chr2.13216_chr2_31140196_31141169_-_1.R 

fitVsDatCorrelation=0.651238009992161
cont.fitVsDatCorrelation=0.269545118749685

fstatistic=6652.37308182844,40,416
cont.fstatistic=4127.23627831364,40,416

residuals=-0.456131109429987,-0.0865403655263866,-0.00147378608788541,0.081935181862258,1.8441186841097
cont.residuals=-0.329588855090487,-0.131306987780049,-0.0296322404603819,0.091817863542548,1.79460360173952

predictedValues:
Include	Exclude	Both
chr2.13216_chr2_31140196_31141169_-_1.R.tl.Lung	46.4140577318053	46.4199338386223	60.9283687242938
chr2.13216_chr2_31140196_31141169_-_1.R.tl.cerebhem	49.2341953081686	59.9712734964181	54.424471651439
chr2.13216_chr2_31140196_31141169_-_1.R.tl.cortex	45.9885540194928	50.4276196175093	55.3382108157946
chr2.13216_chr2_31140196_31141169_-_1.R.tl.heart	46.1961342944944	49.0314833597076	58.512928134153
chr2.13216_chr2_31140196_31141169_-_1.R.tl.kidney	47.3910196226466	48.2594533894837	64.6655666402748
chr2.13216_chr2_31140196_31141169_-_1.R.tl.liver	52.9063720153465	50.1224192214439	67.4631203354732
chr2.13216_chr2_31140196_31141169_-_1.R.tl.stomach	48.7555914644414	49.831749038628	57.5051339220364
chr2.13216_chr2_31140196_31141169_-_1.R.tl.testicle	50.8316898927602	53.2506389982492	61.2149512894848


diffExp=-0.00587610681693462,-10.7370781882495,-4.43906559801651,-2.8353490652132,-0.868433766837171,2.7839527939026,-1.07615757418666,-2.41894910548906
diffExpScore=1.22177575425810
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,-1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	54.6928284766255	55.7209456050048	53.5865657075487
cerebhem	52.6060060430288	51.3840828940071	53.7056264746336
cortex	53.820934401511	54.0992015241733	50.0564948809615
heart	53.5488662962471	56.3837158673067	51.6258999132322
kidney	55.2224229032247	49.5454735373623	52.4030306352965
liver	53.4645180597315	55.6365769431494	55.8984669578557
stomach	53.1368410237274	52.0684842057788	54.9687859801856
testicle	57.8317755448345	53.0563229948625	53.7707470200421
cont.diffExp=-1.02811712837928,1.22192314902172,-0.278267122662257,-2.83484957105956,5.67694936586237,-2.17205888341788,1.06835681794858,4.77545254997193
cont.diffExpScore=2.56494499528773

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=0.365920119208476
cont.tran.correlation=-0.119465544209316

tran.covariance=0.00152803495638059
cont.tran.covariance=-0.000157322737369047

tran.mean=49.6895115818261
cont.tran.mean=53.888687270036

weightedLogRatios:
wLogRatio
Lung	-0.00048582492477155
cerebhem	-0.78816745900763
cortex	-0.357018436013962
heart	-0.230086244147497
kidney	-0.0702300869425514
liver	0.213059101076511
stomach	-0.085097028014485
testicle	-0.18371686850886

cont.weightedLogRatios:
wLogRatio
Lung	-0.0746997850655538
cerebhem	0.0928576486206378
cortex	-0.0205670385460787
heart	-0.206672565815107
kidney	0.429262250388473
liver	-0.159247865591725
stomach	0.080485266334025
testicle	0.345982345877991

varWeightedLogRatios=0.087289416194114
cont.varWeightedLogRatios=0.0519217001676057

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.54442149469	0.0848599802003454	41.7678802931841	6.60869542619487e-151	***
df.mm.trans1	0.268814612278166	0.068830532926142	3.90545591978221	0.000109716687543366	***
df.mm.trans2	0.276399396648103	0.068830532926142	4.01565097490514	7.03347593823083e-05	***
df.mm.exp2	0.428007715617836	0.0930758684124163	4.59848210839513	5.65528554940688e-06	***
df.mm.exp3	0.169835463728060	0.0930758684124163	1.82469921178199	0.068763489789359	.  
df.mm.exp4	0.090478540750669	0.0930758684124163	0.97209451057455	0.331568410422467	   
df.mm.exp5	0.000163159227127823	0.0930758684124163	0.00175297023719263	0.998602173123795	   
df.mm.exp6	0.105778633549649	0.0930758684124163	1.13647753551916	0.256411007833046	   
df.mm.exp7	0.177965503627189	0.0930758684124163	1.91204773764376	0.0565566820252916	.  
df.mm.exp8	0.223505853247718	0.0930758684124163	2.40132976527675	0.0167735551286413	*  
df.mm.trans1:exp2	-0.369021688654343	0.075040164128762	-4.9176556706504	1.26323027338211e-06	***
df.mm.trans2:exp2	-0.171871018672665	0.075040164128762	-2.29038703030753	0.0224984894843069	*  
df.mm.trans1:exp3	-0.179045305568845	0.075040164128762	-2.38599298985567	0.0174795192422140	*  
df.mm.trans2:exp3	-0.0870254060363844	0.075040164128762	-1.15971769314173	0.246828946197878	   
df.mm.trans1:exp4	-0.095184801147559	0.075040164128762	-1.26845139869671	0.205346158845469	   
df.mm.trans2:exp4	-0.0357449069888701	0.075040164128762	-0.476343667472997	0.634079645275764	   
df.mm.trans1:exp5	0.020667210381923	0.075040164128762	0.275415314210401	0.783133926898054	   
df.mm.trans2:exp5	0.0386995989698278	0.075040164128762	0.51571847448818	0.606325019821951	   
df.mm.trans1:exp6	0.0251427703324731	0.075040164128762	0.335057507194820	0.737750592099237	   
df.mm.trans2:exp6	-0.0290392116702541	0.075040164128762	-0.386982251536997	0.698967234147107	   
df.mm.trans1:exp7	-0.128747997758445	0.075040164128762	-1.71572116416917	0.0869576483894244	.  
df.mm.trans2:exp7	-0.107042167404783	0.075040164128762	-1.42646499574692	0.154484203711001	   
df.mm.trans1:exp8	-0.132588258073912	0.075040164128762	-1.76689722914788	0.0779786467092577	.  
df.mm.trans2:exp8	-0.0862250243309173	0.075040164128762	-1.14905164896712	0.251194907360677	   
df.mm.trans1:probe2	0.0571422586010803	0.0476871920560482	1.19827266268727	0.231493099634851	   
df.mm.trans1:probe3	0.0315563135717335	0.0476871920560482	0.66173561938066	0.508507043110521	   
df.mm.trans1:probe4	0.114408668651888	0.0476871920560482	2.39914878018861	0.016872390293268	*  
df.mm.trans1:probe5	-0.00747314460259601	0.0476871920560482	-0.15671177690254	0.875548030622458	   
df.mm.trans1:probe6	0.121127475349455	0.0476871920560482	2.54004209782557	0.0114467148550046	*  
df.mm.trans2:probe2	0.139398369331954	0.0476871920560482	2.92318258470985	0.00365389606806711	** 
df.mm.trans2:probe3	-0.0349851091045101	0.0476871920560482	-0.733637431690065	0.463582987103708	   
df.mm.trans2:probe4	-0.0131704680422406	0.0476871920560482	-0.2761845995621	0.782543439151332	   
df.mm.trans2:probe5	0.0229680441155192	0.0476871920560482	0.48163968405865	0.630315197559861	   
df.mm.trans2:probe6	0.105594258686101	0.0476871920560482	2.21431068036031	0.0273488592449516	*  
df.mm.trans3:probe2	0.161141243828196	0.0476871920560482	3.3791304725764	0.000795748929608668	***
df.mm.trans3:probe3	-0.0618752797966003	0.0476871920560482	-1.29752407572827	0.195169974548259	   
df.mm.trans3:probe4	-0.0422578650518848	0.0476871920560482	-0.886147060246656	0.37605024914329	   
df.mm.trans3:probe5	0.250991449234294	0.0476871920560482	5.26328849346584	2.27183860933379e-07	***
df.mm.trans3:probe6	-0.0796149628855306	0.0476871920560482	-1.66952507482422	0.095765644878766	.  
df.mm.trans3:probe7	-0.087940873962558	0.0476871920560482	-1.84411935723115	0.0658766363177481	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.0727480788945	0.107684769260288	37.8210224795128	1.05064737468395e-136	***
df.mm.trans1	-0.0652048504858474	0.0873438815177109	-0.74653025893549	0.455768839428781	   
df.mm.trans2	-0.0752817528378633	0.0873438815177109	-0.861900702484791	0.389238712836162	   
df.mm.exp2	-0.122149339277341	0.118110484942715	-1.03419556135584	0.301645574653400	   
df.mm.exp3	0.0225393511241152	0.118110484942715	0.190832770985972	0.848749709163564	   
df.mm.exp4	0.0279612170061413	0.118110484942715	0.23673780545142	0.812976731997872	   
df.mm.exp5	-0.085494755122286	0.118110484942715	-0.723854069041814	0.469562178532668	   
df.mm.exp6	-0.066468208286239	0.118110484942715	-0.562762978396685	0.573899442647936	   
df.mm.exp7	-0.122125465098530	0.118110484942715	-1.03399342706757	0.301739948751181	   
df.mm.exp8	0.003372521313257	0.118110484942715	0.0285539536552807	0.977234029764384	   
df.mm.trans1:exp2	0.0832470414576249	0.0952237172384702	0.87422591631398	0.382499640919945	   
df.mm.trans2:exp2	0.0411216730330304	0.0952237172384702	0.431842761715012	0.666079429670944	   
df.mm.trans1:exp3	-0.0386094387448729	0.0952237172384702	-0.405460318758432	0.68534762428412	   
df.mm.trans2:exp3	-0.0520760440625696	0.0952237172384702	-0.546881024736251	0.584753698399384	   
df.mm.trans1:exp4	-0.0490991856474254	0.0952237172384702	-0.515619291824804	0.606394243065226	   
df.mm.trans2:exp4	-0.0161369453729555	0.0952237172384702	-0.16946351015203	0.865514445792686	   
df.mm.trans1:exp5	0.095131243566007	0.0952237172384702	0.9990288798301	0.318361447491036	   
df.mm.trans2:exp5	-0.0319704591145504	0.0952237172384702	-0.335740507110076	0.737235817788996	   
df.mm.trans1:exp6	0.0437538339553161	0.0952237172384702	0.459484624463281	0.646126209782198	   
df.mm.trans2:exp6	0.0649529325137931	0.0952237172384702	0.682108768670839	0.495549781165028	   
df.mm.trans1:exp7	0.0932633629927504	0.0952237172384702	0.979413172447255	0.3279450995532	   
df.mm.trans2:exp7	0.054329201723681	0.0952237172384702	0.570542752365186	0.568617670517704	   
df.mm.trans1:exp8	0.0524332588460787	0.0952237172384702	0.550632346296346	0.582181293597219	   
df.mm.trans2:exp8	-0.0523745934332187	0.0952237172384702	-0.550016266452361	0.582603395619141	   
df.mm.trans1:probe2	0.00365947951989247	0.0605136162075806	0.0604736545133795	0.951807439182302	   
df.mm.trans1:probe3	0.00198798288991157	0.0605136162075806	0.0328518276463957	0.97380850413223	   
df.mm.trans1:probe4	-0.0071668157351422	0.0605136162075806	-0.118433109509731	0.905781657911874	   
df.mm.trans1:probe5	-0.0227125904171590	0.0605136162075806	-0.375330245332682	0.707606168805194	   
df.mm.trans1:probe6	-0.0513062987274617	0.0605136162075806	-0.847847177922156	0.397010630830517	   
df.mm.trans2:probe2	0.120365759561209	0.0605136162075806	1.98906902453683	0.0473481406455037	*  
df.mm.trans2:probe3	-0.00766853555634724	0.0605136162075806	-0.126724133128018	0.899219971703132	   
df.mm.trans2:probe4	0.00598070887826056	0.0605136162075806	0.0988324488449816	0.921318909425874	   
df.mm.trans2:probe5	0.0350880743537351	0.0605136162075806	0.579837672126089	0.562337986685263	   
df.mm.trans2:probe6	0.143801306545928	0.0605136162075806	2.37634627639248	0.0179368427474899	*  
df.mm.trans3:probe2	0.0371097301926326	0.0605136162075806	0.613245952205775	0.540048858726617	   
df.mm.trans3:probe3	0.0131163127596156	0.0605136162075806	0.21674977602764	0.828509608712326	   
df.mm.trans3:probe4	0.030323674833905	0.0605136162075806	0.501104986518825	0.61656228324033	   
df.mm.trans3:probe5	0.111208278564471	0.0605136162075806	1.8377397606349	0.0668137168800322	.  
df.mm.trans3:probe6	0.0691618033842445	0.0605136162075806	1.14291307838880	0.253732004668542	   
df.mm.trans3:probe7	0.0823386494073056	0.0605136162075806	1.36066317909111	0.17435688178431