fitVsDatCorrelation=0.698743525347619
cont.fitVsDatCorrelation=0.26348050509621

fstatistic=14385.6374393087,79,1313
cont.fstatistic=7903.68626678134,79,1313

residuals=-0.556986128318862,-0.0789630944123729,-0.00714562243146432,0.0675767691944436,1.03696003951530
cont.residuals=-0.457025393315029,-0.120158191806592,-0.0111141568751869,0.0977761058139221,1.28955713221878

predictedValues:
Include	Exclude	Both
Lung	56.9789957970401	57.4415903772064	50.5617984403037
cerebhem	62.2366406916016	73.3793452065428	54.4541364348817
cortex	55.2986709510099	53.8700198498522	51.2933096276817
heart	57.081878229166	51.8512869068768	52.6324702161169
kidney	56.8632512387869	55.4950580937249	51.4245897484257
liver	56.4451859828021	54.82273727215	53.6448248894931
stomach	58.2861430664671	52.9575984238414	52.9899060848458
testicle	57.5335527251058	54.7492831908352	51.8951366084712


diffExp=-0.462594580166282,-11.1427045149412,1.42865110115770,5.23059132228923,1.36819314506203,1.62244871065212,5.32854464262566,2.7842695342706
diffExpScore=4.10316597832921
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=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	56.7334894529957	51.8756673425874	54.7758289369834
cerebhem	57.257036371755	51.2959331727606	55.03967611202
cortex	56.7735409882166	53.0234985622127	57.5475809346556
heart	56.0911355994223	48.4112878257932	55.3413462201832
kidney	56.1470153680158	46.2158921715855	55.4881721589561
liver	54.5388506905292	49.2616603774677	52.6354776097548
stomach	54.9321623699319	49.6884593198511	54.6295522367299
testicle	57.0419496080679	53.7713738234839	52.9505540332238
cont.diffExp=4.85782211040831,5.96110319899439,3.75004242600388,7.67984777362917,9.93112319643032,5.27719031306157,5.24370305008078,3.27057578458405
cont.diffExpScore=0.978710452896676

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=0,0,0,0,1,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=0.868690209874738
cont.tran.correlation=0.534668404351733

tran.covariance=0.0032698996129281
cont.tran.covariance=0.000464012345513948

tran.mean=57.2057023751881
cont.tran.mean=53.3161845652923

weightedLogRatios:
wLogRatio
Lung	-0.0327214467114451
cerebhem	-0.693923451928292
cortex	0.104690218116587
heart	0.384084980631945
kidney	0.0981146788724137
liver	0.117204965183595
stomach	0.385162141804829
testicle	0.199783507247778

cont.weightedLogRatios:
wLogRatio
Lung	0.357487100539850
cerebhem	0.438940632019269
cortex	0.273675853480487
heart	0.582110958707955
kidney	0.765099968044865
liver	0.401779951473776
stomach	0.396884459695099
testicle	0.237025092617927

varWeightedLogRatios=0.116167497605763
cont.varWeightedLogRatios=0.0291880305126467

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.11775374578335	0.0623487511895018	66.0438848769868	0	***
df.mm.trans1	-0.0372255077304163	0.0537296810488535	-0.692829493935933	0.488539081894444	   
df.mm.trans2	-0.0765621505636962	0.0459208141932654	-1.66726465784060	0.0957002652993853	.  
df.mm.exp2	0.258972588943663	0.0570639083359705	4.53829042726852	6.19029608576841e-06	***
df.mm.exp3	-0.108492344577822	0.0570639083359705	-1.90124279499155	0.0574889730973328	.  
df.mm.exp4	-0.140721779826480	0.0570639083359705	-2.46603823555099	0.0137887107973136	*  
df.mm.exp5	-0.0534281975948672	0.0570639083359704	-0.936287035937013	0.349297594676702	   
df.mm.exp6	-0.115264972057462	0.0570639083359705	-2.01992775151021	0.0435936563680213	*  
df.mm.exp7	-0.105500496205282	0.0570639083359705	-1.84881301126687	0.0647094994767317	.  
df.mm.exp8	-0.064347496830338	0.0570639083359704	-1.12763914542068	0.259678365807320	   
df.mm.trans1:exp2	-0.170711389129023	0.0533463490592263	-3.20005758856141	0.00140687593853294	** 
df.mm.trans2:exp2	-0.0140987053616843	0.0326678337088764	-0.431577602828725	0.666119292878544	   
df.mm.trans1:exp3	0.0785585142467857	0.0533463490592262	1.47261275855201	0.141095143024573	   
df.mm.trans2:exp3	0.0442978377649922	0.0326678337088764	1.35600781367256	0.17532983504125	   
df.mm.trans1:exp4	0.142525771964992	0.0533463490592262	2.67170620817474	0.0076400152716502	** 
df.mm.trans2:exp4	0.038332922016637	0.0326678337088764	1.17341487526372	0.240842288214179	   
df.mm.trans1:exp5	0.0513947767665078	0.0533463490592262	0.963416947417495	0.335515721192086	   
df.mm.trans2:exp5	0.0189535590442197	0.0326678337088764	0.580190263398754	0.561885869131433	   
df.mm.trans1:exp6	0.105852274569125	0.0533463490592262	1.98424590315647	0.0474363456953640	*  
df.mm.trans2:exp6	0.068601381701767	0.0326678337088764	2.09996727401997	0.0359221208400076	*  
df.mm.trans1:exp7	0.128182172924702	0.0533463490592262	2.40282934418607	0.0164068388686291	*  
df.mm.trans2:exp7	0.0242234478418489	0.0326678337088764	0.741507626667849	0.458518312931733	   
df.mm.trans1:exp8	0.0740330949678729	0.0533463490592262	1.38778184961973	0.165438938738412	   
df.mm.trans2:exp8	0.0163431610542729	0.0326678337088764	0.500282975599699	0.61695967756596	   
df.mm.trans1:probe2	0.0194223270933771	0.0405194608368489	0.479333305336438	0.631781355745902	   
df.mm.trans1:probe3	0.0358215377086708	0.0405194608368489	0.884057610068055	0.376826962523716	   
df.mm.trans1:probe4	-0.0860297633351546	0.0405194608368489	-2.12317147263021	0.0339261155432056	*  
df.mm.trans1:probe5	-0.175726420120295	0.0405194608368489	-4.33684003910752	1.55600741615585e-05	***
df.mm.trans1:probe6	0.0937373238701992	0.0405194608368489	2.31339020644010	0.0208550577054427	*  
df.mm.trans1:probe7	-0.0452194416211216	0.0405194608368488	-1.11599317185382	0.264629253161645	   
df.mm.trans1:probe8	-0.137820414018064	0.0405194608368489	-3.40133879305543	0.000690720516781374	***
df.mm.trans1:probe9	-0.0404023211186913	0.0405194608368489	-0.99710905042322	0.318895300461388	   
df.mm.trans1:probe10	-0.0187158799712559	0.0405194608368489	-0.461898544174	0.644230597222733	   
df.mm.trans1:probe11	-0.124142180771849	0.0405194608368489	-3.0637668470394	0.00223020195842145	** 
df.mm.trans1:probe12	-0.270823669205665	0.0405194608368489	-6.6837925187636	3.43258641801345e-11	***
df.mm.trans1:probe13	-0.230023782901733	0.0405194608368489	-5.6768717586821	1.68652079080603e-08	***
df.mm.trans1:probe14	-0.286138445180256	0.0405194608368489	-7.06175351968255	2.65791708355621e-12	***
df.mm.trans1:probe15	-0.21308087995448	0.0405194608368489	-5.2587293994964	1.69183024294825e-07	***
df.mm.trans1:probe16	-0.179972678731475	0.0405194608368489	-4.44163557496811	9.67803964700832e-06	***
df.mm.trans1:probe17	-0.0344500684087782	0.0405194608368489	-0.850210434622784	0.395363108487812	   
df.mm.trans1:probe18	-0.06861490906023	0.0405194608368489	-1.69338159104602	0.0906200548977528	.  
df.mm.trans1:probe19	0.0596403635810043	0.0405194608368489	1.47189430336069	0.141289059051898	   
df.mm.trans1:probe20	-0.0769597381069714	0.0405194608368489	-1.89932779255995	0.0577403757333947	.  
df.mm.trans1:probe21	0.0141294942147563	0.0405194608368489	0.348708840713565	0.7273638133557	   
df.mm.trans1:probe22	-0.0491575584194131	0.0405194608368489	-1.21318392209969	0.225277716603240	   
df.mm.trans1:probe23	0.0233477535801763	0.0405194608368489	0.576210865050396	0.564571416264381	   
df.mm.trans1:probe24	0.0059967703605792	0.0405194608368489	0.147997289123000	0.882367631432518	   
df.mm.trans1:probe25	0.0208006077190157	0.0405194608368488	0.513348580889788	0.607793871530298	   
df.mm.trans1:probe26	-0.0732089979352601	0.0405194608368489	-1.80676140361382	0.0710283404944583	.  
df.mm.trans1:probe27	0.128845363301261	0.0405194608368489	3.17983903635972	0.00150800499898440	** 
df.mm.trans1:probe28	-0.0818721028559585	0.0405194608368489	-2.02056249429417	0.0435277551914604	*  
df.mm.trans1:probe29	-0.182261405092903	0.0405194608368489	-4.49812019530015	7.46141797371097e-06	***
df.mm.trans1:probe30	0.0645085397887597	0.0405194608368489	1.59203845402836	0.111616768312932	   
df.mm.trans1:probe31	-0.0299856996244876	0.0405194608368489	-0.740032048926433	0.459412845672636	   
df.mm.trans1:probe32	-0.0296114365220066	0.0405194608368489	-0.730795423000238	0.465034502105753	   
df.mm.trans2:probe2	0.130597969084722	0.0405194608368489	3.22309246933401	0.00129930859026760	** 
df.mm.trans2:probe3	0.0949241633430726	0.0405194608368489	2.34268081022311	0.0192944343411763	*  
df.mm.trans2:probe4	-0.0124735659081572	0.0405194608368489	-0.307841359449027	0.758251873356947	   
df.mm.trans2:probe5	-0.00891836642165135	0.0405194608368489	-0.220100816680682	0.825826854054583	   
df.mm.trans2:probe6	0.0448722357264745	0.0405194608368489	1.10742430426584	0.268313354512373	   
df.mm.trans3:probe2	-0.202228484685195	0.0405194608368488	-4.99089771948018	6.8163995115086e-07	***
df.mm.trans3:probe3	0.343998565904681	0.0405194608368489	8.48971232094591	5.52434132942446e-17	***
df.mm.trans3:probe4	-0.115990300231985	0.0405194608368489	-2.86258251804038	0.00426875091862759	** 
df.mm.trans3:probe5	-0.0708792787992355	0.0405194608368489	-1.74926510213524	0.080478842175032	.  
df.mm.trans3:probe6	-0.239715535606199	0.0405194608368489	-5.91605936148586	4.20102932541712e-09	***
df.mm.trans3:probe7	-0.0857310603693504	0.0405194608368489	-2.11579963303425	0.0345496880414192	*  
df.mm.trans3:probe8	0.00587031717412027	0.0405194608368489	0.144876487813030	0.884830625439186	   
df.mm.trans3:probe9	-0.106945234802838	0.0405194608368489	-2.63935483330964	0.0084047485487997	** 
df.mm.trans3:probe10	-0.197888316292831	0.0405194608368489	-4.88378453725299	1.16855184000928e-06	***
df.mm.trans3:probe11	-0.133304947066731	0.0405194608368489	-3.28989933018807	0.00102881898052333	** 
df.mm.trans3:probe12	0.241686314662112	0.0405194608368489	5.96469720155604	3.1468433320869e-09	***
df.mm.trans3:probe13	-0.195059942827812	0.0405194608368488	-4.81398169667702	1.65102576104384e-06	***
df.mm.trans3:probe14	-0.180185873028377	0.0405194608368488	-4.44689710344106	9.4475287212412e-06	***
df.mm.trans3:probe15	-0.103839482300160	0.0405194608368489	-2.56270641700462	0.0104966677534289	*  
df.mm.trans3:probe16	-0.173358946693274	0.0405194608368489	-4.27841198063572	2.01880123192601e-05	***
df.mm.trans3:probe17	-0.158832409009215	0.0405194608368489	-3.91990430595195	9.31539742029194e-05	***
df.mm.trans3:probe18	-0.265039367485186	0.0405194608368488	-6.54103884926712	8.73065616317893e-11	***
df.mm.trans3:probe19	0.137709376940946	0.0405194608368489	3.3985984536031	0.000697616075222505	***
df.mm.trans3:probe20	-0.115660752800428	0.0405194608368489	-2.85444945247753	0.00437888873058521	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.0073874063984	0.084076002260865	47.663867199163	1.18202718781756e-288	***
df.mm.trans1	0.0486937882867673	0.072453364328163	0.672070769084215	0.501656883006307	   
df.mm.trans2	-0.0756385469821288	0.0619232687788592	-1.22148827853790	0.222120470662112	   
df.mm.exp2	-0.00685779775483764	0.0769495009079937	-0.089120756780961	0.92899953288891	   
df.mm.exp3	-0.0267720295474192	0.0769495009079937	-0.347916870564628	0.727958382848823	   
df.mm.exp4	-0.0907750083300343	0.0769495009079937	-1.17966987776271	0.238345232895517	   
df.mm.exp5	-0.138838136629036	0.0769495009079937	-1.80427598607873	0.0714171331186749	.  
df.mm.exp6	-0.0512964720427516	0.0769495009079937	-0.666625142950379	0.505128722578225	   
df.mm.exp7	-0.072668777619986	0.0769495009079937	-0.94436970691823	0.345154496791037	   
df.mm.exp8	0.0752041570325348	0.0769495009079937	0.977318321043488	0.328591614382615	   
df.mm.trans1:exp2	0.0160436594108974	0.0719364490634353	0.223025456771570	0.82355038408239	   
df.mm.trans2:exp2	-0.00438057149921848	0.0440518985282823	-0.0994411511323639	0.920803190581595	   
df.mm.trans1:exp3	0.0274777397880522	0.0719364490634353	0.381972423518177	0.702543630446355	   
df.mm.trans2:exp3	0.0486573710353214	0.0440518985282823	1.10454651583478	0.269558506590083	   
df.mm.trans1:exp4	0.0793881183853801	0.0719364490634353	1.10358683836860	0.269974617842948	   
df.mm.trans2:exp4	0.0216581714988156	0.0440518985282823	0.491651261861292	0.623048076414421	   
df.mm.trans1:exp5	0.128446982496650	0.0719364490634352	1.78556189760468	0.0744009638497454	.  
df.mm.trans2:exp5	0.0233120190613898	0.0440518985282823	0.529194423854921	0.596760036965888	   
df.mm.trans1:exp6	0.0118450971744366	0.0719364490634353	0.164660576504010	0.86923649380149	   
df.mm.trans2:exp6	-0.000407272332306546	0.0440518985282823	-0.00924528444659582	0.992624839836416	   
df.mm.trans1:exp7	0.0404031108359055	0.0719364490634353	0.561650058654925	0.574450319156238	   
df.mm.trans2:exp7	0.0295916340108068	0.0440518985282823	0.671744805545857	0.501864343440364	   
df.mm.trans1:exp8	-0.0697818811288347	0.0719364490634353	-0.970049009053803	0.332200720038606	   
df.mm.trans2:exp8	-0.0393127594411804	0.0440518985282823	-0.892419186336332	0.372331812767492	   
df.mm.trans1:probe2	-0.0340335222669155	0.0546396554210624	-0.622872197942089	0.533476675014808	   
df.mm.trans1:probe3	0.00742643407779725	0.0546396554210624	0.135916561343001	0.89190807745849	   
df.mm.trans1:probe4	-0.0694150387401119	0.0546396554210624	-1.27041501644159	0.204161900634817	   
df.mm.trans1:probe5	-0.0185596592813619	0.0546396554210624	-0.339673798056339	0.734156520909378	   
df.mm.trans1:probe6	-0.00290816592191257	0.0546396554210624	-0.053224455745589	0.957561166883727	   
df.mm.trans1:probe7	-0.0366874462782273	0.0546396554210624	-0.671443587912618	0.502056094677782	   
df.mm.trans1:probe8	0.0627388189569052	0.0546396554210624	1.14822867152857	0.251083325027373	   
df.mm.trans1:probe9	-0.0231932616681949	0.0546396554210624	-0.424476719142237	0.671287721857787	   
df.mm.trans1:probe10	-0.120010020488685	0.0546396554210624	-2.19639050729488	0.0282383279322407	*  
df.mm.trans1:probe11	-0.0423593272928093	0.0546396554210624	-0.775248799912465	0.438332253859567	   
df.mm.trans1:probe12	-0.00722901579555564	0.0546396554210624	-0.132303466042156	0.894764537192717	   
df.mm.trans1:probe13	-0.0576564617348185	0.0546396554210624	-1.05521276242517	0.291522152432778	   
df.mm.trans1:probe14	0.0130910061451313	0.0546396554210624	0.239588006993269	0.810687057989358	   
df.mm.trans1:probe15	0.0251453728288902	0.0546396554210624	0.460203722646414	0.64544619892094	   
df.mm.trans1:probe16	0.00896295787298465	0.0546396554210624	0.164037598771709	0.86972679188779	   
df.mm.trans1:probe17	-0.0699576735233928	0.0546396554210624	-1.28034616954092	0.200649555616540	   
df.mm.trans1:probe18	0.0225234991603154	0.0546396554210624	0.412218909265542	0.68024626927301	   
df.mm.trans1:probe19	-0.0667777823942218	0.0546396554210624	-1.22214867351598	0.221870762717978	   
df.mm.trans1:probe20	-0.0673130282177185	0.0546396554210624	-1.23194459589822	0.218190356829369	   
df.mm.trans1:probe21	-0.0162564748953089	0.0546396554210624	-0.297521548590191	0.766115424652092	   
df.mm.trans1:probe22	-0.0917815389476618	0.0546396554210624	-1.6797605738978	0.0932418042982178	.  
df.mm.trans1:probe23	0.0749375340464514	0.0546396554210624	1.37148621214702	0.170457762012676	   
df.mm.trans1:probe24	-0.0178089016531509	0.0546396554210624	-0.325933637683337	0.744526502085993	   
df.mm.trans1:probe25	-0.0252047892145192	0.0546396554210624	-0.461291145053659	0.644666141711595	   
df.mm.trans1:probe26	0.0193307600750783	0.0546396554210624	0.353786273469556	0.723555861143264	   
df.mm.trans1:probe27	-0.0513355656578683	0.0546396554210624	-0.939529454610717	0.347631780150959	   
df.mm.trans1:probe28	-0.0699974944611072	0.0546396554210624	-1.28107496143039	0.200393553861086	   
df.mm.trans1:probe29	-0.0152368385446558	0.0546396554210624	-0.278860443522898	0.780395839520683	   
df.mm.trans1:probe30	-0.0935657488557818	0.0546396554210624	-1.71241469468920	0.0870563834568954	.  
df.mm.trans1:probe31	-0.0866618485580346	0.0546396554210624	-1.5860614033929	0.112966167889548	   
df.mm.trans1:probe32	-0.0714655796939184	0.0546396554210624	-1.30794345504547	0.191121430426751	   
df.mm.trans2:probe2	0.0428578280009477	0.0546396554210624	0.784372223263087	0.432963216429888	   
df.mm.trans2:probe3	0.0728164451695368	0.0546396554210624	1.33266662478746	0.182872446365313	   
df.mm.trans2:probe4	0.0538012281379743	0.0546396554210624	0.984655333628534	0.324974804988066	   
df.mm.trans2:probe5	0.106374613774014	0.0546396554210624	1.94683903026608	0.0517670396491568	.  
df.mm.trans2:probe6	0.168775455586417	0.0546396554210624	3.08888213671563	0.00205127733593058	** 
df.mm.trans3:probe2	0.00951549568749807	0.0546396554210624	0.174149994434812	0.86177442999439	   
df.mm.trans3:probe3	0.0522735439727968	0.0546396554210624	0.956696076685844	0.338896791694837	   
df.mm.trans3:probe4	0.0152475316753236	0.0546396554210624	0.279056146270023	0.780245683061831	   
df.mm.trans3:probe5	0.0404006420853613	0.0546396554210624	0.739401480006182	0.459795410803506	   
df.mm.trans3:probe6	0.0154013121464163	0.0546396554210624	0.281870594309777	0.778087157286319	   
df.mm.trans3:probe7	0.0767125219272451	0.0546396554210624	1.40397155392151	0.160563798113099	   
df.mm.trans3:probe8	0.0152861951067057	0.0546396554210624	0.279763753795805	0.779702826951829	   
df.mm.trans3:probe9	0.0163144540108890	0.0546396554210624	0.298582666474871	0.765305738597411	   
df.mm.trans3:probe10	-0.0238499138528843	0.0546396554210624	-0.436494587476675	0.662549690364909	   
df.mm.trans3:probe11	0.100166328243138	0.0546396554210624	1.83321668980596	0.0669966441019354	.  
df.mm.trans3:probe12	0.0100510257969764	0.0546396554210624	0.183951119741176	0.85408020528523	   
df.mm.trans3:probe13	0.0146726601310812	0.0546396554210624	0.268535004805782	0.788329718602453	   
df.mm.trans3:probe14	0.00325317688694985	0.0546396554210624	0.0595387518804854	0.952532060929077	   
df.mm.trans3:probe15	0.0224060084880997	0.0546396554210624	0.410068627179933	0.681822503487503	   
df.mm.trans3:probe16	-0.00883235676630814	0.0546396554210624	-0.161647373107398	0.871608419195882	   
df.mm.trans3:probe17	0.0242582041637976	0.0546396554210624	0.443967004858646	0.657139595085905	   
df.mm.trans3:probe18	0.0558874349734892	0.0546396554210624	1.02283651942552	0.306573559002533	   
df.mm.trans3:probe19	0.0460266510344968	0.0546396554210624	0.842367154035063	0.399735881292778	   
df.mm.trans3:probe20	-0.0290634926063938	0.0546396554210624	-0.531912077088071	0.594876876853408