chr13.6399_chr13_54165018_54165546_-_0.R fitVsDatCorrelation=0.840340730735193 cont.fitVsDatCorrelation=0.255248909181822 fstatistic=8524.92368118689,43,485 cont.fstatistic=2671.69265999399,43,485 residuals=-0.624860359156522,-0.101157207439864,0.00412433590312101,0.101236197100755,0.85077447724712 cont.residuals=-0.714333281822482,-0.249356877583027,0.0127969777508200,0.224167749768851,0.95787642099542 predictedValues: Include Exclude Both chr13.6399_chr13_54165018_54165546_-_0.R.tl.Lung 113.051057141830 125.116253224897 81.7745865132026 chr13.6399_chr13_54165018_54165546_-_0.R.tl.cerebhem 102.568959063588 91.2298534298953 83.3894249863592 chr13.6399_chr13_54165018_54165546_-_0.R.tl.cortex 106.702566253352 118.811858804621 95.0591928283519 chr13.6399_chr13_54165018_54165546_-_0.R.tl.heart 101.494378946547 101.105807017888 73.8340999448829 chr13.6399_chr13_54165018_54165546_-_0.R.tl.kidney 132.715260235840 130.447776989400 73.5697494924132 chr13.6399_chr13_54165018_54165546_-_0.R.tl.liver 121.459897290134 102.236471026636 67.7016101266205 chr13.6399_chr13_54165018_54165546_-_0.R.tl.stomach 100.029799414779 114.244522933289 76.6167273830297 chr13.6399_chr13_54165018_54165546_-_0.R.tl.testicle 103.128931094582 113.128965886684 79.9802600904541 diffExp=-12.0651960830678,11.3391056336925,-12.1092925512695,0.388571928659061,2.26748324644015,19.2234262634982,-14.21472351851,-10.0000347921017 diffExpScore=5.046660721324 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 96.6554054852383 91.7642684628308 93.0926908008672 cerebhem 91.2815546410103 83.4769106966735 96.2128328170586 cortex 91.07325808635 84.2730368434442 93.587220729578 heart 104.461673565518 91.6568265017804 86.7748630090299 kidney 100.356114327084 97.0677559506606 84.422010435972 liver 104.806029460232 92.8134616455835 92.9070298240395 stomach 95.8878723650208 95.0747568397008 89.6520776252017 testicle 88.9633331641906 91.207717894932 90.2926286115438 cont.diffExp=4.89113702240752,7.80464394433682,6.8002212429058,12.8048470637375,3.28835837642316,11.9925678146486,0.813115525319915,-2.24438473074147 cont.diffExpScore=1.07399219517000 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=0.507270450134208 cont.tran.correlation=0.566803527702119 tran.covariance=0.00581638297627206 cont.tran.covariance=0.00193188964585577 tran.mean=111.092022422123 cont.tran.mean=93.8012484956406 weightedLogRatios: wLogRatio Lung -0.484562170266915 cerebhem 0.535619416402164 cortex -0.507788943637167 heart 0.0177143034421310 kidney 0.0840897815035982 liver 0.81210467335107 stomach -0.620769764645082 testicle -0.433335582027549 cont.weightedLogRatios: wLogRatio Lung 0.236027695367322 cerebhem 0.399456425639033 cortex 0.347104241475369 heart 0.599370351025931 kidney 0.152988177780029 liver 0.557939257673429 stomach 0.0388238502201327 testicle -0.112135487186468 varWeightedLogRatios=0.282147365825412 cont.varWeightedLogRatios=0.0611385801346923 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.37306193747037 0.0862305949123242 62.3103892873926 1.31263487417521e-233 *** df.mm.trans1 -0.591232206218459 0.0690321007031743 -8.56459821149948 1.44871104497028e-16 *** df.mm.trans2 -0.540796352959581 0.0690321007031743 -7.83398371845742 3.00873718711354e-14 *** df.mm.exp2 -0.432720338782757 0.0924386857793235 -4.68116065405538 3.70707575094578e-06 *** df.mm.exp3 -0.260029710966877 0.0924386857793234 -2.81299662337952 0.00510739053630981 ** df.mm.exp4 -0.218766067578637 0.0924386857793234 -2.36660728929976 0.0183439019701388 * df.mm.exp5 0.307828610505377 0.0924386857793234 3.33008423811053 0.000934368093373468 *** df.mm.exp6 0.058646291758665 0.0924386857793234 0.634434503955084 0.526096433557688 df.mm.exp7 -0.148122564658322 0.0924386857793235 -1.60238717599178 0.109721066302044 df.mm.exp8 -0.170387796416256 0.0924386857793235 -1.84325204301388 0.0659021820834327 . df.mm.trans1:exp2 0.335416132724069 0.0725148711691757 4.62548064026136 4.80094070015365e-06 *** df.mm.trans2:exp2 0.116859191643555 0.0725148711691757 1.61152036484936 0.107716889570156 df.mm.trans1:exp3 0.202235370314531 0.0725148711691757 2.78888132949612 0.00549701815212281 ** df.mm.trans2:exp3 0.208327603605859 0.0725148711691757 2.87289490068644 0.00424561405551455 ** df.mm.trans1:exp4 0.110929934909948 0.0725148711691757 1.52975428517483 0.126729498070967 df.mm.trans2:exp4 0.00569029941705123 0.0725148711691757 0.078470792615433 0.937485926709451 df.mm.trans1:exp5 -0.147462227549670 0.0725148711691757 -2.03354463949393 0.0425413847832444 * df.mm.trans2:exp5 -0.266098971056425 0.0725148711691757 -3.66957793299559 0.000269888507415222 *** df.mm.trans1:exp6 0.0130983033032870 0.0725148711691757 0.180629201874039 0.856734084987668 df.mm.trans2:exp6 -0.260601149183231 0.0725148711691757 -3.59376145860142 0.000359250096188787 *** df.mm.trans1:exp7 0.0257511506227293 0.0725148711691757 0.355115443322686 0.722657483556354 df.mm.trans2:exp7 0.0572203230733085 0.0725148711691757 0.789083978923642 0.430448486324058 df.mm.trans1:exp8 0.0785282102695687 0.0725148711691757 1.08292559861775 0.279379536261542 df.mm.trans2:exp8 0.0696729244882483 0.0725148711691757 0.960808774323032 0.337127078615841 df.mm.trans1:probe2 -0.0299589315351937 0.0496475383674232 -0.603432365840149 0.546503193957472 df.mm.trans1:probe3 -0.0116048875211929 0.0496475383674232 -0.233745476670150 0.815281209003314 df.mm.trans1:probe4 -0.0559749720827345 0.0496475383674232 -1.12744707841271 0.260110966170462 df.mm.trans1:probe5 -0.323876518155943 0.0496475383674232 -6.52351614613904 1.73005404928836e-10 *** df.mm.trans1:probe6 -0.442427594255045 0.0496475383674232 -8.91137020693355 1.02235091065913e-17 *** df.mm.trans2:probe2 0.0334977087556942 0.0496475383674232 0.67471036545236 0.500181289819103 df.mm.trans2:probe3 0.124724190399822 0.0496475383674232 2.51219283978964 0.0123219200927002 * df.mm.trans2:probe4 -0.0999944883304478 0.0496475383674232 -2.01408753824661 0.0445519825447942 * df.mm.trans2:probe5 -0.0639124092818321 0.0496475383674232 -1.28732282371867 0.198595775210880 df.mm.trans2:probe6 -0.0426710593888461 0.0496475383674232 -0.859479861278383 0.390500438189981 df.mm.trans3:probe2 0.099114690100088 0.0496475383674232 1.9963666550107 0.0464525800033126 * df.mm.trans3:probe3 0.0601316231227284 0.0496475383674232 1.21117028356404 0.226419969094173 df.mm.trans3:probe4 0.356329980830797 0.0496475383674232 7.17719332212867 2.68529018536222e-12 *** df.mm.trans3:probe5 0.0790088269006856 0.0496475383674232 1.59139464913588 0.112172332154681 df.mm.trans3:probe6 -0.100437892378151 0.0496475383674232 -2.02301857616478 0.0436193231576878 * df.mm.trans3:probe7 0.588371759016883 0.0496475383674232 11.8509754635277 1.24900297690276e-28 *** df.mm.trans3:probe8 -0.00553519100830766 0.0496475383674232 -0.111489737262374 0.911274127228662 df.mm.trans3:probe9 0.517947492512622 0.0496475383674232 10.4324909057823 3.99475283734998e-23 *** df.mm.trans3:probe10 0.034400098134182 0.0496475383674232 0.692886279267251 0.488712563006497 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.54768542549405 0.153810397661440 29.5668270457514 1.33522997124859e-110 *** df.mm.trans1 0.0381149374506791 0.123133266926381 0.309542160312106 0.75704209050843 df.mm.trans2 -0.0410874068771021 0.123133266926381 -0.333682423139699 0.738763432485505 df.mm.exp2 -0.184823383945340 0.164883833092825 -1.12093090316071 0.262871989756794 df.mm.exp3 -0.149947110619521 0.164883833092825 -0.909410630544386 0.363585110020923 df.mm.exp4 0.146775267030945 0.164883833092825 0.890173792528918 0.373813916627752 df.mm.exp5 0.191526648363192 0.164883833092825 1.16158537056430 0.245975263290087 df.mm.exp6 0.0943242296376287 0.164883833092825 0.572064755339153 0.56754315489345 df.mm.exp7 0.0651271843570914 0.164883833092825 0.394988296520415 0.69302517751612 df.mm.exp8 -0.0584714573088869 0.164883833092825 -0.35462213736849 0.723026830041448 df.mm.trans1:exp2 0.127619988370415 0.129345520371737 0.986659514791367 0.324301541417184 df.mm.trans2:exp2 0.0901704695363173 0.129345520371737 0.697128661875331 0.486056293716237 df.mm.trans1:exp3 0.0904591946402559 0.129345520371737 0.699360862133282 0.484661804719011 df.mm.trans2:exp3 0.0647860873943834 0.129345520371737 0.500876158742794 0.616685513195241 df.mm.trans1:exp4 -0.0691071555836621 0.129345520371737 -0.534283331846741 0.59339033759364 df.mm.trans2:exp4 -0.147946800472720 0.129345520371737 -1.14381077943421 0.253266342407202 df.mm.trans1:exp5 -0.153953777507269 0.129345520371737 -1.19025210200406 0.234529593326756 df.mm.trans2:exp5 -0.135340388177370 0.129345520371737 -1.04634770333294 0.295921715153196 df.mm.trans1:exp6 -0.0133650589342138 0.129345520371737 -0.103328347945896 0.917745088512161 df.mm.trans2:exp6 -0.082955528954552 0.129345520371737 -0.641348294986477 0.521599375634213 df.mm.trans1:exp7 -0.0730998042721623 0.129345520371737 -0.565151418171071 0.572232098831249 df.mm.trans2:exp7 -0.0296866775338098 0.129345520371737 -0.229514539417297 0.818565779717419 df.mm.trans1:exp8 -0.0244563773141567 0.129345520371737 -0.189077884134444 0.85011087099766 df.mm.trans2:exp8 0.0523879874247105 0.129345520371737 0.405023593195561 0.685638750770437 df.mm.trans1:probe2 -0.0922686645897678 0.0885568240248054 -1.04191478867764 0.297970270038907 df.mm.trans1:probe3 -0.0318150375056902 0.0885568240248054 -0.359261274961471 0.71955599840307 df.mm.trans1:probe4 -0.0390637807498648 0.0885568240248054 -0.441115421426166 0.65932601173998 df.mm.trans1:probe5 -0.0040713171501274 0.0885568240248054 -0.0459740646185211 0.96334984478025 df.mm.trans1:probe6 -0.0671528863834507 0.0885568240248054 -0.75830278606921 0.448638057442374 df.mm.trans2:probe2 0.0669877078847492 0.0885568240248054 0.756437559978275 0.449754167051014 df.mm.trans2:probe3 0.0836693578781584 0.0885568240248054 0.944809830292942 0.345226409409058 df.mm.trans2:probe4 -0.0185173469644748 0.0885568240248054 -0.209101299288782 0.834456955531122 df.mm.trans2:probe5 0.0408626008752686 0.0885568240248054 0.461428030253464 0.644698418482892 df.mm.trans2:probe6 0.0289972132519268 0.0885568240248054 0.327441883460099 0.743474979228496 df.mm.trans3:probe2 0.04958847145951 0.0885568240248054 0.55996217124521 0.575763770718572 df.mm.trans3:probe3 -0.0419153254045967 0.0885568240248054 -0.473315589918354 0.636201001179638 df.mm.trans3:probe4 0.0452155628091671 0.0885568240248054 0.510582479747714 0.609875754956445 df.mm.trans3:probe5 0.121422785158778 0.0885568240248054 1.37112849851939 0.170968990425961 df.mm.trans3:probe6 -0.00579971247064254 0.0885568240248054 -0.065491423552159 0.947809720634052 df.mm.trans3:probe7 0.000544161476054416 0.0885568240248054 0.00614477181229978 0.995099738916867 df.mm.trans3:probe8 -0.0608224820489036 0.0885568240248054 -0.686818692050957 0.492525239674145 df.mm.trans3:probe9 -0.026731898447446 0.0885568240248054 -0.301861530625333 0.762887015982283 df.mm.trans3:probe10 -0.19267440240456 0.0885568240248054 -2.17571490990452 0.0300586776148286 *