fitVsDatCorrelation=0.904416919867033
cont.fitVsDatCorrelation=0.259015255053908

fstatistic=7303.48032972732,59,853
cont.fstatistic=1413.42173480024,59,853

residuals=-0.86823690283037,-0.130749773581107,0.00774657512549014,0.130118641587737,0.89672552260389
cont.residuals=-0.93704338422349,-0.333855704782133,-0.098463262686524,0.247661888925317,1.68940391303309

predictedValues:
Include	Exclude	Both
Lung	145.347788563621	88.5734822542694	161.981444803311
cerebhem	91.513036297174	102.470625334997	94.394139631479
cortex	102.226916277613	95.6071978687776	130.396949358935
heart	91.2654382987301	83.7562238099647	113.610644167167
kidney	79.4862436918834	85.7187923539617	80.4467714031934
liver	69.8614143825542	92.3039281693977	68.4685697980705
stomach	95.0897529798	76.6798131545215	98.4020950270869
testicle	86.4383725209072	75.0034375165649	82.937449193817


diffExp=56.7743063093517,-10.9575890378232,6.61971840883578,7.50921448876545,-6.23254866207832,-22.4425137868436,18.4099398252785,11.4349350043423
diffExpScore=2.25999710475803
diffExp1.5=1,0,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=1,0,0,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=1,0,0,0,0,-1,0,0
diffExp1.3Score=2
diffExp1.2=1,0,0,0,0,-1,1,0
diffExp1.2Score=1.5

cont.predictedValues:
Include	Exclude	Both
Lung	102.042706574635	104.903120763748	93.8474891193947
cerebhem	103.359782548684	80.2360903655207	111.612724943006
cortex	112.189933357213	95.6005945567334	98.6923526532208
heart	100.111064220532	127.786367369970	102.535754323262
kidney	100.338902779454	91.4171219340594	96.4066079085263
liver	107.621158327212	95.458815998893	108.711912692597
stomach	97.0052495629587	91.1796062821664	100.388240199329
testicle	125.665846996744	117.713250896520	105.027746509836
cont.diffExp=-2.86041418911323,23.1236921831637,16.5893388004795,-27.6753031494382,8.9217808453944,12.1623423283185,5.82564328079224,7.95259610022424
cont.diffExpScore=2.33374481669434

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

tran.correlation=0.0595106067648259
cont.tran.correlation=0.309057003365469

tran.covariance=0.00120619022034651
cont.tran.covariance=0.0038891652681128

tran.mean=91.3339039671711
cont.tran.mean=103.289350783440

weightedLogRatios:
wLogRatio
Lung	2.34348783902406
cerebhem	-0.517185504130909
cortex	0.307535431804750
heart	0.383873959994207
kidney	-0.333153795418837
liver	-1.22176642847495
stomach	0.956967069839356
testicle	0.622715871996227

cont.weightedLogRatios:
wLogRatio
Lung	-0.128255011208778
cerebhem	1.14252759624716
cortex	0.742495811172137
heart	-1.15408671312916
kidney	0.42481596404599
liver	0.553880132239263
stomach	0.281414866970886
testicle	0.313860360047734

varWeightedLogRatios=1.15722814367929
cont.varWeightedLogRatios=0.468251713642775

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.97640400871678	0.0995679394008496	39.9365903587521	1.80298302941974e-197	***
df.mm.trans1	0.668702291600291	0.0859844369528062	7.77701541463041	2.13897327512340e-14	***
df.mm.trans2	0.488594550979884	0.0759668614050813	6.43168010291396	2.100159659987e-10	***
df.mm.exp2	0.22309848232115	0.0977176734224777	2.2830924489636	0.0226701335772371	*  
df.mm.exp3	-0.05862027159917	0.0977176734224777	-0.599894262174336	0.54873602716689	   
df.mm.exp4	-0.166574690836003	0.0977176734224777	-1.70465264881846	0.088623366767891	.  
df.mm.exp5	0.063580175329239	0.0977176734224777	0.650651751135674	0.515446530170702	   
df.mm.exp6	0.169745242178334	0.0977176734224777	1.73709868678974	0.0827307231337824	.  
df.mm.exp7	-0.0700825368416817	0.0977176734224777	-0.717194079505794	0.473450691172751	   
df.mm.exp8	-0.0166011872177517	0.0977176734224777	-0.169889300843025	0.865137478506337	   
df.mm.trans1:exp2	-0.685746459323429	0.0903224775817976	-7.59220160565685	8.25090271737583e-14	***
df.mm.trans2:exp2	-0.0773548223695381	0.066707570606945	-1.15961084575136	0.24653176941918	   
df.mm.trans1:exp3	-0.293314128969743	0.0903224775817976	-3.24741013336478	0.00121008575821838	** 
df.mm.trans2:exp3	0.135035864879906	0.0667075706069449	2.02429594799016	0.043250907906769	*  
df.mm.trans1:exp4	-0.298782556505047	0.0903224775817976	-3.30795350730348	0.000979141793092298	***
df.mm.trans2:exp4	0.110652657472085	0.0667075706069449	1.65877210735306	0.0975293421622054	.  
df.mm.trans1:exp5	-0.667125616292084	0.0903224775817976	-7.38604203685537	3.60149551977404e-13	***
df.mm.trans2:exp5	-0.0963406085444324	0.0667075706069449	-1.44422301198902	0.149043446670756	   
df.mm.trans1:exp6	-0.902361169376192	0.0903224775817976	-9.99043863205589	2.66570209630166e-22	***
df.mm.trans2:exp6	-0.128491058316855	0.0667075706069449	-1.92618404699448	0.0544134203416341	.  
df.mm.trans1:exp7	-0.354225661690514	0.0903224775817976	-3.92178858656442	9.49533886778664e-05	***
df.mm.trans2:exp7	-0.0741114971317747	0.0667075706069449	-1.11099079845757	0.266885366948764	   
df.mm.trans1:exp8	-0.503096521496359	0.0903224775817976	-5.57000355798196	3.41483016145608e-08	***
df.mm.trans2:exp8	-0.149697382198830	0.0667075706069449	-2.24408385490275	0.0250827472037841	*  
df.mm.trans1:probe2	0.243394086293192	0.0618395730266315	3.93589532366877	8.96381782065809e-05	***
df.mm.trans1:probe3	-0.0359208682320891	0.0618395730266315	-0.58087186689694	0.561480249036758	   
df.mm.trans1:probe4	0.8623105207972	0.0618395730266315	13.9443155667624	5.80479739618312e-40	***
df.mm.trans1:probe5	-0.0286668140064839	0.0618395730266315	-0.463567463412764	0.643075931128689	   
df.mm.trans1:probe6	0.0358737726372933	0.0618395730266315	0.58011028992461	0.561993444933992	   
df.mm.trans1:probe7	-0.0904211472850811	0.0618395730266315	-1.46218906210981	0.144057720397942	   
df.mm.trans1:probe8	0.120209776201815	0.0618395730266315	1.94389725411018	0.052236355034758	.  
df.mm.trans1:probe9	0.756938108669886	0.0618395730266315	12.2403514711188	7.47005524447941e-32	***
df.mm.trans1:probe10	0.0500476262304258	0.0618395730266315	0.809313903394394	0.418560297626474	   
df.mm.trans1:probe11	0.327146904085188	0.0618395730266315	5.2902516636766	1.553698236548e-07	***
df.mm.trans1:probe12	0.307216158415664	0.0618395730266315	4.96795406855995	8.1755708803745e-07	***
df.mm.trans1:probe13	0.354480655399987	0.0618395730266315	5.73226233705282	1.37460351620081e-08	***
df.mm.trans1:probe14	0.338827032375115	0.0618395730266315	5.47912955720437	5.62809973355323e-08	***
df.mm.trans1:probe15	0.22231959154669	0.0618395730266315	3.59510230529805	0.000342876503369319	***
df.mm.trans1:probe16	0.373221568974231	0.0618395730266315	6.0353193061909	2.363920176412e-09	***
df.mm.trans1:probe17	1.10742760238196	0.0618395730266315	17.9080732317644	3.98591334990155e-61	***
df.mm.trans1:probe18	1.19231042917260	0.0618395730266315	19.2807028059384	4.92363812483107e-69	***
df.mm.trans1:probe19	1.00046276571916	0.0618395730266315	16.1783582381512	1.51251151166242e-51	***
df.mm.trans1:probe20	1.21136625607867	0.0618395730266315	19.5888521991733	7.67169239694502e-71	***
df.mm.trans1:probe21	1.19180710147521	0.0618395730266315	19.2725635567043	5.49384326387567e-69	***
df.mm.trans1:probe22	1.14838845743733	0.0618395730266315	18.5704460951368	6.52861039491763e-65	***
df.mm.trans2:probe2	0.0220119690562374	0.0618395730266315	0.355952798166279	0.721963928052713	   
df.mm.trans2:probe3	0.0730539904076882	0.0618395730266315	1.18134694067547	0.237794184591403	   
df.mm.trans2:probe4	0.0576405472203814	0.0618395730266315	0.932098078936577	0.35154958136179	   
df.mm.trans2:probe5	-0.0204347062757388	0.0618395730266315	-0.330447079040123	0.741143318206635	   
df.mm.trans2:probe6	0.169071491753052	0.0618395730266315	2.73403394425509	0.00638600468428298	** 
df.mm.trans3:probe2	0.127438781686954	0.0618395730266315	2.06079659754559	0.0396251321809523	*  
df.mm.trans3:probe3	-0.136858595464597	0.0618395730266315	-2.21312322783435	0.0271531665330015	*  
df.mm.trans3:probe4	-0.602864985531255	0.0618395730266315	-9.74885426960546	2.31479302846160e-21	***
df.mm.trans3:probe5	0.34845592772541	0.0618395730266315	5.63483721945081	2.3804085694368e-08	***
df.mm.trans3:probe6	0.120803640021466	0.0618395730266315	1.95350055165227	0.0510868723536288	.  
df.mm.trans3:probe7	0.123144180029563	0.0618395730266315	1.99134913134879	0.0467610679029456	*  
df.mm.trans3:probe8	-0.289791986394694	0.0618395730266315	-4.68618996237075	3.23854242499205e-06	***
df.mm.trans3:probe9	0.223102967638507	0.0618395730266315	3.60777018208755	0.000326807176670562	***
df.mm.trans3:probe10	-0.375620538468839	0.0618395730266315	-6.07411274180493	1.87626429620895e-09	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.72724852369411	0.225407375626189	20.9720223686633	4.44065288846525e-79	***
df.mm.trans1	-0.0816822761123785	0.194656295940801	-0.419623088570533	0.67486648083789	   
df.mm.trans2	-0.0710782163783885	0.171977957632933	-0.413298409614194	0.679491871546052	   
df.mm.exp2	-0.428603385750026	0.221218641773656	-1.93746504505058	0.0530183233680876	.  
df.mm.exp3	-0.0483928288622668	0.221218641773656	-0.218755654922521	0.826892720369469	   
df.mm.exp4	0.0896708421918794	0.221218641773656	0.405349393129481	0.685322347163967	   
df.mm.exp5	-0.181346145387844	0.221218641773656	-0.819759781245703	0.412582055666775	   
df.mm.exp6	-0.188146878928495	0.221218641773656	-0.850501917107878	0.395284762858077	   
df.mm.exp7	-0.258206391848362	0.221218641773656	-1.16719996912625	0.243455800215235	   
df.mm.exp8	0.210895724418628	0.221218641773656	0.953336132650201	0.340689856721205	   
df.mm.trans1:exp2	0.441427904392	0.204476990829385	2.15881455708788	0.0311428207107357	*  
df.mm.trans2:exp2	0.160539539105957	0.151016266032938	1.06306124050863	0.288055036421038	   
df.mm.trans1:exp3	0.143194679836331	0.204476990829385	0.700297276752337	0.483932627483432	   
df.mm.trans2:exp3	-0.0444653967394913	0.151016266032938	-0.294441108282952	0.768492496489866	   
df.mm.trans1:exp4	-0.108782047870687	0.204476990829385	-0.532001412136657	0.594863546133228	   
df.mm.trans2:exp4	0.107651757612793	0.151016266032938	0.71284875755909	0.476134304661496	   
df.mm.trans1:exp5	0.164508211792335	0.204476990829385	0.80453165476012	0.421314165934229	   
df.mm.trans2:exp5	0.0437416711457685	0.151016266032938	0.289648739800176	0.772155364547099	   
df.mm.trans1:exp6	0.241372728488595	0.204476990829385	1.18043955708443	0.238154499720514	   
df.mm.trans2:exp6	0.0938045224644878	0.151016266032938	0.621155090962376	0.534663531984631	   
df.mm.trans1:exp7	0.207580070527658	0.204476990829385	1.01517569133665	0.310309942500675	   
df.mm.trans2:exp7	0.118000383743423	0.151016266032938	0.781375323620346	0.434798590706053	   
df.mm.trans1:exp8	-0.00266076579777952	0.204476990829385	-0.0130125437927618	0.98962082795928	   
df.mm.trans2:exp8	-0.0956813993831977	0.151016266032938	-0.63358340062738	0.526522579218115	   
df.mm.trans1:probe2	-0.149409618782536	0.139995825460039	-1.06724338594785	0.286163900533989	   
df.mm.trans1:probe3	0.0133197786479361	0.139995825460039	0.0951441130774156	0.924222705657852	   
df.mm.trans1:probe4	0.224197555168793	0.139995825460039	1.60145886087717	0.109645568685088	   
df.mm.trans1:probe5	-0.187167908093103	0.139995825460039	-1.33695349470638	0.181594255644585	   
df.mm.trans1:probe6	0.0981526603468083	0.139995825460039	0.701111336886439	0.48342475041131	   
df.mm.trans1:probe7	-0.105361237804173	0.139995825460039	-0.752602711244757	0.451896325452532	   
df.mm.trans1:probe8	-0.062718038744313	0.139995825460039	-0.447999349539288	0.654267425264757	   
df.mm.trans1:probe9	-0.122710171797550	0.139995825460039	-0.876527363543257	0.380990183305144	   
df.mm.trans1:probe10	0.0298898818979705	0.139995825460039	0.213505522752194	0.830983701241004	   
df.mm.trans1:probe11	-0.0444200586174651	0.139995825460039	-0.317295594147161	0.751096967064612	   
df.mm.trans1:probe12	0.0409971450179355	0.139995825460039	0.292845482236454	0.769711483358358	   
df.mm.trans1:probe13	-0.00830128366831398	0.139995825460039	-0.0592966514611077	0.952729716760293	   
df.mm.trans1:probe14	-0.150950468006220	0.139995825460039	-1.07824978002154	0.281227118091171	   
df.mm.trans1:probe15	-0.0384890668458831	0.139995825460039	-0.274930103947062	0.783436514428166	   
df.mm.trans1:probe16	0.0169204337626443	0.139995825460039	0.120863845097111	0.903827343176495	   
df.mm.trans1:probe17	0.181327059650030	0.139995825460039	1.29523190462410	0.195590672836766	   
df.mm.trans1:probe18	-0.0326403699599493	0.139995825460039	-0.233152451886977	0.815698962038987	   
df.mm.trans1:probe19	0.0237481367108852	0.139995825460039	0.169634606123766	0.865337726186428	   
df.mm.trans1:probe20	-0.176760775213003	0.139995825460039	-1.26261461462976	0.207072772245488	   
df.mm.trans1:probe21	-0.122209638189981	0.139995825460039	-0.872952016879	0.382934899391199	   
df.mm.trans1:probe22	-0.0730085760011304	0.139995825460039	-0.521505378901247	0.602150131380947	   
df.mm.trans2:probe2	0.0492822827787921	0.139995825460039	0.352026802348186	0.724905110809533	   
df.mm.trans2:probe3	0.0416234840821865	0.139995825460039	0.297319466101279	0.766295011458245	   
df.mm.trans2:probe4	-0.090252464199445	0.139995825460039	-0.644679681718133	0.519308118177456	   
df.mm.trans2:probe5	0.0118480406572229	0.139995825460039	0.0846313853880229	0.93257430496766	   
df.mm.trans2:probe6	-0.0626300227307253	0.139995825460039	-0.447370644981145	0.654721045504834	   
df.mm.trans3:probe2	-0.154034714811830	0.139995825460039	-1.10028077127056	0.271520214602368	   
df.mm.trans3:probe3	-0.0202226694759592	0.139995825460039	-0.144451946402728	0.885177721060264	   
df.mm.trans3:probe4	0.0494548407161335	0.139995825460039	0.353259395797129	0.723981265819238	   
df.mm.trans3:probe5	0.0252160469574956	0.139995825460039	0.180119991968571	0.857101148770296	   
df.mm.trans3:probe6	-0.0274556105060115	0.139995825460039	-0.196117351469517	0.844565026581282	   
df.mm.trans3:probe7	-0.0711361595871238	0.139995825460039	-0.508130577132311	0.611493146663151	   
df.mm.trans3:probe8	0.0418993758962609	0.139995825460039	0.299290180679144	0.764791551782859	   
df.mm.trans3:probe9	-0.126642013671882	0.139995825460039	-0.904612785815044	0.365925976415069	   
df.mm.trans3:probe10	-0.0452493226908278	0.139995825460039	-0.323219085584406	0.746608546463315