chr7.22128_chr7_128962745_128964838_+_2.R fitVsDatCorrelation=0.87914557235742 cont.fitVsDatCorrelation=0.231142504792404 fstatistic=10002.740611363,61,899 cont.fstatistic=2388.66875477055,61,899 residuals=-0.594560961647835,-0.0910664504487419,0.000603731616124789,0.0870617292172213,0.969671034261664 cont.residuals=-0.701103132076925,-0.269525670513579,-0.00474285904523356,0.230560392949834,1.02311079521598 predictedValues: Include Exclude Both chr7.22128_chr7_128962745_128964838_+_2.R.tl.Lung 51.7671341272893 77.6745390632227 72.14308743151 chr7.22128_chr7_128962745_128964838_+_2.R.tl.cerebhem 48.3742671756342 65.9411750252678 71.1479487371951 chr7.22128_chr7_128962745_128964838_+_2.R.tl.cortex 64.084764536836 84.1654911925608 107.52264308241 chr7.22128_chr7_128962745_128964838_+_2.R.tl.heart 58.0205392335136 92.3579744043232 85.472772470292 chr7.22128_chr7_128962745_128964838_+_2.R.tl.kidney 52.9743274822201 84.4411975797521 73.9338984282747 chr7.22128_chr7_128962745_128964838_+_2.R.tl.liver 52.5712159224384 88.00274300018 68.9054471862869 chr7.22128_chr7_128962745_128964838_+_2.R.tl.stomach 53.1623360078042 84.3242916314454 68.896756833809 chr7.22128_chr7_128962745_128964838_+_2.R.tl.testicle 52.8915194455428 77.8565309227214 72.217771236211 diffExp=-25.9074049359334,-17.5669078496336,-20.0807266557247,-34.3374351708096,-31.466870097532,-35.4315270777416,-31.1619556236412,-24.9650114771787 diffExpScore=0.995493827783246 diffExp1.5=-1,0,0,-1,-1,-1,-1,0 diffExp1.5Score=0.833333333333333 diffExp1.4=-1,0,0,-1,-1,-1,-1,-1 diffExp1.4Score=0.857142857142857 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 67.117729913539 65.0192490192757 66.220733665544 cerebhem 66.3365799380338 67.5250286668043 59.9797703748229 cortex 65.7560929361802 77.5244992044235 62.9262947965473 heart 70.6058332149387 65.2827547567847 68.778797432921 kidney 68.2287590670272 69.1248600745379 69.9913531240698 liver 69.9284257984377 64.9536246546863 67.4416151473217 stomach 68.3682989603608 63.945051774907 69.8101298564646 testicle 69.0195394530275 65.7960175085012 60.4296592127061 cont.diffExp=2.09848089426329,-1.18844872877048,-11.7684062682433,5.32307845815396,-0.896101007510651,4.97480114375136,4.42324718545375,3.22352194452631 cont.diffExpScore=4.71422352427371 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=0.578643859245782 cont.tran.correlation=-0.641953494171244 tran.covariance=0.00535824478566481 cont.tran.covariance=-0.00100456560237450 tran.mean=68.038127921922 cont.tran.mean=67.7832715588416 weightedLogRatios: wLogRatio Lung -1.68380853464793 cerebhem -1.24967159238828 cortex -1.17113170356935 heart -1.99581733207158 kidney -1.95960834773818 liver -2.17402145551769 stomach -1.93939310784934 testicle -1.6089604107937 cont.weightedLogRatios: wLogRatio Lung 0.133112800831898 cerebhem -0.0746430294104947 cortex -0.702735623488755 heart 0.330621076813853 kidney -0.0551862368735417 liver 0.310734729497035 stomach 0.280346682544969 testicle 0.201388395034274 varWeightedLogRatios=0.131971174179239 cont.varWeightedLogRatios=0.117536809269946 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.01173326519442 0.0764264363308419 52.4914343490786 5.22259217838487e-276 *** df.mm.trans1 -0.269655489232287 0.0657405222785334 -4.10181543873038 4.47108258764793e-05 *** df.mm.trans2 0.459232163808349 0.0578269035147401 7.9414967064818 5.94479458865471e-15 *** df.mm.exp2 -0.21766195484287 0.0738112984718466 -2.94889751771392 0.00327169122555986 ** df.mm.exp3 -0.105341332196683 0.0738112984718466 -1.42717083126322 0.153877887246235 df.mm.exp4 0.117639730360579 0.0738112984718466 1.59379028409113 0.111334508746279 df.mm.exp5 0.0820598646913661 0.0738112984718466 1.11175208118938 0.26654198040384 df.mm.exp6 0.186169974050694 0.0738112984718466 2.52224222991692 0.0118326086313170 * df.mm.exp7 0.154779529662811 0.0738112984718466 2.09696256355452 0.0362757483745406 * df.mm.exp8 0.0227931239776567 0.0738112984718466 0.308802642001353 0.757543205359585 df.mm.trans1:exp2 0.149874485660962 0.0678965194548633 2.20739570841472 0.0275383584005723 * df.mm.trans2:exp2 0.0538974908505577 0.0487320860697576 1.10599597097908 0.269024139218406 df.mm.trans1:exp3 0.318792513546613 0.0678965194548633 4.6952703335337 3.07767544848616e-06 *** df.mm.trans2:exp3 0.185598805027554 0.0487320860697576 3.80855448629633 0.000149275567414939 *** df.mm.trans1:exp4 -0.00359812937877711 0.0678965194548633 -0.0529943126343773 0.957748212480225 df.mm.trans2:exp4 0.0555048012699883 0.0487320860697576 1.13897856107649 0.25501549959548 df.mm.trans1:exp5 -0.0590079272135195 0.0678965194548633 -0.86908618714612 0.385031952191669 df.mm.trans2:exp5 0.00146801971019450 0.0487320860697576 0.0301242944554661 0.975974611459361 df.mm.trans1:exp6 -0.170756701491884 0.0678965194548633 -2.51495515326674 0.0120782203692478 * df.mm.trans2:exp6 -0.0613295106916108 0.0487320860697576 -1.25850370131540 0.208536376728645 df.mm.trans1:exp7 -0.128184825415290 0.0678965194548633 -1.88794398364566 0.0593552933204577 . df.mm.trans2:exp7 -0.072637070297523 0.0487320860697576 -1.49053890682099 0.136433357267878 df.mm.trans1:exp8 -0.00130558249660654 0.0678965194548633 -0.0192290047720999 0.984662686163082 df.mm.trans2:exp8 -0.0204528591987044 0.0487320860697576 -0.419700054896626 0.674804862015491 df.mm.trans1:probe2 0.226130539037026 0.0480100893254982 4.71006286832563 2.86751404772186e-06 *** df.mm.trans1:probe3 0.821687419481832 0.0480100893254982 17.1148904537745 4.67966220585146e-57 *** df.mm.trans1:probe4 0.0655252268059418 0.0480100893254982 1.36482201400824 0.172650480490128 df.mm.trans1:probe5 0.729901986957628 0.0480100893254982 15.2030957911586 1.26115767230751e-46 *** df.mm.trans1:probe6 0.402180770932211 0.0480100893254982 8.37700526248786 2.07219405511475e-16 *** df.mm.trans1:probe7 0.421418164618781 0.0480100893254982 8.77770007386688 8.28944205229146e-18 *** df.mm.trans1:probe8 0.0115293307191086 0.0480100893254982 0.240143913104227 0.810273438764714 df.mm.trans1:probe9 0.496625934604256 0.0480100893254982 10.3441993460424 9.00107092104993e-24 *** df.mm.trans1:probe10 0.00917015311616451 0.0480100893254982 0.191004708489351 0.848565030547514 df.mm.trans1:probe11 0.62062385900799 0.0480100893254982 12.9269465590929 3.49546468679837e-35 *** df.mm.trans1:probe12 0.765815968858156 0.0480100893254982 15.9511465114361 1.25846150095761e-50 *** df.mm.trans1:probe13 0.759507890570104 0.0480100893254982 15.8197558313379 6.46249975437112e-50 *** df.mm.trans1:probe14 0.619238312009538 0.0480100893254982 12.8980870627262 4.79547979553574e-35 *** df.mm.trans1:probe15 0.463321731563277 0.0480100893254982 9.65050759272816 4.91011123849213e-21 *** df.mm.trans1:probe16 0.450238231781832 0.0480100893254982 9.37799196184186 5.31053752903348e-20 *** df.mm.trans1:probe17 0.0273123314627585 0.0480100893254982 0.568887328611007 0.569574693432038 df.mm.trans1:probe18 0.0345349635438886 0.0480100893254982 0.719327208698757 0.472126275772092 df.mm.trans1:probe19 -0.0144118932661313 0.0480100893254982 -0.300184679274844 0.76410568875146 df.mm.trans1:probe20 0.09164605250637 0.0480100893254982 1.90889152246790 0.0565942569605983 . df.mm.trans1:probe21 -0.0391550622359838 0.0480100893254982 -0.815559037404009 0.414968403617915 df.mm.trans1:probe22 -0.00380026062493905 0.0480100893254982 -0.0791554583282296 0.9369265878842 df.mm.trans2:probe2 -0.446958696513272 0.0480100893254982 -9.30968266863632 9.56364817602158e-20 *** df.mm.trans2:probe3 -0.340649010356336 0.0480100893254982 -7.09536297770264 2.61511534627033e-12 *** df.mm.trans2:probe4 -0.70374585032217 0.0480100893254982 -14.6582907928149 8.78900309432256e-44 *** df.mm.trans2:probe5 -0.391806375552982 0.0480100893254982 -8.1609174458439 1.11639548481373e-15 *** df.mm.trans2:probe6 -0.248722409686408 0.0480100893254982 -5.18062793010283 2.73063852698627e-07 *** df.mm.trans3:probe2 0.287910722255165 0.0480100893254982 5.99687953719877 2.911242331771e-09 *** df.mm.trans3:probe3 0.346530163726514 0.0480100893254982 7.21786125781006 1.12334076012225e-12 *** df.mm.trans3:probe4 0.103712943212869 0.0480100893254982 2.16023224847005 0.0310183582570829 * df.mm.trans3:probe5 -0.0574011607885614 0.0480100893254982 -1.19560620684110 0.232165539480774 df.mm.trans3:probe6 -0.133790498895170 0.0480100893254982 -2.78671630848463 0.00543666668874187 ** df.mm.trans3:probe7 0.0325901260924653 0.0480100893254982 0.678818276539982 0.497427720135488 df.mm.trans3:probe8 0.373840108146245 0.0480100893254982 7.78669886680877 1.89031701318234e-14 *** df.mm.trans3:probe9 -0.0219633544589907 0.0480100893254982 -0.457473726201253 0.647441117168464 df.mm.trans3:probe10 0.0348709186685428 0.0480100893254982 0.726324802941428 0.467828736220708 df.mm.trans3:probe11 -0.192793751077078 0.0480100893254982 -4.01569240519378 6.4218735994563e-05 *** df.mm.trans3:probe12 0.154592173890917 0.0480100893254982 3.21999346518218 0.00132792748764486 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.31114646147192 0.156030393196072 27.6301711042568 3.84261645022658e-122 *** df.mm.trans1 -0.0167789750409471 0.134214285429075 -0.125016312438767 0.900538585259866 df.mm.trans2 -0.137936984202613 0.11805802973277 -1.16838290893758 0.242962085625318 df.mm.exp2 0.125094464095066 0.150691389992591 0.830136772254981 0.40668184529894 df.mm.exp3 0.206444228717635 0.150691389992591 1.36998025386709 0.171035107259986 df.mm.exp4 0.0168071589728623 0.150691389992591 0.111533638210442 0.911218088768688 df.mm.exp5 0.0222708973294928 0.150691389992591 0.147791438718481 0.882540505796284 df.mm.exp6 0.0217455221432805 0.150691389992591 0.1443050073687 0.885291966576375 df.mm.exp7 -0.0509837196714978 0.150691389992591 -0.338332002073937 0.73519200663959 df.mm.exp8 0.131330932499070 0.150691389992591 0.871522470564022 0.383701621247909 df.mm.trans1:exp2 -0.136801225721941 0.138615917943983 -0.986908486060199 0.323953039604970 df.mm.trans2:exp2 -0.0872795046936145 0.0994902669256164 -0.877266765791962 0.380576128627318 df.mm.trans1:exp3 -0.226940133997324 0.138615917943983 -1.63718667641788 0.101941435479216 df.mm.trans2:exp3 -0.0305335883598874 0.0994902669256164 -0.306900255707584 0.758990365336741 df.mm.trans1:exp4 0.0338573652792583 0.138615917943983 0.244253082773225 0.807090550145233 df.mm.trans2:exp4 -0.0127626149277637 0.0994902669256164 -0.128280035044087 0.89795605447721 df.mm.trans1:exp5 -0.00585297444032832 0.138615917943983 -0.0422244034245301 0.96632918461824 df.mm.trans2:exp5 0.0389601734595082 0.0994902669256165 0.391597838295445 0.69544818658409 df.mm.trans1:exp6 0.0192784679392599 0.138615917943983 0.139078312398801 0.889419414453134 df.mm.trans2:exp6 -0.0227553385505200 0.0994902669256164 -0.228719243134938 0.81913915436704 df.mm.trans1:exp7 0.06944473109987 0.138615917943983 0.500986698569017 0.616503121755818 df.mm.trans2:exp7 0.0343245034218947 0.0994902669256164 0.345003631838251 0.730172340059735 df.mm.trans1:exp8 -0.103389527786179 0.138615917943983 -0.745870527134989 0.455940607722105 df.mm.trans2:exp8 -0.119454984999671 0.0994902669256164 -1.20067006241908 0.230195474770938 df.mm.trans1:probe2 -0.213327102225476 0.0980162555585887 -2.17644615181163 0.0297815793052879 * df.mm.trans1:probe3 -0.119055472229842 0.0980162555585887 -1.21465027970465 0.224818443441811 df.mm.trans1:probe4 -0.177561773335017 0.0980162555585887 -1.81155434191098 0.0703886843023487 . df.mm.trans1:probe5 -0.0593078851931335 0.0980162555585887 -0.605082135153414 0.5452771238408 df.mm.trans1:probe6 0.00491838881839262 0.0980162555585887 0.0501793176077072 0.95999063922548 df.mm.trans1:probe7 -0.136487851406860 0.0980162555585887 -1.39250219903856 0.164114682970105 df.mm.trans1:probe8 -0.0516642363788632 0.0980162555585887 -0.527098654038883 0.598255121992399 df.mm.trans1:probe9 -0.228484357271606 0.0980162555585886 -2.33108636898530 0.0199690728031741 * df.mm.trans1:probe10 -0.0888952433509479 0.0980162555585887 -0.906943882362566 0.364679500145667 df.mm.trans1:probe11 -0.0670573097428371 0.0980162555585886 -0.684144781502635 0.49406005921854 df.mm.trans1:probe12 -0.153493232772107 0.0980162555585887 -1.56599772045319 0.117701058523762 df.mm.trans1:probe13 -0.150923801396391 0.0980162555585886 -1.53978338119820 0.123965051415563 df.mm.trans1:probe14 -0.117323258590808 0.0980162555585886 -1.19697756175432 0.231630841746971 df.mm.trans1:probe15 -0.207216208715871 0.0980162555585886 -2.11410043706483 0.0347815054384001 * df.mm.trans1:probe16 -0.198596752805643 0.0980162555585887 -2.02616139204515 0.0430431090523154 * df.mm.trans1:probe17 -0.208996079440732 0.0980162555585887 -2.13225937115917 0.0332559996919975 * df.mm.trans1:probe18 -0.180759814673255 0.0980162555585887 -1.84418200474111 0.0654854976209683 . df.mm.trans1:probe19 -0.109854055470554 0.0980162555585887 -1.12077384352731 0.262683442124186 df.mm.trans1:probe20 -0.194315228956388 0.0980162555585887 -1.98247961880402 0.0477296516695108 * df.mm.trans1:probe21 -0.123634064920521 0.0980162555585887 -1.26136286492417 0.207505343133848 df.mm.trans1:probe22 -0.207219029244399 0.0980162555585887 -2.11412921319500 0.0347790414208059 * df.mm.trans2:probe2 0.044940724582946 0.0980162555585887 0.458502769023684 0.64670209061924 df.mm.trans2:probe3 -0.0418215664072621 0.0980162555585886 -0.426679902929607 0.669714644913098 df.mm.trans2:probe4 -0.0194184623211183 0.0980162555585887 -0.198114712814254 0.84300010286532 df.mm.trans2:probe5 -0.0304787646913905 0.0980162555585887 -0.310956223717116 0.755905986008946 df.mm.trans2:probe6 0.0733080446287006 0.0980162555585887 0.74791721241464 0.45470569148487 df.mm.trans3:probe2 -0.0601604503921718 0.0980162555585886 -0.613780337244277 0.539515763949663 df.mm.trans3:probe3 -0.00273400028454653 0.0980162555585886 -0.0278933353346915 0.97775341455782 df.mm.trans3:probe4 -0.0487286444702439 0.0980162555585887 -0.497148602469481 0.61920582106563 df.mm.trans3:probe5 0.00567682752931339 0.0980162555585887 0.0579172046204122 0.953827449258324 df.mm.trans3:probe6 0.0755330039267839 0.0980162555585887 0.77061711341987 0.441136381784517 df.mm.trans3:probe7 0.0274023081893756 0.0980162555585887 0.279569016722905 0.779872487294884 df.mm.trans3:probe8 0.119053963179704 0.0980162555585887 1.21463488378762 0.224824315113434 df.mm.trans3:probe9 0.0588426162075086 0.0980162555585887 0.600335279818313 0.548434110949975 df.mm.trans3:probe10 0.0225676701451782 0.0980162555585886 0.230244157120331 0.817954431319874 df.mm.trans3:probe11 0.0586224594417008 0.0980162555585887 0.598089154779633 0.549931084589284 df.mm.trans3:probe12 0.182681555046537 0.0980162555585887 1.86378834822291 0.0626772484479252 .