fitVsDatCorrelation=0.787626773203883
cont.fitVsDatCorrelation=0.247121381831576

fstatistic=13948.2418300707,59,853
cont.fstatistic=5631.17114462943,59,853

residuals=-0.421457450417243,-0.0807961053712053,-0.00330873320557426,0.077364228526676,0.694210504089825
cont.residuals=-0.501950305728602,-0.140922384543394,-0.0294190482754321,0.107809789402291,0.843677146454158

predictedValues:
Include	Exclude	Both
Lung	49.6082750382799	48.405656114021	55.9351399155102
cerebhem	57.4420539395256	54.3187102908058	59.5626144235409
cortex	60.4565200765101	50.3195231037548	63.1294515408487
heart	51.9316537071894	52.8460592912618	52.618365191474
kidney	47.605911283214	49.4482509305491	53.9443538775633
liver	49.2662569166137	55.02629261127	49.2961682933897
stomach	48.998955463991	50.2803378784202	56.0912111221
testicle	55.5107135836644	49.9358821554089	62.7908584160653


diffExp=1.20261892425886,3.12334364871980,10.1369969727554,-0.914405584072483,-1.84233964733516,-5.7600356946563,-1.28138241442924,5.57483142825543
diffExpScore=2.65453227521219
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=0,0,1,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	52.8095986825748	52.3853066414091	53.304512815213
cerebhem	52.5282397327746	54.197329614226	50.6135969100721
cortex	52.6006928730285	49.5779885325112	55.086572098578
heart	54.7785466578095	58.2979274681215	53.8471456378841
kidney	52.3951114152259	51.578042897331	51.7076787458605
liver	52.8706749531364	56.247555683874	52.1961542123924
stomach	54.0590233588485	55.610396693467	53.4906603460999
testicle	53.1520211390176	51.659022496818	52.6436094754186
cont.diffExp=0.424292041165629,-1.66908988145131,3.02270434051738,-3.51938081031199,0.817068517894974,-3.37688073073765,-1.55137333461855,1.49299864219961
cont.diffExpScore=2.96171486612974

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=0.140053480970210
cont.tran.correlation=0.734184051295605

tran.covariance=0.000629217506080337
cont.tran.covariance=0.000611774782718258

tran.mean=51.96256577403
cont.tran.mean=53.4217174275109

weightedLogRatios:
wLogRatio
Lung	0.0955107503408456
cerebhem	0.224907738559536
cortex	0.735989635206479
heart	-0.069096925085134
kidney	-0.147396347870020
liver	-0.43703749923596
stomach	-0.100800478941134
testicle	0.419498549393374

cont.weightedLogRatios:
wLogRatio
Lung	0.0319660733326708
cerebhem	-0.124403124739054
cortex	0.232772303960571
heart	-0.251215686650967
kidney	0.0620980897862994
liver	-0.247581053841651
stomach	-0.113294292900772
testicle	0.112794370135374

varWeightedLogRatios=0.134277752116183
cont.varWeightedLogRatios=0.0304978532572969

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.26011091705437	0.061816392566779	52.7386148185942	1.05059557468016e-270	***
df.mm.trans1	0.56857793050001	0.0533831245408176	10.6508926817363	5.89086392526745e-25	***
df.mm.trans2	0.633422643159654	0.0471637492443931	13.430286041879	1.91509641754528e-37	***
df.mm.exp2	0.199035799455609	0.0606676616724746	3.28075607281751	0.00107730314934207	** 
df.mm.exp3	0.115548640423678	0.0606676616724745	1.90461668108272	0.0571660502893408	.  
df.mm.exp4	0.194664920528194	0.0606676616724745	3.20870979961496	0.00138310548494421	** 
df.mm.exp5	0.0163490752971410	0.0606676616724745	0.269485832261089	0.787621017671671	   
df.mm.exp6	0.247622645196365	0.0606676616724745	4.08162501026001	4.89225548459763e-05	***
df.mm.exp7	0.0228524283640689	0.0606676616724745	0.376682201589405	0.706503471511723	   
df.mm.exp8	0.0279248486956601	0.0606676616724745	0.460292154433402	0.645423842441412	   
df.mm.trans1:exp2	-0.0524167726194304	0.0560763812668886	-0.934738858592876	0.350187428289566	   
df.mm.trans2:exp2	-0.083783728047233	0.041415152273201	-2.02302112749801	0.0433824575479657	*  
df.mm.trans1:exp3	0.0822181345555158	0.0560763812668886	1.46618117464122	0.142967469837764	   
df.mm.trans2:exp3	-0.0767721741014856	0.041415152273201	-1.85372188408356	0.0641240274064262	.  
df.mm.trans1:exp4	-0.148894073514084	0.0560763812668886	-2.65520117650676	0.00807390968891623	** 
df.mm.trans2:exp4	-0.106898443772011	0.041415152273201	-2.58114332326585	0.0100132862585174	*  
df.mm.trans1:exp5	-0.0575497904127322	0.0560763812668886	-1.02627503973252	0.305052894757323	   
df.mm.trans2:exp5	0.004960942927198	0.041415152273201	0.119785698105670	0.904681117724486	   
df.mm.trans1:exp6	-0.254540897633031	0.0560763812668886	-4.53918194937678	6.45822725414905e-06	***
df.mm.trans2:exp6	-0.119428195469261	0.041415152273201	-2.88368360163052	0.00402940974849915	** 
df.mm.trans1:exp7	-0.0352111028066498	0.0560763812668886	-0.627913249948618	0.530228834290235	   
df.mm.trans2:exp7	0.0151450065174483	0.041415152273201	0.365687572933261	0.714688885325524	   
df.mm.trans1:exp8	0.0844935357062954	0.0560763812668886	1.50675799324780	0.132242930435629	   
df.mm.trans2:exp8	0.00319830816276036	0.041415152273201	0.0772255560395446	0.938462221444822	   
df.mm.trans1:probe2	0.178948940436251	0.0383928737039188	4.66099364731809	3.65022945511236e-06	***
df.mm.trans1:probe3	0.0064934352802635	0.0383928737039188	0.169131264576340	0.865733491997184	   
df.mm.trans1:probe4	-0.00600428069094491	0.0383928737039188	-0.156390499373639	0.87576223037869	   
df.mm.trans1:probe5	0.161442967101574	0.0383928737039188	4.20502430598457	2.88638538345396e-05	***
df.mm.trans1:probe6	0.0439446017283083	0.0383928737039188	1.14460308616656	0.252694680195889	   
df.mm.trans1:probe7	0.222068450325213	0.0383928737039188	5.78410597856723	1.02287578093291e-08	***
df.mm.trans1:probe8	0.0299574316968621	0.0383928737039188	0.780286256451918	0.435438864330707	   
df.mm.trans1:probe9	0.203537762410018	0.0383928737039188	5.30144640851001	1.46421903203457e-07	***
df.mm.trans1:probe10	0.36784844619232	0.0383928737039188	9.58116469814485	1.01284691337415e-20	***
df.mm.trans1:probe11	0.178093218624422	0.0383928737039188	4.63870508881039	4.05591485976106e-06	***
df.mm.trans1:probe12	0.215335507019821	0.0383928737039188	5.60873636812035	2.7538082288055e-08	***
df.mm.trans1:probe13	0.129808685886833	0.0383928737039187	3.38106198790697	0.000754882009717612	***
df.mm.trans1:probe14	0.1786416898161	0.0383928737039188	4.65299084391972	3.79119109306115e-06	***
df.mm.trans1:probe15	0.150633785438482	0.0383928737039187	3.92348295155377	9.42995708647729e-05	***
df.mm.trans1:probe16	0.154109214355725	0.0383928737039187	4.01400571221098	6.49477899004899e-05	***
df.mm.trans1:probe17	0.0480488921157127	0.0383928737039188	1.2515054873532	0.211093211456394	   
df.mm.trans1:probe18	0.207204498029607	0.0383928737039188	5.39695203926497	8.78817202297676e-08	***
df.mm.trans1:probe19	-0.0532828356736671	0.0383928737039188	-1.38783140029001	0.165550789612462	   
df.mm.trans1:probe20	0.0241137271435043	0.0383928737039188	0.628078203508975	0.530120826356853	   
df.mm.trans1:probe21	-0.0289498982920674	0.0383928737039188	-0.754043537228433	0.45103117683899	   
df.mm.trans1:probe22	0.00300760778231831	0.0383928737039188	0.0783376572827713	0.937577835545634	   
df.mm.trans2:probe2	0.0746633978741998	0.0383928737039187	1.94472022203899	0.0521370069460835	.  
df.mm.trans2:probe3	-0.0754814335059956	0.0383928737039188	-1.96602718744367	0.0496194341959012	*  
df.mm.trans2:probe4	-0.04084342528029	0.0383928737039188	-1.06382829259590	0.287707550225528	   
df.mm.trans2:probe5	-0.103742191527206	0.0383928737039187	-2.70212103233672	0.00702671002186624	** 
df.mm.trans2:probe6	-0.0772666109097117	0.0383928737039188	-2.01252481139033	0.0444785067331614	*  
df.mm.trans3:probe2	-0.382516784898829	0.0383928737039187	-9.96322358802191	3.40758896425379e-22	***
df.mm.trans3:probe3	-0.411981147517627	0.0383928737039187	-10.7306671205385	2.75899912864882e-25	***
df.mm.trans3:probe4	-0.69309967566707	0.0383928737039187	-18.0528209743342	6.00295894411926e-62	***
df.mm.trans3:probe5	-0.648223507571443	0.0383928737039187	-16.8839538444156	2.13539069516776e-55	***
df.mm.trans3:probe6	-0.682508181009879	0.0383928737039187	-17.7769496045881	2.20163507643704e-60	***
df.mm.trans3:probe7	-0.640721955327047	0.0383928737039187	-16.6885646609373	2.53488335889582e-54	***
df.mm.trans3:probe8	-0.381482031782657	0.0383928737039187	-9.93627189057533	4.34339623298778e-22	***
df.mm.trans3:probe9	-0.367007587121399	0.0383928737039187	-9.55926326202403	1.22637472505364e-20	***
df.mm.trans3:probe10	-0.171645999340128	0.0383928737039187	-4.47077758919119	8.8460022959316e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.9201732630648	0.0972147566594484	40.3248786271975	8.15282923467965e-200	***
df.mm.trans1	-0.0179930746342658	0.0839522858981193	-0.214325011424959	0.830344838240714	   
df.mm.trans2	0.0315620534486669	0.0741714651334243	0.425528245827302	0.670558970725774	   
df.mm.exp2	0.0804641929121266	0.0954082197568564	0.843367511910253	0.399259366692436	   
df.mm.exp3	-0.0919278541243619	0.0954082197568564	-0.963521322991205	0.335559033499617	   
df.mm.exp4	0.133417663819952	0.0954082197568564	1.39838752006862	0.162360171571549	   
df.mm.exp5	0.00700493847349556	0.0954082197568564	0.0734207020249129	0.94148855695321	   
df.mm.exp6	0.0933044879646173	0.0954082197568564	0.977950203896474	0.328376221543821	   
df.mm.exp7	0.0796414677558099	0.0954082197568564	0.834744301473947	0.404095412401036	   
df.mm.exp8	0.00497802701346958	0.0954082197568564	0.0521760811191725	0.958400607445559	   
df.mm.trans1:exp2	-0.0858062356792337	0.0881878015336131	-0.972994384563814	0.330831923490974	   
df.mm.trans2:exp2	-0.0464586991892474	0.0651310078617715	-0.713311534927379	0.475848102681391	   
df.mm.trans1:exp3	0.0879641788518952	0.0881878015336131	0.99746424473874	0.318822088042462	   
df.mm.trans2:exp3	0.0368486653707352	0.0651310078617715	0.56576224720704	0.571704205001221	   
df.mm.trans1:exp4	-0.096811998282938	0.088187801533613	-1.09779353379206	0.272604440870064	   
df.mm.trans2:exp4	-0.0264772649260168	0.0651310078617715	-0.406523187576183	0.684460195108942	   
df.mm.trans1:exp5	-0.0148846125215880	0.0881878015336131	-0.168783122639866	0.86600724768505	   
df.mm.trans2:exp5	-0.0225350261917984	0.0651310078617715	-0.345995355079178	0.729431523893838	   
df.mm.trans1:exp6	-0.0921486189408079	0.088187801533613	-1.04491343857444	0.296358996688745	   
df.mm.trans2:exp6	-0.0221680467319048	0.0651310078617715	-0.340360873563517	0.73366858102403	   
df.mm.trans1:exp7	-0.0562579603651659	0.088187801533613	-0.637933584768217	0.523688123762518	   
df.mm.trans2:exp7	-0.0198974374889323	0.0651310078617715	-0.30549868859946	0.760060903000587	   
df.mm.trans1:exp8	0.00148513670571413	0.088187801533613	0.0168406137797648	0.986567707473922	   
df.mm.trans2:exp8	-0.0189393057814888	0.0651310078617715	-0.290787850568564	0.771284263393465	   
df.mm.trans1:probe2	0.0920275606743769	0.0603780602459357	1.52418875829274	0.127832211598802	   
df.mm.trans1:probe3	0.118533589300584	0.0603780602459357	1.96318975498328	0.0499486863316244	*  
df.mm.trans1:probe4	0.121357128397537	0.0603780602459357	2.0099540777431	0.0447504887606003	*  
df.mm.trans1:probe5	0.0563023046838194	0.0603780602459357	0.932496083088548	0.351344070041530	   
df.mm.trans1:probe6	0.0547757729189295	0.0603780602459357	0.907213194591105	0.364550278136026	   
df.mm.trans1:probe7	0.0619456792881985	0.0603780602459357	1.02596338861960	0.305199691280068	   
df.mm.trans1:probe8	0.112727368839923	0.0603780602459357	1.86702534630551	0.062240889329714	.  
df.mm.trans1:probe9	0.0883629872851379	0.0603780602459357	1.46349496696668	0.143700375720975	   
df.mm.trans1:probe10	0.0292272247214171	0.0603780602459357	0.484070283185099	0.628460243663569	   
df.mm.trans1:probe11	0.131473447983795	0.0603780602459357	2.17750367349115	0.0297164139867092	*  
df.mm.trans1:probe12	0.109148824991866	0.0603780602459357	1.80775640269452	0.0709965594212955	.  
df.mm.trans1:probe13	0.143430050830457	0.0603780602459357	2.37553260648370	0.0177437224611524	*  
df.mm.trans1:probe14	0.0579723658189797	0.0603780602459357	0.96015614915158	0.337248709758524	   
df.mm.trans1:probe15	0.105245029546448	0.0603780602459357	1.74310054211344	0.0816763747287845	.  
df.mm.trans1:probe16	0.104235504676296	0.0603780602459357	1.72638048078585	0.0846410661499848	.  
df.mm.trans1:probe17	0.156219198439976	0.0603780602459357	2.58735040184554	0.00983608101564411	** 
df.mm.trans1:probe18	2.67006638624722e-05	0.0603780602459357	0.000442224605323744	0.999647259211595	   
df.mm.trans1:probe19	0.173612384695415	0.0603780602459357	2.87542170099944	0.00413532278762383	** 
df.mm.trans1:probe20	0.123333009014034	0.0603780602459357	2.04267922009528	0.0413911580845451	*  
df.mm.trans1:probe21	0.0994441932428692	0.0603780602459357	1.64702530750088	0.099921159283016	.  
df.mm.trans1:probe22	0.125008601662136	0.0603780602459357	2.07043090077659	0.0387123872792974	*  
df.mm.trans2:probe2	0.034393110928626	0.0603780602459357	0.569629279054905	0.569079142487084	   
df.mm.trans2:probe3	0.0535794750730247	0.0603780602459357	0.887399741806568	0.375113858263099	   
df.mm.trans2:probe4	-0.0340010505879716	0.0603780602459357	-0.563135855134735	0.573490365056313	   
df.mm.trans2:probe5	0.0654393338375086	0.0603780602459357	1.08382636956134	0.278748039691392	   
df.mm.trans2:probe6	-0.00915762308687101	0.0603780602459357	-0.151671369526772	0.87948200313393	   
df.mm.trans3:probe2	-0.00155959729787464	0.0603780602459357	-0.0258305300223622	0.97939855204056	   
df.mm.trans3:probe3	0.0636184094283329	0.0603780602459357	1.05366765956373	0.292333466737897	   
df.mm.trans3:probe4	0.0273943392422245	0.0603780602459357	0.453713470267845	0.650150477181207	   
df.mm.trans3:probe5	0.118818862025069	0.0603780602459357	1.96791452956734	0.0494014407845675	*  
df.mm.trans3:probe6	0.0446980286989832	0.0603780602459357	0.740302495921803	0.459320178909237	   
df.mm.trans3:probe7	0.0660197931742494	0.0603780602459357	1.09344011558724	0.274509299364973	   
df.mm.trans3:probe8	0.0660489782283022	0.0603780602459357	1.09392348742685	0.274297349422208	   
df.mm.trans3:probe9	-0.00821205849935483	0.0603780602459357	-0.136010638067950	0.891844962132047	   
df.mm.trans3:probe10	0.0459607841132553	0.0603780602459357	0.76121663938929	0.446738067013394