chr4.17247_chr4_115993685_115998119_-_2.R fitVsDatCorrelation=0.907846234128805 cont.fitVsDatCorrelation=0.351628936459769 fstatistic=9730.7769717465,44,508 cont.fstatistic=1942.96433514834,44,508 residuals=-0.579334255803118,-0.08885771992438,-0.00310856693842358,0.086863161473374,0.630611862780191 cont.residuals=-0.695439479753738,-0.228276473937762,-0.0258403807696852,0.161331202900194,1.64989166744832 predictedValues: Include Exclude Both chr4.17247_chr4_115993685_115998119_-_2.R.tl.Lung 58.8966972151229 108.102991467607 123.465077596762 chr4.17247_chr4_115993685_115998119_-_2.R.tl.cerebhem 57.3578051986933 75.9264362659341 61.5834905201573 chr4.17247_chr4_115993685_115998119_-_2.R.tl.cortex 68.8641979062576 79.3381831995418 90.1941656740763 chr4.17247_chr4_115993685_115998119_-_2.R.tl.heart 55.3115655528122 79.4782265772307 77.9401112243403 chr4.17247_chr4_115993685_115998119_-_2.R.tl.kidney 57.7652754813618 85.5861070198002 86.3433559687993 chr4.17247_chr4_115993685_115998119_-_2.R.tl.liver 55.929472447842 87.0688831882909 98.4698411899525 chr4.17247_chr4_115993685_115998119_-_2.R.tl.stomach 74.4202181416605 101.100842112778 104.453027067747 chr4.17247_chr4_115993685_115998119_-_2.R.tl.testicle 128.632651517375 111.687280168097 172.144696811886 diffExp=-49.2062942524838,-18.5686310672408,-10.4739852932842,-24.1666610244185,-27.8208315384383,-31.1394107404488,-26.6806239711172,16.9453713492775 diffExpScore=1.19110184696499 diffExp1.5=-1,0,0,0,0,-1,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=-1,0,0,-1,-1,-1,0,0 diffExp1.4Score=0.8 diffExp1.3=-1,-1,0,-1,-1,-1,-1,0 diffExp1.3Score=0.857142857142857 diffExp1.2=-1,-1,0,-1,-1,-1,-1,0 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 79.712446517503 77.8310548539402 83.2958711217191 cerebhem 94.6268366061283 71.2057773932299 69.8407287908809 cortex 82.7672675233574 77.624934089006 76.5697486254504 heart 73.8174656339448 74.1116504143917 84.7642482397472 kidney 76.2547829742393 82.077223862226 72.5720042054653 liver 72.2825904903915 76.4980062027777 71.2024914514789 stomach 77.0847436876774 74.2488821247302 84.8592349802257 testicle 74.6761528765391 80.3840274686006 70.8406589889109 cont.diffExp=1.88139166356277,23.4210592128984,5.1423334343513,-0.294184780446855,-5.8224408879867,-4.21541571238622,2.83586156294723,-5.70787459206147 cont.diffExpScore=2.70386997201607 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=0,1,0,0,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,1,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.645007663210599 cont.tran.correlation=-0.521992012166274 tran.covariance=0.02709635243134 cont.tran.covariance=-0.00205908242250934 tran.mean=80.3416770912753 cont.tran.mean=77.8252401699177 weightedLogRatios: wLogRatio Lung -2.65962799386844 cerebhem -1.17498075124653 cortex -0.609221867521682 heart -1.52041381819924 kidney -1.67198623186144 liver -1.87904640186193 stomach -1.36739857116069 testicle 0.67610695545753 cont.weightedLogRatios: wLogRatio Lung 0.104294438557953 cerebhem 1.25342150492403 cortex 0.281204652281299 heart -0.0171169899925433 kidney -0.321610464991321 liver -0.24423572817334 stomach 0.162156145109999 testicle -0.320397030935177 varWeightedLogRatios=0.966929653343845 cont.varWeightedLogRatios=0.264658318765935 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.12492574404222 0.0796733428025215 51.7729719746574 9.26414460337476e-205 *** df.mm.trans1 -0.185450893535211 0.0686554688480261 -2.70118166326589 0.00714018303226352 ** df.mm.trans2 0.65361132816037 0.0641207814239751 10.1934398434512 2.51869192627563e-22 *** df.mm.exp2 0.315768967545558 0.0862068406769792 3.66292239764079 0.000275521581521319 *** df.mm.exp3 0.160980123529557 0.0862068406769792 1.86737064327362 0.0624255140033988 . df.mm.exp4 0.089613337853576 0.0862068406769792 1.03951539286031 0.299059604367023 df.mm.exp5 0.104667866666083 0.0862068406769792 1.21414804027302 0.225255323925085 df.mm.exp6 -0.041870346363643 0.0862068406769792 -0.4856963326209 0.627391899733576 df.mm.exp7 0.334197572560331 0.0862068406769792 3.87669435436782 0.000119776172871092 *** df.mm.exp8 0.481417051887328 0.0862068406769792 5.58444142143219 3.82430834979389e-08 *** df.mm.trans1:exp2 -0.34224505024655 0.0778164093780125 -4.39810899760242 1.33099273077321e-05 *** df.mm.trans2:exp2 -0.669088437301811 0.0684044425272715 -9.7813594056418 8.123831559571e-21 *** df.mm.trans1:exp3 -0.00462871920252922 0.0778164093780125 -0.0594825595208855 0.952591148194841 df.mm.trans2:exp3 -0.470345005040505 0.0684044425272715 -6.87594237542375 1.81389715375173e-11 *** df.mm.trans1:exp4 -0.152416323827770 0.0778164093780125 -1.95866559567622 0.0506986779337846 . df.mm.trans2:exp4 -0.397214630649943 0.0684044425272715 -5.8068542915408 1.12304544474012e-08 *** df.mm.trans1:exp5 -0.124065056380323 0.0778164093780125 -1.59433026236980 0.111484021640288 df.mm.trans2:exp5 -0.338229295274321 0.0684044425272715 -4.94455159311438 1.03866805329759e-06 *** df.mm.trans1:exp6 -0.00982319185122992 0.0778164093780125 -0.126235480790579 0.899595471765438 df.mm.trans2:exp6 -0.174514484887157 0.0684044425272715 -2.55121565850905 0.0110267422208211 * df.mm.trans1:exp7 -0.100254933061729 0.0778164093780125 -1.28835208233157 0.198209906740185 df.mm.trans2:exp7 -0.401163514478470 0.0684044425272715 -5.86458276183646 8.11850499066043e-09 *** df.mm.trans1:exp8 0.299758612873969 0.0778164093780125 3.85212598820665 0.000132076074192471 *** df.mm.trans2:exp8 -0.448798624659424 0.0684044425272715 -6.56095727233646 1.31986550561258e-10 *** df.mm.trans1:probe2 0.067503256764793 0.0454349944044177 1.48571068731615 0.137975962087079 df.mm.trans1:probe3 0.184328871835386 0.0454349944044177 4.0569801812821 5.753270901967e-05 *** df.mm.trans1:probe4 0.0273414918365449 0.0454349944044177 0.601771656295977 0.547594607689376 df.mm.trans1:probe5 0.195476346998022 0.0454349944044177 4.30233016555661 2.02784619329979e-05 *** df.mm.trans1:probe6 0.0762640689951138 0.0454349944044177 1.67853149306647 0.0938583708287645 . df.mm.trans1:probe7 0.326732451670902 0.0454349944044177 7.19120704104529 2.31238627285722e-12 *** df.mm.trans1:probe8 0.341108664468555 0.0454349944044177 7.5076198190395 2.72244476138273e-13 *** df.mm.trans1:probe9 0.353253992567768 0.0454349944044177 7.77493201437305 4.22853356030124e-14 *** df.mm.trans1:probe10 0.256279795989189 0.0454349944044177 5.6405816562458 2.81741535680422e-08 *** df.mm.trans1:probe11 0.275705131844201 0.0454349944044177 6.0681229404398 2.53223210594837e-09 *** df.mm.trans1:probe12 0.213278717276490 0.0454349944044177 4.69415084280836 3.44831500596519e-06 *** df.mm.trans2:probe2 -0.341884797916721 0.0454349944044177 -7.52470210238388 2.42059869454445e-13 *** df.mm.trans2:probe3 -0.160465240455742 0.0454349944044177 -3.53175437917827 0.000450412595870636 *** df.mm.trans2:probe4 -0.112869293130851 0.0454349944044177 -2.48419295766164 0.0133057083877430 * df.mm.trans2:probe5 -0.154939742152613 0.0454349944044177 -3.41014110783181 0.000700973364439604 *** df.mm.trans2:probe6 -0.279820349028254 0.0454349944044177 -6.15869667634529 1.49217516088564e-09 *** df.mm.trans3:probe2 0.173795082278740 0.0454349944044177 3.8251370899661 0.000146959977221137 *** df.mm.trans3:probe3 -0.126389569598325 0.0454349944044177 -2.78176703343086 0.00560737941041422 ** df.mm.trans3:probe4 0.341740631282103 0.0454349944044177 7.52152907162844 2.47405587595147e-13 *** df.mm.trans3:probe5 0.725214680623072 0.0454349944044177 15.9615884216453 8.83707036784726e-47 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.30764545127421 0.177879280145757 24.216679130613 1.04089700614813e-86 *** df.mm.trans1 -0.0138818490129856 0.153280695238632 -0.0905648881052763 0.92787402974177 df.mm.trans2 0.0444512957841951 0.143156519368723 0.310508358125860 0.756301758648186 df.mm.exp2 0.258730459235917 0.192466014652717 1.34429166470125 0.179454076299967 df.mm.exp3 0.119152009134578 0.192466014652717 0.619080773037125 0.536140669209648 df.mm.exp4 -0.143273015438545 0.192466014652717 -0.744406827860313 0.456974594329415 df.mm.exp5 0.146594195796126 0.192466014652717 0.76166275932215 0.446614755019804 df.mm.exp6 0.0417528991133717 0.192466014652717 0.216936476752585 0.828344944655716 df.mm.exp7 -0.0992329919039187 0.192466014652717 -0.515587087325383 0.606367133843219 df.mm.exp8 0.128975907017424 0.192466014652717 0.67012302016097 0.503083871979306 df.mm.trans1:exp2 -0.0872150790536224 0.173733477180655 -0.502005027867672 0.61588149268848 df.mm.trans2:exp2 -0.34769701513375 0.152720252063251 -2.27669225552186 0.0232197037396584 * df.mm.trans1:exp3 -0.0815450863677897 0.173733477180655 -0.469368872891410 0.639007380744907 df.mm.trans2:exp3 -0.121803832163401 0.152720252063251 -0.79756175437004 0.425497487905025 df.mm.trans1:exp4 0.0664426400528252 0.173733477180655 0.382440052032892 0.702294936177954 df.mm.trans2:exp4 0.0943052467601073 0.152720252063251 0.61750321575589 0.537179553510496 df.mm.trans1:exp5 -0.190939795443639 0.173733477180655 -1.09903858796938 0.272271819532556 df.mm.trans2:exp5 -0.093474151474131 0.152720252063251 -0.612061270272248 0.540771061526188 df.mm.trans1:exp6 -0.139595335073549 0.173733477180655 -0.803502798302899 0.422059980975938 df.mm.trans2:exp6 -0.0590287355164837 0.152720252063251 -0.386515440611219 0.699276811293834 df.mm.trans1:exp7 0.065712635251001 0.173733477180655 0.378238185969594 0.70541166386571 df.mm.trans2:exp7 0.0521151997270262 0.152720252063251 0.341246161022850 0.733059372479819 df.mm.trans1:exp8 -0.194240845145441 0.173733477180655 -1.11803924204810 0.264078672463709 df.mm.trans2:exp8 -0.0967009280817151 0.152720252063251 -0.633189945506805 0.526894551658385 df.mm.trans1:probe2 -0.00865444043034108 0.101438496412988 -0.0853171205841435 0.932042894424976 df.mm.trans1:probe3 0.259515657844171 0.101438496412988 2.55835473731395 0.0108057765774029 * df.mm.trans1:probe4 0.381071012743268 0.101438496412988 3.7566705562335 0.000192139098008258 *** df.mm.trans1:probe5 0.0838733769638206 0.101438496412988 0.826839710067724 0.40871611644645 df.mm.trans1:probe6 0.108611430708317 0.101438496412988 1.07071215119481 0.284807316720226 df.mm.trans1:probe7 0.101785240743848 0.101438496412988 1.00341827159433 0.316136801777071 df.mm.trans1:probe8 0.104904689134255 0.101438496412988 1.03417038741539 0.301548573325676 df.mm.trans1:probe9 0.190951532829691 0.101438496412988 1.88243654610443 0.0603480501365268 . df.mm.trans1:probe10 0.00659284843201145 0.101438496412988 0.0649935543718029 0.948204700027325 df.mm.trans1:probe11 0.18906199189382 0.101438496412988 1.86380909200477 0.0629251984553413 . df.mm.trans1:probe12 0.0215430125750367 0.101438496412988 0.212375117305845 0.831899583746499 df.mm.trans2:probe2 -0.0289370480434184 0.101438496412988 -0.285266925937138 0.775555917826763 df.mm.trans2:probe3 0.119426840049569 0.101438496412988 1.17733251450559 0.239614111643712 df.mm.trans2:probe4 0.0282630607259102 0.101438496412988 0.278622630710558 0.780647822184459 df.mm.trans2:probe5 0.0822088307184107 0.101438496412988 0.810430296440052 0.418072398964282 df.mm.trans2:probe6 -0.174080245034038 0.101438496412988 -1.71611618063919 0.0867504410879237 . df.mm.trans3:probe2 0.0192045319858652 0.101438496412988 0.189321930676866 0.849916124697874 df.mm.trans3:probe3 0.147795686113549 0.101438496412988 1.45699799720835 0.145734761553838 df.mm.trans3:probe4 0.0968467688732929 0.101438496412988 0.954733876170637 0.340166378185805 df.mm.trans3:probe5 0.157073430692313 0.101438496412988 1.54845976869391 0.122134369570496