chr18.11107_chr18_35840804_35842168_-_0.R fitVsDatCorrelation=0.82652629508381 cont.fitVsDatCorrelation=0.241893725176126 fstatistic=6775.79994395819,39,393 cont.fstatistic=2273.68608227187,39,393 residuals=-0.78491328590782,-0.0794802387258016,-0.00473673826598878,0.0765182988388417,0.86736543995021 cont.residuals=-0.513985317832128,-0.210303601979047,-0.0470497830190139,0.175958217713957,1.10833503441648 predictedValues: Include Exclude Both chr18.11107_chr18_35840804_35842168_-_0.R.tl.Lung 78.4394241818574 57.0287245765818 66.6219743382315 chr18.11107_chr18_35840804_35842168_-_0.R.tl.cerebhem 89.9506493150884 76.0834733689539 68.871943594411 chr18.11107_chr18_35840804_35842168_-_0.R.tl.cortex 68.6525176480738 57.6565265389985 60.2440649053218 chr18.11107_chr18_35840804_35842168_-_0.R.tl.heart 83.00245824935 59.4735280083838 59.8795131026997 chr18.11107_chr18_35840804_35842168_-_0.R.tl.kidney 86.5357847617736 59.052136188784 68.1472369389408 chr18.11107_chr18_35840804_35842168_-_0.R.tl.liver 83.6622995138415 57.6877900580506 67.2530330589086 chr18.11107_chr18_35840804_35842168_-_0.R.tl.stomach 83.9089458086582 57.8260700545754 61.577650097847 chr18.11107_chr18_35840804_35842168_-_0.R.tl.testicle 82.3308703033405 60.747112112628 64.6030908687179 diffExp=21.4106996052757,13.8671759461345,10.9959911090753,23.5289302409662,27.4836485729896,25.9745094557909,26.0828757540827,21.5837581907126 diffExpScore=0.994183597835907 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=0,0,0,0,1,1,1,0 diffExp1.4Score=0.75 diffExp1.3=1,0,0,1,1,1,1,1 diffExp1.3Score=0.857142857142857 diffExp1.2=1,0,0,1,1,1,1,1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 66.605811579692 77.4592984554424 62.2865707910721 cerebhem 72.5451985998597 69.3840938985411 69.5585191950891 cortex 67.3355173427512 69.1872949071178 68.4433582972461 heart 69.5567860290201 67.3005811554387 63.1831741349991 kidney 65.1643847734246 73.2977407315919 65.8196772018793 liver 74.3839263892983 72.1495337403227 71.9758426957061 stomach 69.2786972306986 74.2876179087288 64.577730567282 testicle 67.9798921097995 69.3081966103187 66.1155279519772 cont.diffExp=-10.8534868757504,3.16110470131861,-1.8517775643666,2.25620487358142,-8.1333559581673,2.23439264897559,-5.00892067803025,-1.32830450051921 cont.diffExpScore=1.69690628260447 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=0.557045385924839 cont.tran.correlation=-0.285869984528839 tran.covariance=0.00412534128701893 cont.tran.covariance=-0.000591003992419306 tran.mean=71.3773944180587 cont.tran.mean=70.3265357163779 weightedLogRatios: wLogRatio Lung 1.33977810024631 cerebhem 0.73929536299179 cortex 0.722965846902767 heart 1.41742400522142 kidney 1.63153117126586 liver 1.57653083250154 stomach 1.57985531327897 testicle 1.29476801529912 cont.weightedLogRatios: wLogRatio Lung -0.645247479792743 cerebhem 0.189878309923403 cortex -0.114574316754593 heart 0.139339373806255 kidney -0.498191628914447 liver 0.130962637135833 stomach -0.298287430234322 testicle -0.0818341303935129 varWeightedLogRatios=0.132322932292958 cont.varWeightedLogRatios=0.0960731423034864 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.50100349445293 0.0887037086814525 50.741998968912 1.26270465797686e-174 *** df.mm.trans1 -0.139307862598917 0.072426274854015 -1.92344370713129 0.0551464552928314 . df.mm.trans2 -0.409497102064204 0.072426274854015 -5.65398542020284 3.01936310047185e-08 *** df.mm.exp2 0.391996086868354 0.0984079292230146 3.98337908300054 8.09640821842352e-05 *** df.mm.exp3 -0.0216900776205693 0.0984079292230145 -0.220409857130666 0.825666422407377 df.mm.exp4 0.205219829525994 0.0984079292230146 2.08539932855329 0.0376777644367372 * df.mm.exp5 0.110460856351331 0.0984079292230146 1.12247922726838 0.262344027395303 df.mm.exp6 0.0665246005634032 0.0984079292230145 0.676008540050096 0.499432833091261 df.mm.exp7 0.160025690704423 0.0984079292230146 1.62614630719206 0.104720084198124 df.mm.exp8 0.142356146987519 0.0984079292230145 1.44659224222581 0.148808245736168 df.mm.trans1:exp2 -0.255061568302806 0.080349737746769 -3.17439204477132 0.00161978746244631 ** df.mm.trans2:exp2 -0.103720096346771 0.080349737746769 -1.29085793252563 0.197511784354899 df.mm.trans1:exp3 -0.111578777586142 0.080349737746769 -1.38866386767552 0.165721486914982 df.mm.trans2:exp3 0.0326384467848286 0.080349737746769 0.406204770545639 0.68481324009706 df.mm.trans1:exp4 -0.148676265133316 0.080349737746769 -1.85036403730259 0.0650114293655914 . df.mm.trans2:exp4 -0.163243604236697 0.080349737746769 -2.03166318664507 0.0428600520530969 * df.mm.trans1:exp5 -0.0122294917218469 0.080349737746769 -0.152203256224551 0.879104732125852 df.mm.trans2:exp5 -0.0755952192697959 0.080349737746769 -0.940827206033235 0.347371340475903 df.mm.trans1:exp6 -0.00206280893514041 0.080349737746769 -0.0256728770122633 0.979531288393912 df.mm.trans2:exp6 -0.0550341410605801 0.080349737746769 -0.684932429201278 0.493790317024153 df.mm.trans1:exp7 -0.0926201186864107 0.080349737746769 -1.15271214671930 0.249729203822382 df.mm.trans2:exp7 -0.146141058546606 0.080349737746769 -1.81881189217051 0.069701072083804 . df.mm.trans1:exp8 -0.0939366752465465 0.080349737746769 -1.16909747163828 0.243072971142974 df.mm.trans2:exp8 -0.0791916839769767 0.080349737746769 -0.985587336035345 0.32494203754394 df.mm.trans1:probe2 -0.0456231447129694 0.0492039646115073 -0.927224972076734 0.354378819287574 df.mm.trans1:probe3 0.0392335773239415 0.0492039646115073 0.797366180422908 0.425719877607141 df.mm.trans1:probe4 0.0798553952063917 0.0492039646115073 1.62294635883296 0.105402713726994 df.mm.trans1:probe5 0.0153598751050937 0.0492039646115073 0.312167428506392 0.755078841983091 df.mm.trans1:probe6 -0.0812533600421076 0.0492039646115073 -1.65135798880534 0.0994642850330052 . df.mm.trans2:probe2 -0.148256791682063 0.0492039646115073 -3.01310662367623 0.0027532987130756 ** df.mm.trans2:probe3 -0.0256620376883223 0.0492039646115073 -0.52154410505207 0.602281573194134 df.mm.trans2:probe4 -0.0941134612912431 0.0492039646115073 -1.91272109949516 0.0565103133898252 . df.mm.trans2:probe5 -0.10751772936066 0.0492039646115073 -2.18514362022598 0.0294682064754013 * df.mm.trans2:probe6 -0.199865718568571 0.0492039646115073 -4.06198403211250 5.87578335040276e-05 *** df.mm.trans3:probe2 0.494471985698414 0.0492039646115073 10.0494338129569 2.67504877382461e-21 *** df.mm.trans3:probe3 0.0960935219845144 0.0492039646115073 1.95296299278374 0.0515333663190242 . df.mm.trans3:probe4 0.113871350452763 0.0492039646115073 2.31427185495805 0.0211677129712943 * df.mm.trans3:probe5 0.771112130739032 0.0492039646115073 15.6717479338788 2.40096667589639e-43 *** df.mm.trans3:probe6 0.00546664125607993 0.0492039646115073 0.111101641894959 0.91159246409218 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.54043544025091 0.152904141480063 29.6946531094642 1.83922725344139e-102 *** df.mm.trans1 -0.301520097010167 0.124845708728161 -2.41514185855356 0.0161847072528812 * df.mm.trans2 -0.157125014945225 0.124845708728161 -1.25855359023472 0.208938751022241 df.mm.exp2 -0.135099564267941 0.169631914565282 -0.796427751311788 0.426264289657665 df.mm.exp3 -0.196300033335042 0.169631914565282 -1.15721168294364 0.24788874712861 df.mm.exp4 -0.111524284082407 0.169631914565282 -0.657448713988823 0.511277299268923 df.mm.exp5 -0.132274585612661 0.169631914565282 -0.779774171338234 0.435993156008436 df.mm.exp6 -0.105148452871813 0.169631914565282 -0.619862442402294 0.535707577029822 df.mm.exp7 -0.0385864821856008 0.169631914565282 -0.227471830902144 0.820175160026418 df.mm.exp8 -0.150427108196167 0.169631914565282 -0.886785417600622 0.375736774249363 df.mm.trans1:exp2 0.220517526145381 0.138503878258777 1.59213972141179 0.112157291403297 df.mm.trans2:exp2 0.0250045937828561 0.138503878258777 0.180533527993621 0.856826793564967 df.mm.trans1:exp3 0.207196042629877 0.138503878258777 1.49595841816615 0.135467083058061 df.mm.trans2:exp3 0.0833646623108267 0.138503878258777 0.601894065053328 0.54759172446257 df.mm.trans1:exp4 0.154875933507214 0.138503878258777 1.11820647518511 0.264161873788603 df.mm.trans2:exp4 -0.0290594611911725 0.138503878258777 -0.209809729203962 0.833924901937353 df.mm.trans1:exp5 0.110395824796640 0.138503878258777 0.797059448330963 0.425897777647028 df.mm.trans2:exp5 0.0770517546313464 0.138503878258777 0.556314780495784 0.578312294433365 df.mm.trans1:exp6 0.215596493519918 0.138503878258777 1.55660979483262 0.120368054266488 df.mm.trans2:exp6 0.0341366585219794 0.138503878258777 0.246467167209566 0.805449300713702 df.mm.trans1:exp7 0.0779321071605351 0.138503878258777 0.562670938462306 0.573979799677612 df.mm.trans2:exp7 -0.00322184711138779 0.138503878258777 -0.0232617826438634 0.981453262667861 df.mm.trans1:exp8 0.170847230679827 0.138503878258777 1.23351947127877 0.218119246704395 df.mm.trans2:exp8 0.0392376674197601 0.138503878258777 0.283296525072384 0.777098710644508 df.mm.trans1:probe2 -0.0474745715830165 0.0848159572826411 -0.559736317363158 0.575978182749401 df.mm.trans1:probe3 -0.166950333126027 0.0848159572826412 -1.96838352681301 0.0497263925565621 * df.mm.trans1:probe4 -0.0817896137259435 0.0848159572826412 -0.964318700706134 0.335479159106768 df.mm.trans1:probe5 -0.137777124124998 0.0848159572826411 -1.62442456041461 0.105086936923505 df.mm.trans1:probe6 -0.04749045998095 0.0848159572826412 -0.559923645295809 0.57585051996222 df.mm.trans2:probe2 -0.0407446888849074 0.0848159572826411 -0.480389424234518 0.631217800649826 df.mm.trans2:probe3 -0.0385121574709553 0.0848159572826411 -0.454067356011997 0.650031007044132 df.mm.trans2:probe4 -0.0677053015844091 0.0848159572826411 -0.798261362054638 0.425200934617608 df.mm.trans2:probe5 -0.0913391579832345 0.0848159572826411 -1.07691006397364 0.28218105701578 df.mm.trans2:probe6 -0.164392391545781 0.0848159572826412 -1.93822479651982 0.0533116277541885 . df.mm.trans3:probe2 0.0203992907661554 0.0848159572826411 0.240512415584449 0.810058452241057 df.mm.trans3:probe3 0.0199895507799434 0.0848159572826411 0.235681485187158 0.81380260560446 df.mm.trans3:probe4 0.054307206912451 0.0848159572826411 0.640294688079477 0.522354160928709 df.mm.trans3:probe5 0.0735516571890921 0.0848159572826411 0.867191263832443 0.38636639065637 df.mm.trans3:probe6 0.131485397171157 0.0848159572826412 1.55024362612561 0.121887938153154