chrX.25944_chrX_24114833_24118848_-_1.R fitVsDatCorrelation=0.640682377605663 cont.fitVsDatCorrelation=0.275193540109658 fstatistic=12427.9228060055,37,347 cont.fstatistic=7923.50414149667,37,347 residuals=-0.342117859077321,-0.0705882303998866,-0.0073197392888294,0.0653970232231262,0.401288504820249 cont.residuals=-0.358383955511032,-0.0972495877199709,-0.0195407235656034,0.0911542247542286,0.431447260540707 predictedValues: Include Exclude Both chrX.25944_chrX_24114833_24118848_-_1.R.tl.Lung 47.3338678974967 46.4392565924277 55.5256770860595 chrX.25944_chrX_24114833_24118848_-_1.R.tl.cerebhem 57.3907429233971 51.4323508020974 56.9173021525491 chrX.25944_chrX_24114833_24118848_-_1.R.tl.cortex 50.1278838219565 46.5700346442335 61.1070881738145 chrX.25944_chrX_24114833_24118848_-_1.R.tl.heart 51.1157926505036 49.6997631802747 57.2121439606439 chrX.25944_chrX_24114833_24118848_-_1.R.tl.kidney 50.1939074195185 48.6292116916669 59.5832253926196 chrX.25944_chrX_24114833_24118848_-_1.R.tl.liver 57.4278204679741 49.8134179637456 55.2560684627952 chrX.25944_chrX_24114833_24118848_-_1.R.tl.stomach 49.9649064560905 49.7186196558277 56.1730070467841 chrX.25944_chrX_24114833_24118848_-_1.R.tl.testicle 53.2811736989556 50.5406370248567 57.2427620352804 diffExp=0.894611305068999,5.95839212129969,3.55784917772303,1.41602947022891,1.5646957278516,7.61440250422846,0.24628680026283,2.74053667409898 diffExpScore=0.95998848273399 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 54.1282452881428 51.0624615808302 55.1627782721972 cerebhem 51.0280587646289 49.9936139298266 51.5440326162899 cortex 50.30836338833 51.0066817806139 48.0055204488253 heart 48.5644215733939 49.4706032529478 51.9755637163529 kidney 48.5545296278509 50.4849332224875 54.5375482337845 liver 52.934487480844 50.4975359774207 53.4407126212765 stomach 51.5930081929965 52.742696999609 51.6937949271532 testicle 50.9754020558299 50.9789650093638 50.6891808468634 cont.diffExp=3.06578370731253,1.03444483480231,-0.698318392283873,-0.906181679553846,-1.93040359463664,2.43695150342334,-1.14968880661242,-0.00356295353396519 cont.diffExpScore=3.94006264376343 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=0.75254206882962 cont.tran.correlation=0.399383573087873 tran.covariance=0.00193195343063329 cont.tran.covariance=0.000293406723330725 tran.mean=50.6049616806889 cont.tran.mean=50.8952505078198 weightedLogRatios: wLogRatio Lung 0.07341735695462 cerebhem 0.437922762790033 cortex 0.285481681484411 heart 0.110127189682221 kidney 0.123511902555252 liver 0.566048619113004 stomach 0.0193151306721195 testicle 0.208537846771694 cont.weightedLogRatios: wLogRatio Lung 0.231022275188274 cerebhem 0.080326814619271 cortex -0.054108208195865 heart -0.0719555446502251 kidney -0.152136099447105 liver 0.185952990562034 stomach -0.0871517574661974 testicle -0.000274776217691493 varWeightedLogRatios=0.0363263240069163 cont.varWeightedLogRatios=0.0187258697291092 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.65558471830095 0.0619158320319374 59.0411950923203 4.54802296306505e-183 *** df.mm.trans1 0.253339367817218 0.0515843849054455 4.91116387801444 1.39698964530204e-06 *** df.mm.trans2 0.175404688397114 0.0515843849054455 3.40034467249405 0.000751417650553975 *** df.mm.exp2 0.270025362499408 0.0710724459469677 3.79929744785895 0.000171308963820093 *** df.mm.exp3 -0.0356187986525433 0.0710724459469676 -0.50116185221937 0.616574986503115 df.mm.exp4 0.114801841236024 0.0710724459469676 1.61527916629866 0.107159085809361 df.mm.exp5 0.0342183385268264 0.0710724459469676 0.48145716769561 0.630495089655206 df.mm.exp6 0.268309429711923 0.0710724459469676 3.77515401555377 0.000188052643211903 *** df.mm.exp7 0.110738404865592 0.0710724459469676 1.55810600564137 0.120119663229328 df.mm.exp8 0.172533906710981 0.0710724459469676 2.42757800737182 0.0157081753245639 * df.mm.trans1:exp2 -0.0773684077698079 0.0600671800860422 -1.28803129527610 0.198593323348987 df.mm.trans2:exp2 -0.167903143772672 0.0600671800860422 -2.79525597060095 0.00547432014629957 ** df.mm.trans1:exp3 0.092970152753486 0.0600671800860422 1.54776955769045 0.122589299178182 df.mm.trans2:exp3 0.0384309507773861 0.0600671800860422 0.639799483217563 0.522725151435456 df.mm.trans1:exp4 -0.0379344004262254 0.0600671800860422 -0.631532899861237 0.528107945991371 df.mm.trans2:exp4 -0.0469468219157773 0.0600671800860422 -0.781571930770333 0.434999120175934 df.mm.trans1:exp5 0.0244492521818757 0.0600671800860422 0.407031795846814 0.684235593302443 df.mm.trans2:exp5 0.0118609266412131 0.0600671800860422 0.197461019881792 0.843582397833393 df.mm.trans1:exp6 -0.0750066291404912 0.0600671800860422 -1.24871234229823 0.212612091652935 df.mm.trans2:exp6 -0.198170193736518 0.0600671800860422 -3.29914261752679 0.00107035190879507 ** df.mm.trans1:exp7 -0.0566435792207782 0.0600671800860422 -0.943003802403243 0.346335035255925 df.mm.trans2:exp7 -0.0425040497476538 0.0600671800860422 -0.707608542414837 0.4796633640729 df.mm.trans1:exp8 -0.0541769143156423 0.0600671800860422 -0.901938699936263 0.367715044519238 df.mm.trans2:exp8 -0.0879013492469996 0.0600671800860422 -1.46338398308505 0.144267558114943 df.mm.trans1:probe2 -0.0929264289316925 0.0329001494988504 -2.82449868305126 0.00500915226022004 ** df.mm.trans1:probe3 -0.150321945787245 0.0329001494988504 -4.56903534108553 6.81965287332085e-06 *** df.mm.trans1:probe4 -0.0904123929151176 0.0329001494988504 -2.74808456169102 0.00630771233508787 ** df.mm.trans1:probe5 -0.105123402749704 0.0329001494988504 -3.19522568593122 0.00152537904626937 ** df.mm.trans1:probe6 -0.0781960660132554 0.0329001494988504 -2.37676932185331 0.0180068171202602 * df.mm.trans2:probe2 -0.0108014444159263 0.0329001494988504 -0.328309888570679 0.742875390645568 df.mm.trans2:probe3 0.059332995872875 0.0329001494988504 1.80342633017361 0.0721885627967156 . df.mm.trans2:probe4 -0.0305908080848826 0.0329001494988504 -0.929807570812146 0.353117102489787 df.mm.trans2:probe5 0.094997176330943 0.0329001494988504 2.88743904748099 0.00412743918787082 ** df.mm.trans2:probe6 -0.0413804988179371 0.0329001494988504 -1.25776020620766 0.209324247284429 df.mm.trans3:probe2 -0.0895958315102958 0.0329001494988504 -2.72326517888395 0.00679079273855735 ** df.mm.trans3:probe3 -0.0746413159546986 0.0329001494988504 -2.26872269857943 0.0238989013340636 * df.mm.trans3:probe4 -0.105695694747920 0.0329001494988504 -3.21262050045132 0.00143847185696429 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.86601258859373 0.0775263393249518 49.8670854609726 2.64681944427536e-160 *** df.mm.trans1 0.107367860669135 0.0645900797389859 1.66229645640659 0.097356360803442 . df.mm.trans2 0.0547001409453286 0.0645900797389859 0.846881458675645 0.397644885518707 df.mm.exp2 -0.0122828601746009 0.0889915612907657 -0.138022751780572 0.890302493639815 df.mm.exp3 0.064694614522019 0.0889915612907656 0.726974710676664 0.467731596788465 df.mm.exp4 -0.0806212084022339 0.0889915612907656 -0.905942172863076 0.365595077786489 df.mm.exp5 -0.108644339249959 0.0889915612907656 -1.22083866912932 0.222976011179212 df.mm.exp6 -0.00171060256377621 0.0889915612907656 -0.0192220761043521 0.98467499442559 df.mm.exp7 0.0493563821661329 0.0889915612907656 0.554618679010124 0.579512800289942 df.mm.exp8 0.0229264635785793 0.0889915612907656 0.25762514159821 0.796848935169817 df.mm.trans1:exp2 -0.0466976301941069 0.0752115966598242 -0.620883377935938 0.535083962073636 df.mm.trans2:exp2 -0.0088714841827317 0.0752115966598242 -0.117953674389559 0.906172610956485 df.mm.trans1:exp3 -0.137879424751403 0.0752115966598242 -1.83322028616172 0.0676263256404876 . df.mm.trans2:exp3 -0.065787595298232 0.0752115966598241 -0.874700155559573 0.382342076924302 df.mm.trans1:exp4 -0.0278437388332924 0.0752115966598242 -0.370205394777448 0.71145531655484 df.mm.trans2:exp4 0.048950207661298 0.0752115966598242 0.650833246935253 0.515584858628853 df.mm.trans1:exp5 -2.43158192075532e-05 0.0752115966598241 -0.000323298803474837 0.999742230650409 df.mm.trans2:exp5 0.0972696587605639 0.0752115966598241 1.29328006690918 0.196774508221167 df.mm.trans1:exp6 -0.0205904773941690 0.0752115966598242 -0.273767321910449 0.7844263220222 df.mm.trans2:exp6 -0.00941447509656401 0.0752115966598241 -0.125173184916482 0.900458931359122 df.mm.trans1:exp7 -0.0973263626547691 0.0752115966598242 -1.29403399179209 0.196514266106621 df.mm.trans2:exp7 -0.0169806851244008 0.0752115966598242 -0.22577216650782 0.821511543203823 df.mm.trans1:exp8 -0.0829394034946444 0.0752115966598242 -1.10274754396948 0.270901025552505 df.mm.trans2:exp8 -0.0245629869572035 0.0752115966598241 -0.326585101873317 0.744178605714276 df.mm.trans1:probe2 0.0295504678673811 0.0411950880765659 0.717329886817042 0.473653160885923 df.mm.trans1:probe3 0.0301986868500115 0.0411950880765659 0.73306523325994 0.464013567117459 df.mm.trans1:probe4 0.0433233711992623 0.0411950880765659 1.05166351674600 0.293685764478172 df.mm.trans1:probe5 0.0322729334857415 0.0411950880765659 0.783417028402961 0.433916634644575 df.mm.trans1:probe6 0.0444114845634873 0.0411950880765659 1.07807718437070 0.281748171083785 df.mm.trans2:probe2 -0.008103365847657 0.0411950880765659 -0.196707088781943 0.844171920522556 df.mm.trans2:probe3 0.0242155038711723 0.0411950880765659 0.587825029677445 0.557032082748 df.mm.trans2:probe4 0.0557109990069125 0.0411950880765659 1.35236994525578 0.177137652947696 df.mm.trans2:probe5 0.0182967065874003 0.0411950880765659 0.444147772020628 0.657212601966499 df.mm.trans2:probe6 0.0332490632409634 0.0411950880765659 0.807112323177126 0.420154642861065 df.mm.trans3:probe2 0.0190581831297368 0.0411950880765659 0.462632416134538 0.643917838339944 df.mm.trans3:probe3 -0.0400989254147812 0.0411950880765659 -0.973390937780074 0.33103708984262 df.mm.trans3:probe4 -0.0501279418558686 0.0411950880765659 -1.21684269160197 0.224491048244822