chr7.21984_chr7_110280163_110282692_+_2.R fitVsDatCorrelation=0.954301898182377 cont.fitVsDatCorrelation=0.286189030558878 fstatistic=6519.71698459226,42,462 cont.fstatistic=624.27630849382,42,462 residuals=-0.639290350061033,-0.110932788294423,0.0030437047349366,0.107851070045265,0.83436129646515 cont.residuals=-1.17272080880269,-0.492901190982291,-0.096557818583919,0.392538573665609,1.78236745557835 predictedValues: Include Exclude Both chr7.21984_chr7_110280163_110282692_+_2.R.tl.Lung 45.818113680545 75.94855189047 86.3330239226592 chr7.21984_chr7_110280163_110282692_+_2.R.tl.cerebhem 53.5440400672986 76.8057721399222 103.042965264429 chr7.21984_chr7_110280163_110282692_+_2.R.tl.cortex 45.0336591155299 105.007534755411 129.836598286566 chr7.21984_chr7_110280163_110282692_+_2.R.tl.heart 46.4824280742407 165.106187545454 283.564547057608 chr7.21984_chr7_110280163_110282692_+_2.R.tl.kidney 44.1649199866482 127.686054269853 158.37531472304 chr7.21984_chr7_110280163_110282692_+_2.R.tl.liver 50.1352237874242 112.733459508221 136.512731552141 chr7.21984_chr7_110280163_110282692_+_2.R.tl.stomach 48.6376069936097 93.4775067637713 121.183510577461 chr7.21984_chr7_110280163_110282692_+_2.R.tl.testicle 48.332448470686 113.792665853469 170.601991868999 diffExp=-30.1304382099249,-23.2617320726235,-59.9738756398809,-118.623759471213,-83.5211342832048,-62.5982357207972,-44.8398997701616,-65.4602173827832 diffExpScore=0.997956720448056 diffExp1.5=-1,0,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.875 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 102.964955173037 75.243665467868 88.7889376912204 cerebhem 110.613216262679 107.141564940449 85.5823483070132 cortex 110.826102101174 73.2579838398867 94.3529039635232 heart 101.746074901431 81.1937564900794 99.1437680546886 kidney 90.1322001389385 95.6915809294695 77.33493830695 liver 89.7509060820686 68.3178012225851 83.3815554988402 stomach 85.4156916992093 74.853687835582 107.339679544639 testicle 100.713077395635 74.3653136955131 86.9742768015243 cont.diffExp=27.7212897051691,3.47165132222925,37.5681182612868,20.5523184113513,-5.55938079053098,21.4331048594835,10.5620038636273,26.3477637001221 cont.diffExpScore=1.07071266917471 cont.diffExp1.5=0,0,1,0,0,0,0,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=0,0,1,0,0,0,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=1,0,1,0,0,1,0,1 cont.diffExp1.3Score=0.8 cont.diffExp1.2=1,0,1,1,0,1,0,1 cont.diffExp1.2Score=0.833333333333333 tran.correlation=-0.403310662837149 cont.tran.correlation=0.277877257864171 tran.covariance=-0.00678847661936531 cont.tran.covariance=0.00397984357495414 tran.mean=78.2941358064096 cont.tran.mean=90.1392236359753 weightedLogRatios: wLogRatio Lung -2.06060651409454 cerebhem -1.50114711718831 cortex -3.58182124780160 heart -5.66937879447438 kidney -4.584976753503 liver -3.50040527687852 stomach -2.75118502682799 testicle -3.68732585816368 cont.weightedLogRatios: wLogRatio Lung 1.40441796252149 cerebhem 0.149560484167404 cortex 1.86329143427093 heart 1.01756806579345 kidney -0.271205413189809 liver 1.18986830140253 stomach 0.57833797796605 testicle 1.35284759449785 varWeightedLogRatios=1.78545479002097 cont.varWeightedLogRatios=0.503248037732241 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.5513587501609 0.0985086517038429 46.2026296313966 2.58968847345179e-175 *** df.mm.trans1 -0.734039250047217 0.0791420338089656 -9.27496065894709 6.85507860707489e-19 *** df.mm.trans2 -0.116072702279727 0.0791420338089656 -1.46663784961485 0.143154929810238 df.mm.exp2 -0.00988523150252506 0.106263231088272 -0.0930258886473482 0.925923320345417 df.mm.exp3 -0.101357907182407 0.106263231088272 -0.95383799404904 0.340664438139162 df.mm.exp4 -0.398300079651508 0.106263231088272 -3.74823987161318 0.000200650106411025 *** df.mm.exp5 -0.123985748499216 0.106263231088272 -1.16677939518159 0.243901364905504 df.mm.exp6 0.0268087347048316 0.106263231088272 0.25228608645037 0.800932139726149 df.mm.exp7 -0.0717116181978574 0.106263231088272 -0.674848839654489 0.500109378971469 df.mm.exp8 -0.223375573911994 0.106263231088272 -2.1020965730511 0.0360855198333323 * df.mm.trans1:exp2 0.165710217465696 0.0840084604419385 1.97254201057791 0.049143613403936 * df.mm.trans2:exp2 0.0211088646604074 0.0840084604419385 0.251270699990944 0.801716547843026 df.mm.trans1:exp3 0.0840885895590212 0.0840084604419385 1.00095382199199 0.317373095519577 df.mm.trans2:exp3 0.425333852097255 0.0840084604419385 5.06298829736583 5.97250790574298e-07 *** df.mm.trans1:exp4 0.412694921808594 0.0840084604419385 4.91253999463332 1.25009296042188e-06 *** df.mm.trans2:exp4 1.17483274519370 0.0840084604419385 13.9846955772470 2.61790731430106e-37 *** df.mm.trans1:exp5 0.0872370488623133 0.0840084604419385 1.03843170560906 0.299612281940047 df.mm.trans2:exp5 0.643504136360163 0.0840084604419385 7.65999201717205 1.10064733651194e-13 *** df.mm.trans1:exp6 0.0632355878166679 0.0840084604419385 0.752728802361191 0.451996261681608 df.mm.trans2:exp6 0.368161370080679 0.0840084604419385 4.3824320567704 1.45398925744481e-05 *** df.mm.trans1:exp7 0.131429148182392 0.0840084604419385 1.5644751432295 0.118390702245412 df.mm.trans2:exp7 0.279376293936195 0.0840084604419385 3.32557331090816 0.000952681291781544 *** df.mm.trans1:exp8 0.276799211852895 0.0840084604419385 3.29489685201650 0.00106031226606343 ** df.mm.trans2:exp8 0.627697483599158 0.0840084604419385 7.4718365304764 3.99019186801047e-13 *** df.mm.trans1:probe2 0.0570925076891653 0.056354588469983 1.01309421715634 0.311545429066075 df.mm.trans1:probe3 -0.0130188113635754 0.056354588469983 -0.231015995627575 0.817404645601333 df.mm.trans1:probe4 0.0142874645489908 0.056354588469983 0.253527972377989 0.799973029614806 df.mm.trans1:probe5 0.0568429519607382 0.056354588469983 1.00866590465859 0.313662866083545 df.mm.trans1:probe6 -0.00480399242660773 0.056354588469983 -0.0852458079640942 0.932102901899533 df.mm.trans2:probe2 -0.41711220351216 0.056354588469983 -7.40156595650297 6.41524228307373e-13 *** df.mm.trans2:probe3 -0.515951600971873 0.056354588469983 -9.15544971545117 1.75660727607372e-18 *** df.mm.trans2:probe4 -0.195256375046277 0.056354588469983 -3.46478220048186 0.000580151968570338 *** df.mm.trans2:probe5 -0.575947647653159 0.056354588469983 -10.2200666048681 3.05125334680779e-22 *** df.mm.trans2:probe6 0.125819542617194 0.056354588469983 2.23264060714793 0.0260510532596330 * df.mm.trans3:probe2 0.670974041235226 0.056354588469983 11.9062894336034 1.08073831301538e-28 *** df.mm.trans3:probe3 1.24490154789252 0.056354588469983 22.0905090728435 2.46770621257037e-74 *** df.mm.trans3:probe4 0.986698269735309 0.056354588469983 17.5087476729756 5.11431288192035e-53 *** df.mm.trans3:probe5 0.139676394831023 0.056354588469983 2.47852745664927 0.0135486580577046 * df.mm.trans3:probe6 0.924245660909234 0.056354588469983 16.4005396189084 5.69282287537871e-48 *** df.mm.trans3:probe7 1.03578662921048 0.056354588469983 18.3798100089434 4.97366066319341e-57 *** df.mm.trans3:probe8 0.600992029253959 0.056354588469983 10.6644737468729 6.90871210987743e-24 *** df.mm.trans3:probe9 1.20941394848490 0.056354588469983 21.4607892865563 2.17393464302761e-71 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.38883521606597 0.315844615139998 13.8955518178476 6.30631599425655e-37 *** df.mm.trans1 0.289963662589421 0.253750150646051 1.14271326283421 0.253749488709653 df.mm.trans2 -0.153793518129112 0.253750150646051 -0.606082470247019 0.544757648776944 df.mm.exp2 0.46185318146095 0.340707833739428 1.35556959871423 0.175898436151181 df.mm.exp3 -0.0139508313744227 0.340707833739428 -0.0409466117092343 0.967356146744723 df.mm.exp4 -0.0461107407784074 0.340707833739428 -0.135338070370500 0.892403530770785 df.mm.exp5 0.245403624402785 0.340707833739428 0.72027584957283 0.471719420749958 df.mm.exp6 -0.171076982290100 0.340707833739428 -0.502122244776266 0.61582075560057 df.mm.exp7 -0.381791517386205 0.340707833739428 -1.12058332558974 0.263047425258047 df.mm.exp8 -0.0132054732995224 0.340707833739428 -0.0387589365192639 0.969099326526205 df.mm.trans1:exp2 -0.390202292761926 0.269353192819639 -1.44866407068436 0.148109769047275 df.mm.trans2:exp2 -0.108433904871109 0.269353192819639 -0.402571448053031 0.687449719722083 df.mm.trans1:exp3 0.0875244671777425 0.269353192819639 0.324943121191623 0.745371210072931 df.mm.trans2:exp3 -0.0127936525233426 0.269353192819639 -0.0474976828357454 0.962137101993773 df.mm.trans1:exp4 0.0342022991536807 0.269353192819639 0.126979371566547 0.899011971053916 df.mm.trans2:exp4 0.122217374216882 0.269353192819639 0.453743922384909 0.650226212368941 df.mm.trans1:exp5 -0.378514830700184 0.269353192819639 -1.40527322783079 0.160612108894011 df.mm.trans2:exp5 -0.00500502363920692 0.269353192819639 -0.0185816384309887 0.985182872653707 df.mm.trans1:exp6 0.0337264159334174 0.269353192819639 0.125212608695531 0.900409700658762 df.mm.trans2:exp6 0.0745156274856755 0.269353192819639 0.276646535003473 0.78217525089946 df.mm.trans1:exp7 0.194932655556365 0.269353192819639 0.723706496721923 0.469612213113632 df.mm.trans2:exp7 0.376595176461919 0.269353192819639 1.39814632423567 0.162739959686681 df.mm.trans1:exp8 -0.00890755980168494 0.269353192819639 -0.0330701845723044 0.973632901167891 df.mm.trans2:exp8 0.00146337240048649 0.269353192819639 0.00543291276842733 0.99566752919425 df.mm.trans1:probe2 -0.214912924820148 0.180687614730396 -1.18941702308052 0.234886524533132 df.mm.trans1:probe3 -0.214776620352193 0.180687614730396 -1.18866265777353 0.235183066300719 df.mm.trans1:probe4 0.0857534900138901 0.180687614730396 0.474595285027382 0.635299716347483 df.mm.trans1:probe5 -0.238912257590503 0.180687614730396 -1.32223925777638 0.186742719839301 df.mm.trans1:probe6 -0.0833045276412302 0.180687614730396 -0.461041714262092 0.644985639574652 df.mm.trans2:probe2 0.216964573388671 0.180687614730396 1.20077169490783 0.230455051296233 df.mm.trans2:probe3 0.138249899816737 0.180687614730396 0.765132131624073 0.444583534398441 df.mm.trans2:probe4 0.266733364730697 0.180687614730396 1.47621277268334 0.140568019456268 df.mm.trans2:probe5 0.368501716689578 0.180687614730396 2.03944092814230 0.0419744900702277 * df.mm.trans2:probe6 0.294900780171433 0.180687614730396 1.63210290097334 0.103339183043441 df.mm.trans3:probe2 -0.190992403250147 0.180687614730396 -1.05703096216709 0.291049847442758 df.mm.trans3:probe3 -0.117881195236881 0.180687614730396 -0.652403295116667 0.514465503624737 df.mm.trans3:probe4 -0.0643251423169182 0.180687614730396 -0.356001945196397 0.722001611735368 df.mm.trans3:probe5 0.142674811021197 0.180687614730396 0.789621420561016 0.430153957288238 df.mm.trans3:probe6 0.093926351330837 0.180687614730396 0.519827280198393 0.603432935466085 df.mm.trans3:probe7 -0.188720187649796 0.180687614730396 -1.04445558114974 0.296820837494048 df.mm.trans3:probe8 0.244731080057929 0.180687614730396 1.35444302822355 0.176257110929209 df.mm.trans3:probe9 -0.268102958495110 0.180687614730396 -1.48379267109783 0.138545812927989