chr11.3955_chr11_119190602_119192013_-_0.R 

fitVsDatCorrelation=0.909627859524167
cont.fitVsDatCorrelation=0.305906083261366

fstatistic=6187.31147427317,37,347
cont.fstatistic=1170.43383500274,37,347

residuals=-0.55410153727715,-0.0969338672317647,0.00485442426004816,0.104182200990591,0.70407567181224
cont.residuals=-0.933302461429535,-0.303944367417897,-0.0636882625706953,0.272170450819372,1.079365248948

predictedValues:
Include	Exclude	Both
chr11.3955_chr11_119190602_119192013_-_0.R.tl.Lung	64.9783312509234	130.832414648225	72.5874369927703
chr11.3955_chr11_119190602_119192013_-_0.R.tl.cerebhem	57.1514250862562	78.4856158038116	69.9424117335424
chr11.3955_chr11_119190602_119192013_-_0.R.tl.cortex	77.6034508485212	121.239143553768	70.0814368385564
chr11.3955_chr11_119190602_119192013_-_0.R.tl.heart	78.4851241541258	144.128832772881	65.9144169468734
chr11.3955_chr11_119190602_119192013_-_0.R.tl.kidney	62.5382289116593	116.081922607293	66.1160906500131
chr11.3955_chr11_119190602_119192013_-_0.R.tl.liver	75.6090986994064	141.906110146899	63.1806877104132
chr11.3955_chr11_119190602_119192013_-_0.R.tl.stomach	76.5682603233443	174.343993141401	64.420509303156
chr11.3955_chr11_119190602_119192013_-_0.R.tl.testicle	76.7940655166624	153.82109751435	66.8504484434264


diffExp=-65.8540833973012,-21.3341907175554,-43.635692705247,-65.6437086187556,-53.5436936956333,-66.2970114474921,-97.7757328180563,-77.0270319976876
diffExpScore=0.997967938728167
diffExp1.5=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.875
diffExp1.4=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.4Score=0.875
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	89.344727715607	114.073445633442	108.716917230208
cerebhem	96.8857081339858	93.6929311124234	93.7902330829121
cortex	92.7373849776108	87.8889675048209	80.5414774206005
heart	98.9055400116616	103.788173288517	93.862833054441
kidney	70.8021262277657	92.16644324768	88.1900061887644
liver	96.7675350677551	84.5573115686024	107.500254501432
stomach	107.726867442203	91.0802725616013	93.9176004081836
testicle	85.2351247551966	74.8168827836368	73.4243834116434
cont.diffExp=-24.7287179178348,3.19277702156243,4.84841747278988,-4.88263327685506,-21.3643170199143,12.2102234991528,16.6465948806019,10.4182419715599
cont.diffExpScore=21.0953429707589

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,-1,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=-1,0,0,0,-1,0,0,0
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.784588063522837
cont.tran.correlation=0.09721806975895

tran.covariance=0.0240294840536003
cont.tran.covariance=0.0017864736864979

tran.mean=101.910444686220
cont.tran.mean=92.5293401270318

weightedLogRatios:
wLogRatio
Lung	-3.16617179956771
cerebhem	-1.33365351616113
cortex	-2.04101139429745
heart	-2.83647894942229
kidney	-2.74933607543277
liver	-2.92152668647176
stomach	-3.90820269381812
testicle	-3.25689818265825

cont.weightedLogRatios:
wLogRatio
Lung	-1.12755028342550
cerebhem	0.152694294733346
cortex	0.241795239888948
heart	-0.222538982565566
kidney	-1.15813359387124
liver	0.607625988664155
stomach	0.771419007425925
testicle	0.571050602918193

varWeightedLogRatios=0.615927837986379
cont.varWeightedLogRatios=0.575856486053565

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.58426113748395	0.100542429685046	45.5952889923625	1.36630382308461e-148	***
df.mm.trans1	-0.438614217135341	0.0837656415491088	-5.23620674328862	2.84703053619485e-07	***
df.mm.trans2	0.203138399495525	0.0837656415491087	2.42508020876832	0.0158148087439103	*  
df.mm.exp2	-0.602231731280347	0.115411457209866	-5.21812778245437	3.11700018535213e-07	***
df.mm.exp3	0.136539721755429	0.115411457209866	1.18306903886624	0.237591706168643	   
df.mm.exp4	0.382080276599106	0.115411457209866	3.31059225692233	0.00102880315169430	** 
df.mm.exp5	-0.0645171555720605	0.115411457209866	-0.559018637592811	0.576509589702561	   
df.mm.exp6	0.371564378624113	0.115411457209866	3.21947567084656	0.00140549947115884	** 
df.mm.exp7	0.570601691589477	0.115411457209866	4.94406452690295	1.19365556901927e-06	***
df.mm.exp8	0.411280363180769	0.115411457209866	3.56360081679663	0.000416989257599383	***
df.mm.trans1:exp2	0.473882208156129	0.0975404841053367	4.85831306357236	1.79541962928677e-06	***
df.mm.trans2:exp2	0.0912298743778496	0.0975404841053367	0.93530266139881	0.350282771241080	   
df.mm.trans1:exp3	0.0410183251957940	0.0975404841053367	0.420526159696902	0.674361426352415	   
df.mm.trans2:exp3	-0.212691960380148	0.0975404841053366	-2.18055059220801	0.0298879298788515	*  
df.mm.trans1:exp4	-0.193225019936337	0.0975404841053367	-1.9809725336986	0.0483835073150081	*  
df.mm.trans2:exp4	-0.285289931702373	0.0975404841053366	-2.92483612644654	0.00367303709052152	** 
df.mm.trans1:exp5	0.0262413389650100	0.0975404841053366	0.269030230941558	0.788066307471527	   
df.mm.trans2:exp5	-0.0551038999436658	0.0975404841053366	-0.564933631907728	0.572483940886977	   
df.mm.trans1:exp6	-0.220041598460376	0.0975404841053366	-2.25590020880711	0.0246990623051285	*  
df.mm.trans2:exp6	-0.29031596259072	0.0975404841053366	-2.97636376581031	0.00312162553596712	** 
df.mm.trans1:exp7	-0.40647290575089	0.0975404841053366	-4.16722255870628	3.89705281648642e-05	***
df.mm.trans2:exp7	-0.283488598668122	0.0975404841053366	-2.90636858396125	0.00389139123803525	** 
df.mm.trans1:exp8	-0.244206846877871	0.0975404841053366	-2.50364604110582	0.0127507351027668	*  
df.mm.trans2:exp8	-0.249407367253773	0.0975404841053366	-2.55696257345239	0.0109839344300942	*  
df.mm.trans1:probe2	0.159064284043979	0.053425123414467	2.97733114830589	0.00311203962009711	** 
df.mm.trans1:probe3	0.0376036301346683	0.053425123414467	0.703856682612466	0.481994071173224	   
df.mm.trans1:probe4	0.0304800601947329	0.053425123414467	0.570519228533577	0.568694825828974	   
df.mm.trans1:probe5	0.0578999698479329	0.053425123414467	1.08375921565497	0.279224017667668	   
df.mm.trans1:probe6	-0.00097865824097119	0.053425123414467	-0.0183183150252897	0.985395444786356	   
df.mm.trans2:probe2	0.0775543045096416	0.053425123414467	1.45164483585714	0.14750387570891	   
df.mm.trans2:probe3	0.385366280749021	0.053425123414467	7.21320337923015	3.45575904643989e-12	***
df.mm.trans2:probe4	0.359684060378135	0.053425123414467	6.7324890873483	6.92420045155894e-11	***
df.mm.trans2:probe5	0.0400981988848651	0.053425123414467	0.750549485375769	0.45343246418253	   
df.mm.trans2:probe6	0.00247405301053403	0.053425123414467	0.046308793549068	0.963090769809738	   
df.mm.trans3:probe2	0.147340909349295	0.053425123414467	2.75789553551872	0.00612548024829983	** 
df.mm.trans3:probe3	-0.302167972650640	0.053425123414467	-5.65591529487821	3.24383364305646e-08	***
df.mm.trans3:probe4	-0.10114676535453	0.053425123414467	-1.89324345719977	0.059157277217617	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.64457430800008	0.230421400677137	20.1568703876945	2.27900832071972e-60	***
df.mm.trans1	-0.0964215712242523	0.191972647914191	-0.502267235837425	0.615798126482534	   
df.mm.trans2	0.108684092682410	0.191972647914191	0.566143634852552	0.571662087304995	   
df.mm.exp2	0.0318967168171776	0.264497980681307	0.120593422811836	0.904082874258997	   
df.mm.exp3	0.0764763476018026	0.264497980681307	0.28913773710034	0.772648640986771	   
df.mm.exp4	0.154085467018824	0.264497980681307	0.58255819806988	0.560569097283496	   
df.mm.exp5	-0.236605827490197	0.264497980681307	-0.894546819906662	0.37164943856476	   
df.mm.exp6	-0.208349429991213	0.264497980681307	-0.78771652416603	0.431400273945494	   
df.mm.exp7	0.108325126585146	0.264497980681307	0.409549919081109	0.68238883654007	   
df.mm.exp8	-0.0763962224281832	0.264497980681307	-0.288834804074489	0.772880267935654	   
df.mm.trans1:exp2	0.0491330675599939	0.223541593739907	0.219793850164460	0.826160951103979	   
df.mm.trans2:exp2	-0.228716473012355	0.223541593739907	-1.02314951408313	0.306949909346012	   
df.mm.trans1:exp3	-0.0392068991520209	0.223541593739907	-0.175389727236348	0.860875711264558	   
df.mm.trans2:exp3	-0.337244563569122	0.223541593739907	-1.50864346060585	0.132299855046861	   
df.mm.trans1:exp4	-0.0524224464275021	0.223541593739907	-0.234508690532537	0.814728397443913	   
df.mm.trans2:exp4	-0.248575941159237	0.223541593739907	-1.11198966152338	0.266912409057334	   
df.mm.trans1:exp5	0.00399262644019132	0.223541593739907	0.0178607764818783	0.985760184949763	   
df.mm.trans2:exp5	0.0233594348151063	0.223541593739907	0.104497039787080	0.916835290200617	   
df.mm.trans1:exp6	0.288158753724964	0.223541593739907	1.28906101501736	0.198235532832221	   
df.mm.trans2:exp6	-0.0910635230239904	0.223541593739907	-0.407367244280917	0.683989470245583	   
df.mm.trans1:exp7	0.0787716592743919	0.223541593739907	0.35238032420062	0.724766979224087	   
df.mm.trans2:exp7	-0.333426393733093	0.223541593739907	-1.49156310534780	0.136722235154096	   
df.mm.trans1:exp8	0.0293076009272417	0.223541593739907	0.131105806471709	0.895767585007435	   
df.mm.trans2:exp8	-0.345402713286109	0.223541593739907	-1.54513845726620	0.123224253849511	   
df.mm.trans1:probe2	-0.079413029080184	0.122438773432003	-0.648593797979253	0.517029952761172	   
df.mm.trans1:probe3	-0.16017980542718	0.122438773432003	-1.30824412020214	0.191656433568910	   
df.mm.trans1:probe4	-0.104136494760007	0.122438773432003	-0.85051893155267	0.395623127042538	   
df.mm.trans1:probe5	-0.0814405235454651	0.122438773432003	-0.665153049664399	0.506394446980351	   
df.mm.trans1:probe6	-0.131335187301860	0.122438773432003	-1.07266010284559	0.284169059371225	   
df.mm.trans2:probe2	-0.0408086096192696	0.122438773432003	-0.333298092388461	0.739110576562027	   
df.mm.trans2:probe3	-0.0640561740332739	0.122438773432003	-0.523169027569913	0.601190542595627	   
df.mm.trans2:probe4	-0.0458636294823167	0.122438773432003	-0.374584195812672	0.70819854112147	   
df.mm.trans2:probe5	-0.0520968742318535	0.122438773432003	-0.425493271220867	0.670740888785748	   
df.mm.trans2:probe6	0.0386662894480722	0.122438773432003	0.315801019270630	0.752343400502324	   
df.mm.trans3:probe2	-0.0409271945362399	0.122438773432003	-0.334266616603841	0.738380313564182	   
df.mm.trans3:probe3	0.0820637277645776	0.122438773432003	0.670242975033985	0.503148712927537	   
df.mm.trans3:probe4	0.0865058061800618	0.122438773432003	0.706522972709321	0.480337099447222