fitVsDatCorrelation=0.791202817644574
cont.fitVsDatCorrelation=0.307982531027033

fstatistic=7273.15050863747,59,853
cont.fstatistic=2996.71329549719,59,853

residuals=-0.678780037617486,-0.105957292373417,-0.00787781486955737,0.0815603179216422,1.36023156169992
cont.residuals=-0.562937181947192,-0.18639926835744,-0.0546062524234372,0.133832716288862,1.84604498824860

predictedValues:
Include	Exclude	Both
Lung	58.7424761434523	70.9043623670667	125.764634456037
cerebhem	70.3301199677814	79.0019865846532	73.3476811831028
cortex	50.63906039809	55.4030745318113	63.3415431978754
heart	54.3702916389505	59.9160136296509	82.111603415813
kidney	54.9485273918919	61.2624476131011	69.1899197700276
liver	55.7423315656688	61.4421484307202	69.0466254616159
stomach	55.417253803715	64.0386137454651	67.2787755133592
testicle	55.9499342208926	61.4336131274472	67.7972424813534


diffExp=-12.1618862236144,-8.67186661687178,-4.76401413372128,-5.54572199070036,-6.31392022120925,-5.69981686505136,-8.62135994175015,-5.48367890655465
diffExpScore=0.982836231963769
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=-1,0,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	65.6514004102615	73.0515642782674	65.0953612966575
cerebhem	66.7009200742262	62.430069737767	69.601997133074
cortex	70.1560982147288	62.5942127662258	66.1958155498729
heart	65.85030743056	71.101895036023	62.5484353073611
kidney	71.1753646273552	66.597016945741	76.4577332120808
liver	67.5991378020299	66.9164760302811	64.9409702311751
stomach	65.3597617542184	72.9682661976345	64.7602216772168
testicle	65.2612630488393	72.453484972815	65.7641856725356
cont.diffExp=-7.40016386800589,4.27085033645916,7.56188544850302,-5.25158760546307,4.57834768161422,0.682661771748784,-7.60850444341605,-7.19222192397575
cont.diffExpScore=3.92175999188871

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=0.956940729899019
cont.tran.correlation=-0.686016469220182

tran.covariance=0.0100992086599654
cont.tran.covariance=-0.00151481817789290

tran.mean=60.5963909475224
cont.tran.mean=67.8667024579359

weightedLogRatios:
wLogRatio
Lung	-0.784146302265728
cerebhem	-0.501291359651702
cortex	-0.356921260564153
heart	-0.392814185491682
kidney	-0.441691959960234
liver	-0.396183091296061
stomach	-0.590988081558187
testicle	-0.380657348955130

cont.weightedLogRatios:
wLogRatio
Lung	-0.452621060527948
cerebhem	0.275746271703085
cortex	0.478290845284007
heart	-0.324241270808904
kidney	0.281366426593076
liver	0.0427165360894435
stomach	-0.466345242118334
testicle	-0.442300330142289

varWeightedLogRatios=0.0209121972126011
cont.varWeightedLogRatios=0.151825800635358

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.53587176214550	0.0899143587583802	39.3248843785582	9.20098257511363e-194	***
df.mm.trans1	0.348791166190810	0.0776478408444995	4.49196220264917	8.0283386669386e-06	***
df.mm.trans2	0.697707182367077	0.0686015164241346	10.1704338145158	5.18698501793871e-23	***
df.mm.exp2	0.827379404168724	0.0882434847804827	9.37609622089312	5.99191533891332e-20	***
df.mm.exp3	0.290734048087772	0.0882434847804827	3.29468004137655	0.0010259628901946	** 
df.mm.exp4	0.180599505029602	0.0882434847804827	2.04660440913986	0.0410029783912487	*  
df.mm.exp5	0.384625892916548	0.0882434847804827	4.35868884681238	1.46797280578889e-05	***
df.mm.exp6	0.403971039260256	0.0882434847804827	4.57791348862965	5.39444001593659e-06	***
df.mm.exp7	0.465449551642081	0.0882434847804827	5.27460529012367	1.68768433690761e-07	***
df.mm.exp8	0.425810007077954	0.0882434847804827	4.82539881711622	1.65501343692569e-06	***
df.mm.trans1:exp2	-0.647342327246153	0.0815652880044056	-7.93649287686188	6.52850155057412e-15	***
df.mm.trans2:exp2	-0.719238365471438	0.0602399574757258	-11.9395563278952	1.7009618385984e-30	***
df.mm.trans1:exp3	-0.439173904143873	0.0815652880044056	-5.38432358775158	9.406173933358e-08	***
df.mm.trans2:exp3	-0.537430919005074	0.0602399574757258	-8.92150229723579	2.76364394816744e-18	***
df.mm.trans1:exp4	-0.257944689097765	0.0815652880044056	-3.16243214986053	0.00161990875714296	** 
df.mm.trans2:exp4	-0.34898765633858	0.0602399574757258	-5.7932918773923	9.70454833802089e-09	***
df.mm.trans1:exp5	-0.451392090661469	0.0815652880044056	-5.53411998786895	4.16318909831125e-08	***
df.mm.trans2:exp5	-0.530790797897784	0.0602399574757258	-8.81127444539898	6.8379387826524e-18	***
df.mm.trans1:exp6	-0.456394267952340	0.0815652880044056	-5.59544726829982	2.96520571846902e-08	***
df.mm.trans2:exp6	-0.547206943179029	0.0602399574757258	-9.0837870096361	7.16264086869783e-19	***
df.mm.trans1:exp7	-0.523721645055896	0.0815652880044056	-6.420888810294	2.24720636052988e-10	***
df.mm.trans2:exp7	-0.567295270540525	0.0602399574757258	-9.41725881478455	4.2039579827892e-20	***
df.mm.trans1:exp8	-0.474515827177138	0.0815652880044056	-5.81761971037861	8.43943474888988e-09	***
df.mm.trans2:exp8	-0.569184836740557	0.0602399574757258	-9.44862613772453	3.20640248968643e-20	***
df.mm.trans1:probe2	0.186972600917759	0.0558439351867731	3.34812724591164	0.000849235192079694	***
df.mm.trans1:probe3	0.241858402635802	0.0558439351867731	4.33096990437535	1.66097831239680e-05	***
df.mm.trans1:probe4	0.0887160107821533	0.0558439351867731	1.58864181912392	0.112511843563721	   
df.mm.trans1:probe5	0.48230735108297	0.0558439351867731	8.63670064564516	2.81790746940364e-17	***
df.mm.trans1:probe6	0.0875895578484708	0.0558439351867731	1.56847037293347	0.117142260906909	   
df.mm.trans1:probe7	0.0653555856700934	0.0558439351867731	1.17032557701222	0.242196838270795	   
df.mm.trans1:probe8	0.326317934738655	0.0558439351867731	5.8433907576045	7.27463187738978e-09	***
df.mm.trans1:probe9	0.09627811891785	0.0558439351867731	1.72405684871316	0.0850598947684539	.  
df.mm.trans1:probe10	0.186583667213124	0.0558439351867731	3.34116259158822	0.000870542684047824	***
df.mm.trans1:probe11	0.506856354716443	0.0558439351867731	9.07630081979777	7.62624472685252e-19	***
df.mm.trans1:probe12	0.698519364914587	0.0558439351867731	12.5084194474897	4.40662542265513e-33	***
df.mm.trans1:probe13	0.364736169397918	0.0558439351867731	6.53134791053027	1.11889230889559e-10	***
df.mm.trans1:probe14	0.351008725322302	0.0558439351867731	6.28552991740883	5.2079897761887e-10	***
df.mm.trans1:probe15	0.634658809196776	0.0558439351867731	11.3648654428475	5.72237914282251e-28	***
df.mm.trans1:probe16	0.388950048348454	0.0558439351867731	6.96494699106696	6.5631826946891e-12	***
df.mm.trans1:probe17	0.198019618588708	0.0558439351867731	3.54594671608332	0.000412509476098276	***
df.mm.trans1:probe18	0.166267933907082	0.0558439351867731	2.97736779027105	0.00298959228495130	** 
df.mm.trans1:probe19	0.115267751439504	0.0558439351867731	2.06410510029397	0.0393096460848608	*  
df.mm.trans1:probe20	0.368293502517623	0.0558439351867731	6.59504924367964	7.44917841829689e-11	***
df.mm.trans1:probe21	0.298551191100945	0.0558439351867731	5.34617036035201	1.15402389274039e-07	***
df.mm.trans1:probe22	0.178896127734243	0.0558439351867731	3.20350145697854	0.00140806156740223	** 
df.mm.trans2:probe2	0.0469277007576008	0.0558439351867731	0.840336566551919	0.400955183421289	   
df.mm.trans2:probe3	0.196939977355434	0.0558439351867731	3.52661352923567	0.000443359668879979	***
df.mm.trans2:probe4	0.0493121161805354	0.0558439351867731	0.883034406791146	0.377466470821078	   
df.mm.trans2:probe5	0.0533355924216952	0.0558439351867731	0.95508298695841	0.339806314660252	   
df.mm.trans2:probe6	0.0975328625993402	0.0558439351867731	1.74652560341846	0.081079603726719	.  
df.mm.trans3:probe2	0.308739444299643	0.0558439351867731	5.52861189432741	4.29133838223271e-08	***
df.mm.trans3:probe3	-0.0109576738144349	0.0558439351867731	-0.196219585489210	0.84448503535931	   
df.mm.trans3:probe4	0.418236108817175	0.0558439351867731	7.48937386698057	1.72809652107434e-13	***
df.mm.trans3:probe5	0.195297824247529	0.0558439351867731	3.49720741552944	0.000494444813736133	***
df.mm.trans3:probe6	0.353950786571167	0.0558439351867731	6.3382135479414	3.76180625924471e-10	***
df.mm.trans3:probe7	0.506812226370853	0.0558439351867731	9.07551061141718	7.67688017866779e-19	***
df.mm.trans3:probe8	0.675536692177844	0.0558439351867731	12.0968676351062	3.33990456235442e-31	***
df.mm.trans3:probe9	-0.0600866386230775	0.0558439351867731	-1.07597429196410	0.282242982140776	   
df.mm.trans3:probe10	0.132891918844588	0.0558439351867731	2.37970190317218	0.0175455947443446	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.07628192425438	0.139879429825746	29.1413964821875	4.05779423528736e-130	***
df.mm.trans1	0.155961605402259	0.120796454031504	1.29111079172559	0.197015046944975	   
df.mm.trans2	0.24125652118064	0.106723121146600	2.26058344797880	0.0240363618460462	*  
df.mm.exp2	-0.208198660316014	0.137280057461127	-1.51659799803748	0.129738699138406	   
df.mm.exp3	-0.104892883995280	0.137280057461127	-0.764079546113113	0.445031139296884	   
df.mm.exp4	0.0158856727427763	0.137280057461126	0.115717264667336	0.907903858362525	   
df.mm.exp5	-0.17260273117112	0.137280057461127	-1.25730375091077	0.208987796316098	   
df.mm.exp6	-0.0561094552535498	0.137280057461126	-0.408722550756786	0.682845871979443	   
df.mm.exp7	-0.000431301551870964	0.137280057461126	-0.00314176406863099	0.997493973666362	   
df.mm.exp8	-0.0244031771220065	0.137280057461126	-0.177761996704559	0.858952098223653	   
df.mm.trans1:exp2	0.224058475378778	0.126890811847842	1.76575807275512	0.0777941430504061	.  
df.mm.trans2:exp2	0.0510801546745529	0.0937150753315731	0.545058033553581	0.58585608306983	   
df.mm.trans1:exp3	0.171256685857901	0.126890811847842	1.34963819179642	0.17749013389143	   
df.mm.trans2:exp3	-0.0495998417659658	0.093715075331573	-0.529262144756078	0.596761315187095	   
df.mm.trans1:exp4	-0.0128605078949906	0.126890811847842	-0.101350978118195	0.919295667658589	   
df.mm.trans2:exp4	-0.0429372349500119	0.093715075331573	-0.458167853977557	0.646948547974898	   
df.mm.trans1:exp5	0.253390555311654	0.126890811847842	1.99691807170011	0.0461514150268828	*  
df.mm.trans2:exp5	0.0800969653399807	0.093715075331573	0.854686026304624	0.392964965542301	   
df.mm.trans1:exp6	0.0853457518333284	0.126890811847842	0.67259205446387	0.501389010911969	   
df.mm.trans2:exp6	-0.0316108812241598	0.093715075331573	-0.337308390483788	0.735967416593298	   
df.mm.trans1:exp7	-0.00402082501428279	0.126890811847842	-0.0316872825993443	0.9747288494017	   
df.mm.trans2:exp7	-0.000709613204667255	0.093715075331573	-0.00757202832262124	0.993960223722714	   
df.mm.trans1:exp8	0.0184428902241194	0.126890811847842	0.145344567944247	0.884473164729057	   
df.mm.trans2:exp8	0.0161823947261629	0.093715075331573	0.172676537567814	0.862946649377321	   
df.mm.trans1:probe2	-0.118636269937817	0.0868761999865086	-1.36557848934737	0.172431281669605	   
df.mm.trans1:probe3	-0.162734299236188	0.0868761999865086	-1.87317469297068	0.0613860507274113	.  
df.mm.trans1:probe4	-0.053685164475874	0.0868761999865086	-0.617950192160926	0.536773117099329	   
df.mm.trans1:probe5	-0.168034648021184	0.0868761999865086	-1.93418505928296	0.0534208309090746	.  
df.mm.trans1:probe6	-0.095426321635865	0.0868761999865086	-1.09841730704939	0.272332249829394	   
df.mm.trans1:probe7	0.0695551296881828	0.0868761999865086	0.800623527490664	0.423572556360747	   
df.mm.trans1:probe8	0.0139052395077858	0.0868761999865086	0.160058100031369	0.87287320057283	   
df.mm.trans1:probe9	-0.112896355807676	0.0868761999865086	-1.29950844794326	0.194120588115112	   
df.mm.trans1:probe10	-0.118914820859362	0.0868761999865086	-1.36878478660241	0.171426904184879	   
df.mm.trans1:probe11	-0.176133037704842	0.0868761999865086	-2.02740264574411	0.0429317389604299	*  
df.mm.trans1:probe12	-0.0858866643308786	0.0868761999865086	-0.988609818848158	0.323134419828382	   
df.mm.trans1:probe13	-0.0864411023729671	0.0868761999865085	-0.994991751324195	0.320022439769479	   
df.mm.trans1:probe14	-0.0612809342203829	0.0868761999865086	-0.705382305279231	0.480764927423305	   
df.mm.trans1:probe15	0.0557620615284784	0.0868761999865085	0.641856590609833	0.52113874515416	   
df.mm.trans1:probe16	-0.0378866545724187	0.0868761999865086	-0.436099352622494	0.66287499315777	   
df.mm.trans1:probe17	0.0135786207361539	0.0868761999865086	0.156298511425024	0.875834712301143	   
df.mm.trans1:probe18	-0.0760094184542517	0.0868761999865086	-0.874916472705478	0.381865632099277	   
df.mm.trans1:probe19	-0.0499145976543779	0.0868761999865086	-0.574548583641197	0.565748121803244	   
df.mm.trans1:probe20	-0.0930799933808235	0.0868761999865086	-1.07140958507944	0.284288348002208	   
df.mm.trans1:probe21	-0.128935737439490	0.0868761999865086	-1.48413187339585	0.138143348609308	   
df.mm.trans1:probe22	-0.0592121570098673	0.0868761999865086	-0.681569371347534	0.495696288565081	   
df.mm.trans2:probe2	0.00290116866340174	0.0868761999865085	0.0333942859362205	0.973367978628565	   
df.mm.trans2:probe3	-0.132779657354033	0.0868761999865085	-1.52837782240306	0.126789476142788	   
df.mm.trans2:probe4	-0.0709140976885249	0.0868761999865086	-0.816266108549148	0.414575841825674	   
df.mm.trans2:probe5	-0.0790323729255012	0.0868761999865086	-0.90971259030407	0.363231074748609	   
df.mm.trans2:probe6	-0.142141339337776	0.0868761999865086	-1.63613670211001	0.102179868375703	   
df.mm.trans3:probe2	-0.376662269977763	0.0868761999865085	-4.33562091845933	1.62698455670812e-05	***
df.mm.trans3:probe3	-0.381362693146988	0.0868761999865085	-4.38972576155739	1.27731126414971e-05	***
df.mm.trans3:probe4	-0.305433957402599	0.0868761999865086	-3.51573799786399	0.000461648842724577	***
df.mm.trans3:probe5	-0.389543277233256	0.0868761999865085	-4.48388945757009	8.33100166645218e-06	***
df.mm.trans3:probe6	-0.363385269120317	0.0868761999865085	-4.18279424257448	3.17741246069462e-05	***
df.mm.trans3:probe7	-0.176726471281291	0.0868761999865085	-2.03423344148036	0.0422369802946315	*  
df.mm.trans3:probe8	-0.308705102410381	0.0868761999865086	-3.55339094548704	0.000401175468560723	***
df.mm.trans3:probe9	-0.398010945492318	0.0868761999865085	-4.58135767395589	5.30844491830159e-06	***
df.mm.trans3:probe10	-0.276637605986858	0.0868761999865086	-3.18427378303631	0.00150383776631359	**