm.trans2:exp7 0.143077678000837 0.0720769686416236 1.98506791694083 0.0476099704327135 * df.mm.trans1:exp8 0.0287495170856494 0.0720769686416236 0.398872450207997 0.690134761632194 df.mm.trans2:exp8 0.101486503814621 0.0720769686416236 1.40802957903551 0.159660853131147 df.mm.trans1:probe2 -0.204818254311015 0.0522247253654525 -3.92186369344712 9.84362977448089e-05 *** df.mm.trans1:probe3 -0.208942553810831 0.0522247253654525 -4.00083585598039 7.13373389317543e-05 *** df.mm.trans1:probe4 0.0949056144323477 0.0522247253654525 1.81725444735664 0.0696967344071159 . df.mm.trans1:probe5 -0.181914090256993 0.0522247253654525 -3.48329433968326 0.000532820939911088 *** df.mm.trans1:probe6 0.15257369125565 0.0522247253654525 2.92148384099651 0.0036199991334315 ** df.mm.trans2:probe2 -0.185716628032916 0.0522247253654525 -3.55610540282077 0.000407282262897815 *** df.mm.trans2:probe3 0.0611991256219826 0.0522247253654525 1.17184198085734 0.241744140160587 df.mm.trans2:probe4 0.264309928389217 0.0522247253654525 5.06101136080004 5.61539873575318e-07 *** df.mm.trans2:probe5 0.107303632675524 0.0522247253654525 2.05465192827049 0.0403624126556886 * df.mm.trans2:probe6 0.14469318100438 0.0522247253654525 2.77058768604070 0.00577582158121929 ** df.mm.trans3:probe2 -0.360596082793549 0.0522247253654525 -6.90470041288314 1.33115203626616e-11 *** df.mm.trans3:probe3 -0.0178965453266186 0.0522247253654525 -0.342683378445442 0.731961468583686 df.mm.trans3:probe4 -0.271527344626344 0.0522247253654525 -5.19921057940045 2.78274527052951e-07 *** df.mm.trans3:probe5 0.324731118780041 0.0522247253654525 6.2179574235704 9.66912093024736e-10 *** df.mm.trans3:probe6 0.0302207787678922 0.0522247253654525 0.578668026617977 0.563038996839953 df.mm.trans3:probe7 0.076286144793603 0.0522247253654525 1.46072850091171 0.144634263370645 df.mm.trans3:probe8 -0.171216732545866 0.0522247253654525 -3.27846113785653 0.00110654858125874 ** df.mm.trans3:probe9 -0.202655427288726 0.0522247253654525 -3.88044984192076 0.000116289996167403 *** df.mm.trans3:probe10 0.0147807530604443 0.0522247253654525 0.283022130935360 0.777261379073922 df.mm.trans3:probe11 -0.154387478681515 0.0522247253654525 -2.95621427592312 0.00324170304690051 ** df.mm.trans3:probe12 -0.108911655469589 0.0522247253654525 -2.08544237825013 0.0374680118579376 * df.mm.trans3:probe13 -0.0964052218166464 0.0522247253654525 -1.84596895707986 0.0654087508476238 . df.mm.trans3:probe14 -0.344773904727494 0.0522247253654525 -6.60173705682266 9.22481907308074e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.41752880311046 0.142637618231697 30.9702928152847 8.61729252772497e-125 *** df.mm.trans1 -0.0595532564173952 0.113086664992051 -0.526616081759785 0.598662598321865 df.mm.trans2 -0.0492503304255858 0.113086664992051 -0.435509619361821 0.663355424712138 df.mm.exp2 -0.113081018976957 0.150291870007943 -0.752409421554073 0.452111714857958 df.mm.exp3 0.0594608070424958 0.150291870007943 0.395635552604097 0.692520143039545 df.mm.exp4 0.158685003361952 0.150291870007943 1.05584555807020 0.291480659419165 df.mm.exp5 -0.172833434567036 0.150291870007943 -1.14998525574205 0.2506263471468 df.mm.exp6 0.0614034763409342 0.150291870007943 0.40856152989306 0.683013049754761 df.mm.exp7 -0.0902158188483913 0.150291870007943 -0.600270785396596 0.548561465044022 df.mm.exp8 -0.0739597961460027 0.150291870007943 -0.492107764326132 0.62283033669862 df.mm.trans1:exp2 0.138260114344096 0.115268602404493 1.19946031668644 0.23084131322596 df.mm.trans2:exp2 0.0827809731519638 0.115268602404493 0.718157168779356 0.472951061733936 df.mm.trans1:exp3 -0.0650847462006172 0.115268602404493 -0.564635510823895 0.572541139636654 df.mm.trans2:exp3 0.0539570062780361 0.115268602404493 0.468098034959197 0.639891247811382 df.mm.trans1:exp4 -0.0976952515049746 0.115268602404493 -0.847544339629876 0.3970432015692 df.mm.trans2:exp4 -0.112283315742454 0.115268602404493 -0.974101476032796 0.330414346336242 df.mm.trans1:exp5 0.0785626962571246 0.115268602404493 0.681561974538719 0.495789427730228 df.mm.trans2:exp5 0.0874037916474733 0.115268602404493 0.758261918894113 0.448603792185929 df.mm.trans1:exp6 0.029577844727147 0.115268602404493 0.256599317681969 0.797579567084456 df.mm.trans2:exp6 -0.073865811919744 0.115268602404493 -0.64081467441185 0.521897516794586 df.mm.trans1:exp7 0.0769610154612447 0.115268602404493 0.667666770099097 0.504613275041784 df.mm.trans2:exp7 0.0123270552209331 0.115268602404493 0.106942002972118 0.914872162417592 df.mm.trans1:exp8 0.0946703744806404 0.115268602404493 0.821302353857207 0.411813275488972 df.mm.trans2:exp8 -0.00445874261268812 0.115268602404493 -0.0386813279564352 0.96915783976902 df.mm.trans1:probe2 0.000678934361031872 0.0835200372225111 0.00812899974197903 0.993516877752032 df.mm.trans1:probe3 0.0135913709090941 0.0835200372225111 0.162731858857826 0.870786536228967 df.mm.trans1:probe4 0.0738923012445004 0.0835200372225111 0.88472543477967 0.376673252425492 df.mm.trans1:probe5 -0.0636522103881295 0.0835200372225111 -0.762119037597523 0.446300372443437 df.mm.trans1:probe6 -0.0056658441954153 0.0835200372225111 -0.0678381426042778 0.945937980843804 df.mm.trans2:probe2 -0.0100556156642044 0.0835200372225111 -0.120397643471046 0.904210069203807 df.mm.trans2:probe3 0.0401363513512169 0.0835200372225111 0.480559548175093 0.631011719749933 df.mm.trans2:probe4 -0.0135572703510805 0.0835200372225111 -0.16232356691798 0.871107885179694 df.mm.trans2:probe5 0.0212995382242311 0.0835200372225111 0.255023093051140 0.798796134445091 df.mm.trans2:probe6 -0.0432711118622377 0.0835200372225111 -0.518092583543232 0.604592270050711 df.mm.trans3:probe2 0.0939355115544597 0.0835200372225112 1.12470629418184 0.261181163740435 df.mm.trans3:probe3 0.102076775870553 0.0835200372225111 1.22218307444720 0.222137434670272 df.mm.trans3:probe4 0.0519885508249847 0.0835200372225111 0.622468003534034 0.533880086027755 df.mm.trans3:probe5 0.0392555057152026 0.0835200372225111 0.470013029455668 0.638523297075388 df.mm.trans3:probe6 0.0652814424317591 0.0835200372225111 0.781626117548758 0.434754932937372 df.mm.trans3:probe7 -0.0132780878482909 0.0835200372225111 -0.158980866027584 0.873739578283063 df.mm.trans3:probe8 0.00968339354383744 0.0835200372225111 0.115940962981605 0.907739669911743 df.mm.trans3:probe9 -0.00544687393719734 0.0835200372225111 -0.065216373439657 0.948024313188186 df.mm.trans3:probe10 0.075201853321 0.0835200372225111 0.900404930623414 0.368280439473368 df.mm.trans3:probe11 0.0234264630321029 0.0835200372225111 0.280489135435740 0.779202796899955 df.mm.trans3:probe12 0.036859672422068 0.0835200372225111 0.441327298787807 0.659141393217338 df.mm.trans3:probe13 0.104023570127902 0.0835200372225111 1.24549238227428 0.213456343923685 df.mm.trans3:probe14 0.0358454095437031 0.0835200372225111 0.429183352112321 0.66794999772465