chr5.18019_chr5_144373933_144377217_+_1.R fitVsDatCorrelation=0.714318433089566 cont.fitVsDatCorrelation=0.273471552919964 fstatistic=8757.3555173089,37,347 cont.fstatistic=4631.17386801741,37,347 residuals=-0.353885118928572,-0.0899775697725533,-0.00782339502042474,0.0737403880527377,0.635574095555578 cont.residuals=-0.429294197556966,-0.135303161668737,-0.0198903103637922,0.106681960035477,0.782525034510221 predictedValues: Include Exclude Both chr5.18019_chr5_144373933_144377217_+_1.R.tl.Lung 66.1788400387627 63.8578957222997 69.518571309276 chr5.18019_chr5_144373933_144377217_+_1.R.tl.cerebhem 70.4172609865905 70.1712287579846 66.0327483471594 chr5.18019_chr5_144373933_144377217_+_1.R.tl.cortex 66.3067105282102 59.7749327699605 74.9939905425213 chr5.18019_chr5_144373933_144377217_+_1.R.tl.heart 63.6072293305575 60.2645504146533 69.9105028390356 chr5.18019_chr5_144373933_144377217_+_1.R.tl.kidney 71.4168746558039 66.6449765944984 72.746306974564 chr5.18019_chr5_144373933_144377217_+_1.R.tl.liver 71.8870854609936 70.5786666910696 66.4785646154177 chr5.18019_chr5_144373933_144377217_+_1.R.tl.stomach 63.4676714116336 59.3521270113705 75.1791849050639 chr5.18019_chr5_144373933_144377217_+_1.R.tl.testicle 68.8245613048542 61.7833388038515 74.6508799401375 diffExp=2.32094431646301,0.246032228605927,6.53177775824972,3.3426789159042,4.77189806130551,1.30841876992400,4.11554440026310,7.04122250100271 diffExpScore=0.967403900208938 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 68.6863586395241 66.2864989809112 63.5847106207566 cerebhem 66.959369027339 68.7925086398212 63.4039264806906 cortex 68.2902410920621 73.1610801869665 67.3167721286151 heart 73.1070000915535 66.1253333619562 70.2873994999628 kidney 70.0967232181546 68.0276206697033 66.3622133530815 liver 65.1267162591536 65.6102709673297 67.2515533707483 stomach 70.4529590329932 65.7998088703348 74.3683456167136 testicle 67.1290352130321 67.1318716493843 66.45007061168 cont.diffExp=2.39985965861287,-1.83313961248216,-4.87083909490437,6.98166672959734,2.06910254845131,-0.483554708176101,4.65315016265838,-0.00283643635221154 cont.diffExpScore=2.34976165816338 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=0.861697450673597 cont.tran.correlation=-0.128069358309083 tran.covariance=0.00302351545244648 cont.tran.covariance=-0.000155149510643156 tran.mean=65.9083719051934 cont.tran.mean=68.1739622437637 weightedLogRatios: wLogRatio Lung 0.149032277800364 cerebhem 0.0148845680663296 cortex 0.429590442356231 heart 0.222719950350512 kidney 0.292797205164212 liver 0.0783592765514275 stomach 0.276015443967152 testicle 0.450875313898671 cont.weightedLogRatios: wLogRatio Lung 0.149788908163804 cerebhem -0.113912267032660 cortex -0.293377040107380 heart 0.425752539856985 kidney 0.126886936251517 liver -0.0309213813950570 stomach 0.288398820494711 testicle -0.00017774139375444 varWeightedLogRatios=0.0242674144273839 cont.varWeightedLogRatios=0.0521185424466567 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.73515254988894 0.0792196589393127 47.1493136918237 6.09308685024955e-153 *** df.mm.trans1 0.387684772649942 0.0660008473550954 5.87393629303173 9.97241739287692e-09 *** df.mm.trans2 0.379859005045469 0.0660008473550953 5.75536557889577 1.90217026240103e-08 *** df.mm.exp2 0.207798911468453 0.0909353027025023 2.28512915548622 0.0229080868504111 * df.mm.exp3 -0.139957569263627 0.0909353027025022 -1.53908949664469 0.124693809379946 df.mm.exp4 -0.103171797018615 0.0909353027025022 -1.13456263906818 0.257341749237885 df.mm.exp5 0.073508633135094 0.0909353027025022 0.808361889722629 0.419436127113008 df.mm.exp6 0.227517918422409 0.0909353027025022 2.50197570867215 0.0128099530220402 * df.mm.exp7 -0.193282853019241 0.0909353027025022 -2.12549853879710 0.0342509785971773 * df.mm.exp8 -0.0650549853817709 0.0909353027025022 -0.715398568525145 0.474843874408105 df.mm.trans1:exp2 -0.145721268860151 0.0768543579840454 -1.89607034243136 0.0587812611446624 . df.mm.trans2:exp2 -0.113520766522605 0.0768543579840454 -1.47708951711198 0.140558617304357 df.mm.trans1:exp3 0.141887900965551 0.0768543579840454 1.84619200117457 0.065715829395854 . df.mm.trans2:exp3 0.0738837225656031 0.0768543579840453 0.961347209236216 0.337047023040002 df.mm.trans1:exp4 0.0635381546528388 0.0768543579840454 0.826734570680156 0.408955640203057 df.mm.trans2:exp4 0.0452556055675088 0.0768543579840454 0.588848918325538 0.55634574574203 df.mm.trans1:exp5 0.00266477303224348 0.0768543579840453 0.0346730244340429 0.972360407733591 df.mm.trans2:exp5 -0.0307891945992635 0.0768543579840453 -0.400617419843065 0.688948361897524 df.mm.trans1:exp6 -0.144782062867025 0.0768543579840454 -1.88384974729840 0.0604212037593048 . df.mm.trans2:exp6 -0.127450226424245 0.0768543579840453 -1.65833441027122 0.0981536130707118 . df.mm.trans1:exp7 0.151452742677231 0.0768543579840454 1.97064612404507 0.0495588957663018 * df.mm.trans2:exp7 0.120110576548577 0.0768543579840454 1.56283364664254 0.119003230577885 df.mm.trans1:exp8 0.104254887351841 0.0768543579840454 1.35652538237954 0.175813964753704 df.mm.trans2:exp8 0.0320284795305624 0.0768543579840453 0.416742529255288 0.677124417873196 df.mm.trans1:probe2 0.256447562733132 0.0420948655104389 6.09213403163235 2.95997497422751e-09 *** df.mm.trans1:probe3 0.0238754562287388 0.0420948655104389 0.567182147732912 0.570957162208295 df.mm.trans1:probe4 0.0646656864152172 0.0420948655104389 1.53618940531313 0.125403218642187 df.mm.trans1:probe5 0.136318107746095 0.0420948655104389 3.23835475165708 0.00131827698402025 ** df.mm.trans1:probe6 0.213927711203073 0.0420948655104389 5.08203812054042 6.11552222873346e-07 *** df.mm.trans2:probe2 0.0512414274535281 0.0420948655104389 1.21728450328036 0.224323177137214 df.mm.trans2:probe3 0.212043148077719 0.0420948655104389 5.0372686907655 7.60983993025832e-07 *** df.mm.trans2:probe4 0.0272244912585473 0.0420948655104389 0.646741376375131 0.518226892182468 df.mm.trans2:probe5 -0.031450392484722 0.0420948655104389 -0.747131321204073 0.455490247947131 df.mm.trans2:probe6 0.157428129585064 0.0420948655104389 3.73984160956694 0.000215345175640283 *** df.mm.trans3:probe2 -0.522752302630384 0.0420948655104389 -12.4184338467776 1.5040629096156e-29 *** df.mm.trans3:probe3 -0.180507791315710 0.0420948655104389 -4.28811896954383 2.3384716047092e-05 *** df.mm.trans3:probe4 -0.341149496556133 0.0420948655104389 -8.1043018529548 9.17271635845328e-15 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.18841318969757 0.108884747197084 38.4664821980662 3.35772750350719e-127 *** df.mm.trans1 0.0125510469599067 0.0907159368681226 0.138355479678865 0.890039734485956 df.mm.trans2 -0.0263303916426394 0.0907159368681226 -0.290251002763901 0.771797596926567 df.mm.exp2 0.014491250485938 0.124987504094627 0.115941594249028 0.907765897922603 df.mm.exp3 0.0358572274351888 0.124987504094627 0.286886498733838 0.774370455007252 df.mm.exp4 -0.040280303648124 0.124987504094627 -0.322274646092846 0.74743871301485 df.mm.exp5 0.00349822500421209 0.124987504094627 0.0279885979766715 0.97768733465765 df.mm.exp6 -0.119536824399750 0.124987504094627 -0.9563902028898 0.339540954603031 df.mm.exp7 -0.138632030278939 0.124987504094627 -1.10916712261077 0.268126204560694 df.mm.exp8 -0.0543390774165302 0.124987504094627 -0.434756080699 0.664009730768894 df.mm.trans1:exp2 -0.0399558627900222 0.105633720873472 -0.378249127831835 0.705476823718158 df.mm.trans2:exp2 0.022617361300769 0.105633720873472 0.21411118640666 0.830586111729842 df.mm.trans1:exp3 -0.04164096936586 0.105633720873472 -0.394201482457838 0.693674437439943 df.mm.trans2:exp3 0.0628201195242153 0.105633720873472 0.594697592821343 0.552433199129898 df.mm.trans1:exp4 0.102653810992726 0.105633720873472 0.97179016457903 0.331831854755929 df.mm.trans2:exp4 0.0378459940295571 0.105633720873472 0.35827568807208 0.720354865976562 df.mm.trans1:exp5 0.0168272082395058 0.105633720873472 0.159297694906170 0.873527013993983 df.mm.trans2:exp5 0.0224293428447656 0.105633720873472 0.212331276975763 0.831973266719814 df.mm.trans1:exp6 0.0663210621208228 0.105633720873472 0.627839875112061 0.530521796961045 df.mm.trans2:exp6 0.109282836543012 0.105633720873472 1.03454498846927 0.301601901181157 df.mm.trans1:exp7 0.164026654316584 0.105633720873472 1.55278686540878 0.121385607629354 df.mm.trans2:exp7 0.13126272272487 0.105633720873472 1.24262140573555 0.214846433193112 df.mm.trans1:exp8 0.03140512803148 0.105633720873472 0.297302109324514 0.766413769468738 df.mm.trans2:exp8 0.067011754771595 0.105633720873472 0.634378437278204 0.526251874603137 df.mm.trans1:probe2 0.0590397136850787 0.0578579717556048 1.02042487653155 0.308237896560393 df.mm.trans1:probe3 0.087196313854005 0.0578579717556048 1.50707519133797 0.132701207146265 df.mm.trans1:probe4 0.0841101308349713 0.0578579717556048 1.45373452063368 0.14692373700585 df.mm.trans1:probe5 -0.00566579426765718 0.0578579717556048 -0.097925905380676 0.922047668912135 df.mm.trans1:probe6 0.0611834224463727 0.0578579717556048 1.05747610208002 0.291029968741045 df.mm.trans2:probe2 0.0803130354781247 0.0578579717556048 1.38810665222368 0.165995121081619 df.mm.trans2:probe3 0.0531850106984787 0.0578579717556048 0.919233928958573 0.358611769053153 df.mm.trans2:probe4 0.0676092009858931 0.0578579717556048 1.16853734990017 0.243392251905253 df.mm.trans2:probe5 0.0491114507716984 0.0578579717556048 0.848827729031841 0.396562344163308 df.mm.trans2:probe6 0.0688157332661196 0.0578579717556048 1.18939069549138 0.235099174957468 df.mm.trans3:probe2 -0.0972821878641903 0.0578579717556048 -1.68139644222434 0.0935856827895194 . df.mm.trans3:probe3 0.0145148053734190 0.0578579717556048 0.250869585175408 0.80206342240733 df.mm.trans3:probe4 -0.00627582796503652 0.0578579717556048 -0.108469546626106 0.913685930113477