fitVsDatCorrelation=0.86572480746391
cont.fitVsDatCorrelation=0.306866955787285

fstatistic=7016.53636668777,43,485
cont.fstatistic=1932.36052101418,43,485

residuals=-0.617416406641604,-0.0941706829325968,-0.008035026752483,0.0871534831663106,0.899317862593593
cont.residuals=-0.735748388210978,-0.237360050700377,-0.0489249770474798,0.201405899972267,1.25284203571267

predictedValues:
Include	Exclude	Both
Lung	94.7945543900023	71.2332545855606	84.4818099651347
cerebhem	79.4614620936697	66.1574437215185	80.9765567451012
cortex	116.772595058077	64.8500852480438	91.4925853950238
heart	71.9834211798962	65.8994002452961	71.5071966403623
kidney	79.0815536793048	69.5486024357092	73.3093733954093
liver	77.6316962234837	69.0770525504683	66.945914936936
stomach	68.8690875692502	77.6288652025866	75.2690897451107
testicle	70.1271623082538	67.6974429417909	65.3127559581033


diffExp=23.5612998044417,13.3040183721512,51.9225098100332,6.08402093460012,9.5329512435956,8.55464367301542,-8.75977763333637,2.42971936646296
diffExpScore=1.15348554838475
diffExp1.5=0,0,1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=1,0,1,0,0,0,0,0
diffExp1.3Score=0.666666666666667
diffExp1.2=1,1,1,0,0,0,0,0
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	81.4676228747612	74.9855570268432	75.978209248974
cerebhem	86.1668841044172	80.7117912640388	94.4813530963469
cortex	75.1095499024486	83.027505992746	77.4696543438535
heart	80.8018289251045	75.9288590012031	93.033619381641
kidney	77.9855408187397	65.3451008765011	59.3943307326975
liver	74.110456924024	70.082256556347	89.8260574246927
stomach	73.2813830046288	66.3663651602958	66.442831513423
testicle	73.0926261099387	85.8056606749356	71.1742680002638
cont.diffExp=6.48206584791798,5.45509284037837,-7.91795609029737,4.87296992390142,12.6404399422386,4.02820036767704,6.91501784433304,-12.7130345649969
cont.diffExpScore=2.93914061935823

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=-0.385230212887045
cont.tran.correlation=0.133287709906168

tran.covariance=-0.00400532948474247
cont.tran.covariance=0.000892243887764809

tran.mean=75.675854964557
cont.tran.mean=76.5168118260608

weightedLogRatios:
wLogRatio
Lung	1.25983453193386
cerebhem	0.784914363457993
cortex	2.62676890585624
heart	0.373738022490669
kidney	0.553154619025998
liver	0.50129151011993
stomach	-0.51389814929134
testicle	0.149251847256523

cont.weightedLogRatios:
wLogRatio
Lung	0.361384683233180
cerebhem	0.289308016304075
cortex	-0.437885689058195
heart	0.27125992424087
kidney	0.754775447360303
liver	0.239062946932321
stomach	0.420723398125882
testicle	-0.70106791840531

varWeightedLogRatios=0.853593045381946
cont.varWeightedLogRatios=0.22795661812992

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.76069900115336	0.0983667465828524	48.3974429015349	8.5851526381876e-188	***
df.mm.trans1	0.0110524787166711	0.0869542435783942	0.127106835294435	0.898908521583994	   
df.mm.trans2	-0.637512131526958	0.0818377976885615	-7.78994730470446	4.10382367755832e-14	***
df.mm.exp2	-0.207985615275092	0.112649270490431	-1.84631124879551	0.0654561275945449	.  
df.mm.exp3	0.034913213623059	0.112649270490431	0.309928448458302	0.756748491584181	   
df.mm.exp4	-0.186368413479296	0.112649270490431	-1.65441296395369	0.0986906103341738	.  
df.mm.exp5	-0.0633184971740163	0.112649270490431	-0.562085283804786	0.574317585638142	   
df.mm.exp6	0.00217784368059165	0.112649270490431	0.01933295858118	0.984583442394416	   
df.mm.exp7	-0.118058290747638	0.112649270490431	-1.04801646946898	0.295152994599163	   
df.mm.exp8	-0.094964242059328	0.112649270490431	-0.843008051857686	0.399639486763672	   
df.mm.trans1:exp2	0.0315458013980323	0.104870763592256	0.300806443258907	0.76369100174245	   
df.mm.trans2:exp2	0.134063259253489	0.094994205734975	1.41127827972490	0.158803732569405	   
df.mm.trans1:exp3	0.173603233421125	0.104870763592256	1.65540163411135	0.0984899263927547	.  
df.mm.trans2:exp3	-0.128794756485435	0.094994205734975	-1.35581697314002	0.175788357238331	   
df.mm.trans1:exp4	-0.088907719876824	0.104870763592256	-0.847783660873326	0.396976644358620	   
df.mm.trans2:exp4	0.108537985798604	0.094994205734975	1.14257480189281	0.253778892838935	   
df.mm.trans1:exp5	-0.117913822253168	0.104870763592256	-1.1243726870496	0.261411123711804	   
df.mm.trans2:exp5	0.0393845527933591	0.094994205734975	0.414599527293678	0.67861841001347	   
df.mm.trans1:exp6	-0.201914007866490	0.104870763592256	-1.92536032875229	0.0547686864252104	.  
df.mm.trans2:exp6	-0.0329150266689459	0.094994205734975	-0.346495098456592	0.729120940720498	   
df.mm.trans1:exp7	-0.201446252846313	0.104870763592256	-1.92090002919735	0.05533021827254	.  
df.mm.trans2:exp7	0.204037854865786	0.094994205734975	2.14789789847849	0.0322166000601255	*  
df.mm.trans1:exp8	-0.206437523985508	0.104870763592256	-1.96849452520581	0.0495802313708218	*  
df.mm.trans2:exp8	0.0440528826668985	0.094994205734975	0.463742839113808	0.643040056221627	   
df.mm.trans1:probe2	-0.0468386333171679	0.052435381796128	-0.893263893820386	0.372158881545318	   
df.mm.trans1:probe3	0.104066811064911	0.052435381796128	1.98466774723847	0.0477444699944175	*  
df.mm.trans1:probe4	-0.0993362228487561	0.052435381796128	-1.89445026327798	0.0587598733120198	.  
df.mm.trans1:probe5	0.0441570743477496	0.052435381796128	0.842123635514566	0.400133810527739	   
df.mm.trans1:probe6	0.0250184965350977	0.052435381796128	0.4771300537559	0.633484436822278	   
df.mm.trans1:probe7	-0.228165078767126	0.052435381796128	-4.35135725061078	1.65073170021011e-05	***
df.mm.trans1:probe8	-0.480717039426325	0.052435381796128	-9.1677989738948	1.37345987648360e-18	***
df.mm.trans1:probe9	-0.376457579058634	0.052435381796128	-7.1794571940436	2.64540664593737e-12	***
df.mm.trans1:probe10	-0.624126190497422	0.052435381796128	-11.9027681141727	7.72974666304378e-29	***
df.mm.trans1:probe11	-0.584027050217678	0.052435381796128	-11.1380337133505	8.20305702349794e-26	***
df.mm.trans1:probe12	-0.577623565431112	0.052435381796128	-11.0159122646794	2.43549876546019e-25	***
df.mm.trans1:probe13	-0.67658326882206	0.052435381796128	-12.9031818906680	5.91485650289103e-33	***
df.mm.trans2:probe2	0.0934709004063679	0.052435381796128	1.78259215828328	0.075278126732546	.  
df.mm.trans2:probe3	0.23832231973345	0.052435381796128	4.54506692942681	6.94243933666908e-06	***
df.mm.trans2:probe4	-0.0243539066021985	0.052435381796128	-0.464455597880225	0.642529784149541	   
df.mm.trans2:probe5	0.323286712182491	0.052435381796128	6.1654306902818	1.48118240141720e-09	***
df.mm.trans2:probe6	0.65423006113531	0.052435381796128	12.4768818062391	3.51908953649861e-31	***
df.mm.trans3:probe2	0.235957605467921	0.052435381796128	4.49996924567724	8.51755115066405e-06	***
df.mm.trans3:probe3	0.670933083018271	0.052435381796128	12.7954266763404	1.67193271442362e-32	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.44829471636287	0.187046942269814	23.7817024025243	1.94727332362834e-83	***
df.mm.trans1	-0.0132381325984654	0.165345769213013	-0.080063328269445	0.936219913845166	   
df.mm.trans2	-0.088287320945858	0.155616713488108	-0.567338295269966	0.570746863098323	   
df.mm.exp2	-0.0882865068705452	0.214205535164396	-0.412157915540269	0.680405787192856	   
df.mm.exp3	0.00117874151436456	0.214205535164396	0.00550285273188631	0.995611643590103	   
df.mm.exp4	-0.198219109169634	0.214205535164396	-0.925368753975044	0.355234326052888	   
df.mm.exp5	0.0649525063578851	0.214205535164396	0.303225153859989	0.761848303300678	   
df.mm.exp6	-0.329703436952097	0.214205535164396	-1.53919195738364	0.124409582621950	   
df.mm.exp7	-0.0938995482442274	0.214205535164396	-0.438361913347209	0.661319136429694	   
df.mm.exp8	0.0916264993775718	0.214205535164396	0.427750381460738	0.669022728361601	   
df.mm.trans1:exp2	0.144366759627571	0.199414500782641	0.723953168204799	0.469443532049105	   
df.mm.trans2:exp2	0.161875661774458	0.180633967609275	0.896152943529467	0.370615656310991	   
df.mm.trans1:exp3	-0.0824367043217508	0.199414500782641	-0.413393730136033	0.679500885643539	   
df.mm.trans2:exp3	0.100697686868843	0.180633967609275	0.557468167264418	0.577464793359042	   
df.mm.trans1:exp4	0.190013033676518	0.199414500782641	0.95285464663189	0.341138353318394	   
df.mm.trans2:exp4	0.210720423282834	0.180633967609275	1.16656034339365	0.243961248041691	   
df.mm.trans1:exp5	-0.108634746946604	0.199414500782641	-0.544768542509426	0.586163111945808	   
df.mm.trans2:exp5	-0.202565558573999	0.180633967609275	-1.12141454486658	0.262666367194863	   
df.mm.trans1:exp6	0.235054402404739	0.199414500782641	1.17872271816855	0.239086561425762	   
df.mm.trans2:exp6	0.262077560765066	0.180633967609275	1.45087640067764	0.147460727299355	   
df.mm.trans1:exp7	-0.0119995346639114	0.199414500782641	-0.060173831977198	0.952041973593092	   
df.mm.trans2:exp7	-0.0282055944196215	0.180633967609275	-0.156147787666561	0.875981503381265	   
df.mm.trans1:exp8	-0.200104687694694	0.199414500782641	-1.00346106681984	0.316138826455458	   
df.mm.trans2:exp8	0.0431629581560941	0.180633967609275	0.238952610781704	0.811243266288642	   
df.mm.trans1:probe2	0.0464994047646869	0.0997072503913204	0.466359312709868	0.641167723018209	   
df.mm.trans1:probe3	-0.0154775556217505	0.0997072503913204	-0.155229991409911	0.876704586639734	   
df.mm.trans1:probe4	-0.148392564267913	0.0997072503913204	-1.48828258412019	0.137326277471553	   
df.mm.trans1:probe5	0.0259137470071733	0.0997072503913204	0.259898321390568	0.795052497915466	   
df.mm.trans1:probe6	0.0195797751943612	0.0997072503913204	0.196372632055508	0.844400770751437	   
df.mm.trans1:probe7	-0.144231202334590	0.0997072503913204	-1.44654678339365	0.148669850588632	   
df.mm.trans1:probe8	-0.149922416652027	0.0997072503913204	-1.50362602582688	0.133328551796787	   
df.mm.trans1:probe9	-0.0936721229899936	0.0997072503913204	-0.939471529125106	0.347956343264746	   
df.mm.trans1:probe10	-0.0383863851299319	0.0997072503913204	-0.384990910683798	0.700412922153938	   
df.mm.trans1:probe11	-0.0248821974931427	0.0997072503913204	-0.249552539012837	0.803039062510486	   
df.mm.trans1:probe12	0.000729986765509137	0.0997072503913204	0.00732130073434141	0.994161509776159	   
df.mm.trans1:probe13	-0.0353729938618421	0.0997072503913204	-0.354768522078524	0.722917222582819	   
df.mm.trans2:probe2	-0.123716079040981	0.0997072503913204	-1.24079320766979	0.215282003525049	   
df.mm.trans2:probe3	-0.0301568216013825	0.0997072503913204	-0.302453647884444	0.762435929789403	   
df.mm.trans2:probe4	-0.110179700996688	0.0997072503913204	-1.10503198678398	0.269693610210623	   
df.mm.trans2:probe5	-0.0449367577072496	0.0997072503913204	-0.45068696138833	0.652416591493843	   
df.mm.trans2:probe6	-0.0754175012597919	0.0997072503913204	-0.756389339429192	0.449783042071963	   
df.mm.trans3:probe2	-0.0569971198095274	0.0997072503913204	-0.571644685675627	0.567827538175333	   
df.mm.trans3:probe3	0.0080290676517161	0.0997072503913204	0.0805264172886573	0.935851803693906