fitVsDatCorrelation=0.85155825107804
cont.fitVsDatCorrelation=0.232579296677106

fstatistic=7338.56075481886,59,853
cont.fstatistic=2122.08082742263,59,853

residuals=-0.715826402236827,-0.110256736105135,-0.00676624179754501,0.083711934651054,1.51249954039835
cont.residuals=-0.703658318463831,-0.267253783206451,-0.0506826261724201,0.222158157365774,2.02556679407181

predictedValues:
Include	Exclude	Both
Lung	71.998332974136	107.408403950595	66.1993010629011
cerebhem	83.6147926219261	116.599570048044	70.4262706605605
cortex	66.3090658286194	87.5633042861105	75.641932643615
heart	65.5171096662462	85.467488246091	68.3444753755983
kidney	71.0666168772752	112.465648132315	62.8932523406013
liver	68.5471703111746	102.803029226467	59.7675779590476
stomach	77.9164548564638	96.09260283806	61.6945155595466
testicle	69.1662730782843	88.6925447272448	67.3062813427122


diffExp=-35.410070976459,-32.9847774261184,-21.2542384574911,-19.9503785798448,-41.39903125504,-34.2558589152922,-18.1761479815961,-19.5262716489604
diffExpScore=0.995534852656613
diffExp1.5=0,0,0,0,-1,0,0,0
diffExp1.5Score=0.5
diffExp1.4=-1,0,0,0,-1,-1,0,0
diffExp1.4Score=0.75
diffExp1.3=-1,-1,-1,-1,-1,-1,0,0
diffExp1.3Score=0.857142857142857
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	79.4913040427447	80.1877885793583	76.2577315820668
cerebhem	82.9180046904643	69.2425206371178	75.9199804645087
cortex	76.8694680511576	68.4445084216399	79.6218553329319
heart	70.7710938556089	78.7328562458112	80.6416053812039
kidney	77.6641437028708	79.1860000843172	84.015244228618
liver	80.133005006046	70.2354178274158	70.9410892127156
stomach	76.0828534359316	79.1740902285224	77.0716859556292
testicle	74.346271435058	69.9212447686023	74.9130027902542
cont.diffExp=-0.69648453661361,13.6754840533465,8.42495962951767,-7.96176239020234,-1.52185638144637,9.8975871786303,-3.09123679259085,4.42502666645572
cont.diffExpScore=2.05759270655629

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=0.669449757342652
cont.tran.correlation=-0.321785504974742

tran.covariance=0.00671358888772627
cont.tran.covariance=-0.00112098152710582

tran.mean=85.7017754793158
cont.tran.mean=75.8375356882917

weightedLogRatios:
wLogRatio
Lung	-1.79063596587916
cerebhem	-1.52711604395154
cortex	-1.20482304286512
heart	-1.14709314726669
kidney	-2.06248328110791
liver	-1.79551491439660
stomach	-0.935250838770964
testicle	-1.08437840996935

cont.weightedLogRatios:
wLogRatio
Lung	-0.0382094880321623
cerebhem	0.780018125553526
cortex	0.497317701331261
heart	-0.459782516601747
kidney	-0.0846501343663584
liver	0.569233698129204
stomach	-0.173313015019294
testicle	0.262518306428257

varWeightedLogRatios=0.166665571482525
cont.varWeightedLogRatios=0.181412572168322

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.69506129416144	0.0930473415666266	50.4588440154364	2.64380309645804e-258	***
df.mm.trans1	-0.581637765370372	0.0803534081623624	-7.23849527570894	1.01239294442271e-12	***
df.mm.trans2	-0.0402353680039055	0.0709918729205203	-0.566760198719527	0.57102621228374	   
df.mm.exp2	0.169788191054026	0.0913182475277757	1.85930189913448	0.0633285015744351	.  
df.mm.exp3	-0.419933646112199	0.0913182475277756	-4.59857320394230	4.89794870640484e-06	***
df.mm.exp4	-0.354724846224634	0.0913182475277756	-3.88449029441504	0.000110479762236653	***
df.mm.exp5	0.0842151573611064	0.0913182475277756	0.922216091975388	0.356676635605783	   
df.mm.exp6	0.00926211762879936	0.0913182475277756	0.101426800004919	0.919235498692432	   
df.mm.exp7	0.0381429735913098	0.0913182475277756	0.417692790038575	0.676276860800225	   
df.mm.exp8	-0.248175858632535	0.0913182475277756	-2.71770281790668	0.00670698707822962	** 
df.mm.trans1:exp2	-0.0202107069889979	0.084407355151369	-0.239442486413106	0.810820009738098	   
df.mm.trans2:exp2	-0.087681032641905	0.0623389631712244	-1.40652054800903	0.159933808733237	   
df.mm.trans1:exp3	0.337617307841528	0.084407355151369	3.9998564963453	6.88791882512894e-05	***
df.mm.trans2:exp3	0.215657227359682	0.0623389631712244	3.45942916579064	0.000568156172122312	***
df.mm.trans1:exp4	0.260393205422359	0.084407355151369	3.08495870952706	0.00210146488067792	** 
df.mm.trans2:exp4	0.126222467332710	0.0623389631712244	2.02477649469431	0.0432014076543589	*  
df.mm.trans1:exp5	-0.0972404199499825	0.084407355151369	-1.15203728129616	0.249628526993775	   
df.mm.trans2:exp5	-0.0382057603682977	0.0623389631712244	-0.612871283459739	0.540124812145117	   
df.mm.trans1:exp6	-0.0583829572786209	0.084407355151369	-0.691680922520577	0.489325943956611	   
df.mm.trans2:exp6	-0.0530857259462606	0.0623389631712244	-0.851565750306944	0.394694156672846	   
df.mm.trans1:exp7	0.0408512218749491	0.084407355151369	0.483977039698614	0.62852638997269	   
df.mm.trans2:exp7	-0.149469062254974	0.0623389631712244	-2.39768283993483	0.0167132171262946	*  
df.mm.trans1:exp8	0.208046253573528	0.084407355151369	2.46478820714659	0.0139054806304944	*  
df.mm.trans2:exp8	0.0567132659020774	0.0623389631712244	0.909756322804165	0.363208019016067	   
df.mm.trans1:probe2	0.072468026329108	0.0577897655446933	1.25399412242057	0.210187685228016	   
df.mm.trans1:probe3	-0.146072513591437	0.0577897655446933	-2.52765368079695	0.0116623099409825	*  
df.mm.trans1:probe4	0.00152134769186673	0.0577897655446933	0.0263255557022489	0.979003828839263	   
df.mm.trans1:probe5	0.0119414033762826	0.0577897655446933	0.206635262554359	0.836344031462618	   
df.mm.trans1:probe6	0.674803860332629	0.0577897655446933	11.6768748578976	2.49276045715816e-29	***
df.mm.trans1:probe7	-0.230994988156313	0.0577897655446933	-3.99716084637281	6.96533210606381e-05	***
df.mm.trans1:probe8	0.0935460565291057	0.0577897655446933	1.61873050785713	0.105874918048398	   
df.mm.trans1:probe9	0.545501894502128	0.0577897655446933	9.43942044686526	3.47196375010225e-20	***
df.mm.trans1:probe10	0.703519831055422	0.0577897655446933	12.1737789455355	1.49883962311416e-31	***
df.mm.trans1:probe11	0.50675919620558	0.0577897655446933	8.76901284213836	9.6543478304019e-18	***
df.mm.trans1:probe12	0.401173816701939	0.0577897655446933	6.94195266100674	7.65833029932434e-12	***
df.mm.trans1:probe13	0.765838214149663	0.0577897655446933	13.2521426057246	1.38323150197896e-36	***
df.mm.trans1:probe14	0.469414440925582	0.0577897655446933	8.12279538601948	1.59116937051992e-15	***
df.mm.trans1:probe15	0.658473127622832	0.0577897655446933	11.3942861926578	4.26955466524972e-28	***
df.mm.trans1:probe16	0.892038382714709	0.0577897655446933	15.4359232003602	1.37097385603981e-47	***
df.mm.trans1:probe17	-0.078308814617331	0.0577897655446933	-1.35506371896887	0.175755991292739	   
df.mm.trans1:probe18	-0.208745239433598	0.0577897655446933	-3.61214892405403	0.000321418880823085	***
df.mm.trans1:probe19	0.0409089616369743	0.0577897655446933	0.707892846620674	0.479205176811651	   
df.mm.trans1:probe20	0.134058240782197	0.0577897655446933	2.31975747813892	0.0205892507000402	*  
df.mm.trans1:probe21	-0.100321786033765	0.0577897655446933	-1.73597842261841	0.0829287389324656	.  
df.mm.trans1:probe22	0.0154985195146624	0.0577897655446933	0.268187963190060	0.788619480626124	   
df.mm.trans2:probe2	0.0819942934930492	0.0577897655446933	1.41883762150993	0.156311635565636	   
df.mm.trans2:probe3	0.00314356132540823	0.0577897655446933	0.0543965059518553	0.956631999923875	   
df.mm.trans2:probe4	-0.098842696011735	0.0577897655446933	-1.71038409794710	0.0875584924839185	.  
df.mm.trans2:probe5	0.207039970805160	0.0577897655446933	3.58264078169758	0.000359404166514142	***
df.mm.trans2:probe6	0.155664901274014	0.0577897655446933	2.69364133608790	0.00720640723634796	** 
df.mm.trans3:probe2	0.0350752018234795	0.0577897655446933	0.606944871516275	0.544049011012903	   
df.mm.trans3:probe3	0.187336840094306	0.0577897655446933	3.2416957973194	0.00123430582764843	** 
df.mm.trans3:probe4	0.230645287096011	0.0577897655446933	3.99110958354097	7.14212523661667e-05	***
df.mm.trans3:probe5	0.302483211491372	0.0577897655446933	5.23420035780278	2.08752237835224e-07	***
df.mm.trans3:probe6	0.0521081486978128	0.0577897655446933	0.901684722314949	0.367478893146057	   
df.mm.trans3:probe7	0.0905681227453844	0.0577897655446933	1.56720003778768	0.117438814156743	   
df.mm.trans3:probe8	0.182512148446318	0.0577897655446933	3.15820884071882	0.00164328389003417	** 
df.mm.trans3:probe9	0.0637881803489758	0.0577897655446933	1.10379718186680	0.269992409743912	   
df.mm.trans3:probe10	0.0503003006347577	0.0577897655446933	0.87040153495443	0.384325883587646	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.43085446086514	0.172616154952413	25.6688284018761	3.98647268602794e-108	***
df.mm.trans1	-0.101537883811576	0.149067089083646	-0.681155608764853	0.495957902939434	   
df.mm.trans2	-0.0376351106318962	0.131700099434177	-0.285763722226392	0.775128474558948	   
df.mm.exp2	-0.100112604379071	0.169408437681695	-0.590954061964576	0.554707750142963	   
df.mm.exp3	-0.235056601091923	0.169408437681695	-1.38751413039754	0.165647411780129	   
df.mm.exp4	-0.190403583729584	0.169408437681695	-1.12393211539638	0.261358022693721	   
df.mm.exp5	-0.132705130448729	0.169408437681695	-0.783344278860957	0.433642405193991	   
df.mm.exp6	-0.0522093408474362	0.169408437681695	-0.308186189317992	0.758015902113907	   
df.mm.exp7	-0.0671640158089639	0.169408437681695	-0.396462045976480	0.691863360300905	   
df.mm.exp8	-0.186124486291746	0.169408437681695	-1.09867305807671	0.27222070363817	   
df.mm.trans1:exp2	0.142317196022500	0.156587741794849	0.908865498609428	0.363677841672819	   
df.mm.trans2:exp2	-0.0466435028032975	0.115647711639688	-0.403324044565792	0.686810930901996	   
df.mm.trans1:exp3	0.201517731751805	0.156587741794849	1.28693171918796	0.198467207640149	   
df.mm.trans2:exp3	0.076708680843885	0.115647711639688	0.663296140980968	0.507320116741055	   
df.mm.trans1:exp4	0.0742065896177778	0.156587741794849	0.473897820909881	0.635694044732766	   
df.mm.trans2:exp4	0.172092898093034	0.115647711639688	1.48807871468487	0.137099711706212	   
df.mm.trans1:exp5	0.109451177738906	0.156587741794849	0.698976666272524	0.484757148250959	   
df.mm.trans2:exp5	0.120133405855240	0.115647711639688	1.03878757436660	0.299197901855027	   
df.mm.trans1:exp6	0.0602495250022768	0.156587741794849	0.384765271608629	0.700507241705325	   
df.mm.trans2:exp6	-0.080309189072572	0.115647711639688	-0.694429556226613	0.487601951677584	   
df.mm.trans1:exp7	0.0233393065052993	0.156587741794849	0.149049384311812	0.881549895290636	   
df.mm.trans2:exp7	0.0544418763502946	0.115647711639688	0.470756192045664	0.637935205851292	   
df.mm.trans1:exp8	0.119210376550675	0.156587741794849	0.761300822045554	0.446687822273574	   
df.mm.trans2:exp8	0.0491227790585147	0.115647711639688	0.424762222806116	0.671117137149506	   
df.mm.trans1:probe2	0.183712979820306	0.107208298012291	1.71360783844589	0.086964096475287	.  
df.mm.trans1:probe3	0.0508234000213177	0.107208298012291	0.474062185144388	0.635576883028345	   
df.mm.trans1:probe4	0.0209906616396045	0.107208298012291	0.195793255081784	0.844818620745038	   
df.mm.trans1:probe5	0.151007786842820	0.107208298012291	1.40854569695255	0.159333929630876	   
df.mm.trans1:probe6	0.0689590147522508	0.107208298012291	0.64322460136756	0.520251246267351	   
df.mm.trans1:probe7	0.00631266267444912	0.107208298012291	0.0588822207934443	0.953059710415248	   
df.mm.trans1:probe8	0.00130602118061528	0.107208298012291	0.0121820904242463	0.990283187072667	   
df.mm.trans1:probe9	0.0588339100833464	0.107208298012291	0.548781308668859	0.583299148269413	   
df.mm.trans1:probe10	0.0353359653476291	0.107208298012291	0.329601029050735	0.741782363724052	   
df.mm.trans1:probe11	-0.000659649656844177	0.107208298012291	-0.00615297200939193	0.99509210827392	   
df.mm.trans1:probe12	0.0211986903416654	0.107208298012291	0.197733671130895	0.843300554014955	   
df.mm.trans1:probe13	0.0205265606835857	0.107208298012291	0.191464290210375	0.848207419979888	   
df.mm.trans1:probe14	-0.00395428007477209	0.107208298012291	-0.0368840859158004	0.97058605852381	   
df.mm.trans1:probe15	0.142163066578729	0.107208298012291	1.32604536416043	0.185179634941939	   
df.mm.trans1:probe16	0.137862377394058	0.107208298012291	1.28593010009591	0.198816416059477	   
df.mm.trans1:probe17	0.0703931669709147	0.107208298012291	0.656601851498885	0.511614050900336	   
df.mm.trans1:probe18	0.242623830723961	0.107208298012291	2.26310682309446	0.0238797221849297	*  
df.mm.trans1:probe19	0.0476108660387727	0.107208298012291	0.444096836919416	0.657085210510751	   
df.mm.trans1:probe20	0.0605697277828842	0.107208298012291	0.564972384655709	0.572241097024188	   
df.mm.trans1:probe21	0.0832745138374064	0.107208298012291	0.776754368657723	0.437519042197516	   
df.mm.trans1:probe22	0.0837025034597454	0.107208298012291	0.780746500146369	0.435168215940781	   
df.mm.trans2:probe2	0.0291975658308429	0.107208298012291	0.272344271592628	0.78542322810615	   
df.mm.trans2:probe3	0.0325100779260962	0.107208298012291	0.303242179279527	0.761779248615938	   
df.mm.trans2:probe4	0.0258729753176189	0.107208298012291	0.241333700817194	0.809354492156904	   
df.mm.trans2:probe5	-0.0901268010339317	0.107208298012291	-0.840670010670244	0.400768409253633	   
df.mm.trans2:probe6	-0.139023562946012	0.107208298012291	-1.29676121646920	0.195064027470335	   
df.mm.trans3:probe2	0.147580102434492	0.107208298012291	1.37657350383057	0.169005359277899	   
df.mm.trans3:probe3	0.0956809070039367	0.107208298012291	0.892476690498034	0.372389179712429	   
df.mm.trans3:probe4	0.0998245445836289	0.107208298012291	0.931127034328854	0.352051304840401	   
df.mm.trans3:probe5	-0.0536571155762884	0.107208298012291	-0.500494052896322	0.616856346331225	   
df.mm.trans3:probe6	0.0275347349683818	0.107208298012291	0.256833990268411	0.797368864396464	   
df.mm.trans3:probe7	0.088960506397289	0.107208298012291	0.829791238613728	0.406888984960321	   
df.mm.trans3:probe8	-0.0429230107810243	0.107208298012291	-0.40037022858159	0.68898409797175	   
df.mm.trans3:probe9	0.0212733239671019	0.107208298012291	0.198429826436223	0.842756065100398	   
df.mm.trans3:probe10	0.0400994242329350	0.107208298012291	0.374032840520774	0.708472835063703