chr15.8615_chr15_100435794_100439525_-_0.R fitVsDatCorrelation=0.930394190824175 cont.fitVsDatCorrelation=0.370103211500688 fstatistic=4342.96895877008,36,324 cont.fstatistic=668.570671075673,36,324 residuals=-1.04879781034839,-0.100260762664118,-0.00371893778706795,0.114189452958067,0.85916273038926 cont.residuals=-1.30336509930824,-0.435098440236461,-0.078523737071997,0.383569874740334,1.68551909794582 predictedValues: Include Exclude Both chr15.8615_chr15_100435794_100439525_-_0.R.tl.Lung 210.144353611289 87.9943055605887 75.3886494798969 chr15.8615_chr15_100435794_100439525_-_0.R.tl.cerebhem 303.690541691307 104.489577704266 235.866747265288 chr15.8615_chr15_100435794_100439525_-_0.R.tl.cortex 362.883805960347 162.946473402861 257.950781944600 chr15.8615_chr15_100435794_100439525_-_0.R.tl.heart 150.189401186110 82.7267533205147 59.5028921452066 chr15.8615_chr15_100435794_100439525_-_0.R.tl.kidney 205.344412515363 92.7923412080456 64.3904389762392 chr15.8615_chr15_100435794_100439525_-_0.R.tl.liver 188.162245100324 88.7999334955716 56.3802587791915 chr15.8615_chr15_100435794_100439525_-_0.R.tl.stomach 143.820632041856 84.8266807872025 61.9352929299513 chr15.8615_chr15_100435794_100439525_-_0.R.tl.testicle 162.704958842906 88.1620830830087 59.9181413557198 diffExp=122.1500480507,199.200963987040,199.937332557486,67.462647865595,112.552071307317,99.3623116047525,58.9939512546538,74.5428757598978 diffExpScore=0.998930712526717 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 160.900180978167 119.338853816312 121.802819183833 cerebhem 125.136638629374 90.1392799897348 108.194853421516 cortex 170.573051168726 133.849201376006 107.119711867664 heart 121.072661238482 123.064914333395 102.484141703271 kidney 138.212196338427 131.365041606318 110.303872353012 liver 159.428051347558 84.9516318582156 113.048210189081 stomach 189.938840642907 92.8774417043633 164.688697222777 testicle 138.177036963749 140.384606592213 125.481251193641 cont.diffExp=41.5613271618545,34.9973586396389,36.7238497927198,-1.99225309491366,6.84715473210875,74.4764194893428,97.061398938544,-2.20756962846374 cont.diffExpScore=1.02565155754036 cont.diffExp1.5=0,0,0,0,0,1,1,0 cont.diffExp1.5Score=0.666666666666667 cont.diffExp1.4=0,0,0,0,0,1,1,0 cont.diffExp1.4Score=0.666666666666667 cont.diffExp1.3=1,1,0,0,0,1,1,0 cont.diffExp1.3Score=0.8 cont.diffExp1.2=1,1,1,0,0,1,1,0 cont.diffExp1.2Score=0.833333333333333 tran.correlation=0.891383628771002 cont.tran.correlation=-0.229860481410813 tran.covariance=0.0642405550828023 cont.tran.covariance=-0.00654218736728742 tran.mean=157.479906219472 cont.tran.mean=132.463101786497 weightedLogRatios: wLogRatio Lung 4.27647129626362 cerebhem 5.52937423899022 cortex 4.39863274674918 heart 2.81104642715768 kidney 3.91405503787363 liver 3.65085049162 stomach 2.48381943901295 testicle 2.932405623953 cont.weightedLogRatios: wLogRatio Lung 1.47357994345809 cerebhem 1.53047930818091 cortex 1.21659851347564 heart -0.078415581032833 kidney 0.249141652412049 liver 2.99447991516528 stomach 3.49768880305306 testicle -0.0782434288097828 varWeightedLogRatios=1.00773143130475 cont.varWeightedLogRatios=1.81066543829036 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.0471174305193 0.132845459174904 37.9923970444053 2.13387117933106e-121 *** df.mm.trans1 0.228500031665928 0.112518716198868 2.03077354048433 0.043094206947649 * df.mm.trans2 -0.553820212971014 0.112518716198869 -4.92202747845236 1.36627521549646e-06 *** df.mm.exp2 -0.600580525093253 0.156695954936347 -3.83277618964203 0.000152198618163153 *** df.mm.exp3 -0.0676744162525555 0.156695954936348 -0.431883619969934 0.666113262765966 df.mm.exp4 -0.1609947678181 0.156695954936347 -1.02743410245337 0.304982518175375 df.mm.exp5 0.187677508496930 0.156695954936347 1.19771763459476 0.231902428292368 df.mm.exp6 0.189161352712662 0.156695954936347 1.20718721034951 0.228240613342946 df.mm.exp7 -0.219323209338476 0.156695954936347 -1.39967371479097 0.162567770958946 df.mm.exp8 -0.0242739234795504 0.156695954936347 -0.154910977053689 0.876987956754551 df.mm.trans1:exp2 0.968795060352064 0.135702677645139 7.13910054807803 6.20948369115659e-12 *** df.mm.trans2:exp2 0.77239575379117 0.135702677645139 5.69182397278099 2.81590644274058e-08 *** df.mm.trans1:exp3 0.613962412786742 0.135702677645139 4.52432054724999 8.51577588415054e-06 *** df.mm.trans2:exp3 0.683824076252256 0.135702677645139 5.0391347327755 7.78847417299571e-07 *** df.mm.trans1:exp4 -0.174902752731275 0.135702677645139 -1.28886736626262 0.198363681550855 df.mm.trans2:exp4 0.0992657131219966 0.135702677645139 0.73149413736386 0.46500610068342 df.mm.trans1:exp5 -0.210783570748380 0.135702677645139 -1.55327495673724 0.121333682877806 df.mm.trans2:exp5 -0.134585505041975 0.135702677645139 -0.991767497719645 0.322051037458983 df.mm.trans1:exp6 -0.299651448921933 0.135702677645138 -2.20814691442950 0.0279340299395952 * df.mm.trans2:exp6 -0.180047554484251 0.135702677645139 -1.32677967456968 0.185515897312164 df.mm.trans1:exp7 -0.159904571040501 0.135702677645139 -1.17834499521557 0.239523792510471 df.mm.trans2:exp7 0.182661231728958 0.135702677645139 1.34603999640019 0.179230654988556 df.mm.trans1:exp8 -0.231582277032068 0.135702677645139 -1.70654169137070 0.0888654465450048 . df.mm.trans2:exp8 0.0261787941963494 0.135702677645139 0.192912878733364 0.847148066701863 df.mm.trans1:probe2 0.278368975570824 0.0678513388225693 4.10263055086882 5.17264772371129e-05 *** df.mm.trans1:probe3 -0.186252143649803 0.0678513388225693 -2.74500322148175 0.00638858352382398 ** df.mm.trans1:probe4 0.0520051273520153 0.0678513388225693 0.766456907917592 0.443962550909972 df.mm.trans1:probe5 0.170865167717931 0.0678513388225693 2.51822838993262 0.0122761402496204 * df.mm.trans1:probe6 0.334607947791069 0.0678513388225693 4.93148629927652 1.30614622679008e-06 *** df.mm.trans2:probe2 -0.0336223111404404 0.0678513388225693 -0.495529074648954 0.620562625295885 df.mm.trans2:probe3 -0.0379025174790404 0.0678513388225693 -0.55861119525077 0.576812943949703 df.mm.trans2:probe4 0.00147445096357539 0.0678513388225693 0.0217306097294715 0.982676222960262 df.mm.trans2:probe5 0.0202576764563052 0.0678513388225693 0.298559716106396 0.765467393335391 df.mm.trans2:probe6 -0.0944333311237924 0.0678513388225693 -1.3917681325454 0.164947316230765 df.mm.trans3:probe2 -0.617981865675776 0.0678513388225693 -9.10788020398233 8.88525239914379e-18 *** df.mm.trans3:probe3 -0.579439703126511 0.0678513388225693 -8.5398418539941 5.31299751368511e-16 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.02868009668402 0.336676116651695 14.9362543048648 9.58868739607573e-39 *** df.mm.trans1 0.114425026831769 0.285161153838109 0.40126442641879 0.688489964812187 df.mm.trans2 -0.414212845685892 0.285161153838109 -1.45255705453151 0.147314512168511 df.mm.exp2 -0.413519156451308 0.397121481838082 -1.04129133114968 0.298516732651431 df.mm.exp3 0.30158281392411 0.397121481838082 0.759422060293062 0.448152286173275 df.mm.exp4 -0.0809528605467905 0.397121481838082 -0.20384910977895 0.838599390622571 df.mm.exp5 0.0431835152773467 0.397121481838082 0.108741322875487 0.91347497805844 df.mm.exp6 -0.27448721274143 0.397121481838082 -0.69119205405601 0.489939782628545 df.mm.exp7 -0.386421721930707 0.397121481838082 -0.97305670834564 0.33125100821312 df.mm.exp8 -0.0195824045459693 0.397121481838082 -0.0493108669300181 0.960701942864933 df.mm.trans1:exp2 0.162141226995618 0.343917291660299 0.471454128441357 0.637633772324059 df.mm.trans2:exp2 0.132908228300011 0.343917291660299 0.386454044396493 0.699414098232084 df.mm.trans1:exp3 -0.243203335141969 0.343917291660299 -0.707156461857087 0.479977547660982 df.mm.trans2:exp3 -0.186835968228216 0.343917291660300 -0.543258430904256 0.587325433472965 df.mm.trans1:exp4 -0.203440446769279 0.343917291660300 -0.591538871997821 0.554571909072623 df.mm.trans2:exp4 0.111697877818465 0.343917291660299 0.324781220738368 0.74555625781809 df.mm.trans1:exp5 -0.195177535258585 0.343917291660299 -0.56751300382817 0.570758707397274 df.mm.trans2:exp5 0.0528295520696029 0.343917291660300 0.153611212203266 0.878011925302398 df.mm.trans1:exp6 0.265295765680837 0.343917291660299 0.77139408838704 0.441035587072349 df.mm.trans2:exp6 -0.0653976873865326 0.343917291660300 -0.190155275621118 0.849306538303722 df.mm.trans1:exp7 0.552339672135609 0.343917291660299 1.6060247202725 0.109242622606786 df.mm.trans2:exp7 0.135735557151862 0.343917291660299 0.394675000191422 0.693342429921777 df.mm.trans1:exp8 -0.132666034715267 0.343917291660299 -0.385749823961472 0.699935112924131 df.mm.trans2:exp8 0.182001292777075 0.343917291660300 0.529200761899594 0.597028562323998 df.mm.trans1:probe2 -0.0525869306867583 0.171958645830150 -0.305811495740089 0.759944568820876 df.mm.trans1:probe3 0.0690896273400806 0.171958645830150 0.401780480455302 0.688110481853938 df.mm.trans1:probe4 -0.0927100698981325 0.171958645830150 -0.539141660778754 0.590159382239972 df.mm.trans1:probe5 -0.155674814593404 0.171958645830150 -0.905303794652875 0.365977162993304 df.mm.trans1:probe6 -0.329006314745021 0.171958645830150 -1.91328742533826 0.0565923927707848 . df.mm.trans2:probe2 0.379812969158468 0.171958645830150 2.20874598846064 0.0278918937802839 * df.mm.trans2:probe3 0.221779765881925 0.171958645830150 1.28972733421607 0.198065186159173 df.mm.trans2:probe4 0.149071671379103 0.171958645830150 0.866904194665193 0.386636053582348 df.mm.trans2:probe5 0.475045255159968 0.171958645830150 2.76255522289463 0.00606257750004061 ** df.mm.trans2:probe6 0.281787698675543 0.171958645830150 1.63869456702908 0.102247537438251 df.mm.trans3:probe2 0.113337485821096 0.171958645830150 0.659097338630152 0.510301412588449 df.mm.trans3:probe3 0.107196183738442 0.171958645830150 0.623383507243504 0.533471114612391