chr14.7550_chr14_69522911_69528691_-_2.R 

fitVsDatCorrelation=0.918463769754795
cont.fitVsDatCorrelation=0.271836872265424

fstatistic=11052.7936789091,52,692
cont.fstatistic=1855.81917129829,52,692

residuals=-0.664862471206018,-0.0884112234801298,0.00187282804722867,0.0825203058518103,0.709735519810664
cont.residuals=-0.77449764373662,-0.231468407767197,-0.071201308373752,0.120165511384892,1.59789445727587

predictedValues:
Include	Exclude	Both
chr14.7550_chr14_69522911_69528691_-_2.R.tl.Lung	69.3053751364669	59.1285513852895	108.778346397037
chr14.7550_chr14_69522911_69528691_-_2.R.tl.cerebhem	72.400445834717	60.0641507727716	94.8785700977369
chr14.7550_chr14_69522911_69528691_-_2.R.tl.cortex	79.9420036309205	54.702440764124	96.900376904544
chr14.7550_chr14_69522911_69528691_-_2.R.tl.heart	59.8065901304792	54.8176431350617	82.5629280923981
chr14.7550_chr14_69522911_69528691_-_2.R.tl.kidney	62.6189927862816	58.9725131908713	100.569563772623
chr14.7550_chr14_69522911_69528691_-_2.R.tl.liver	61.6590616112567	59.642140869856	86.213452663168
chr14.7550_chr14_69522911_69528691_-_2.R.tl.stomach	59.8441169396528	55.3784972401341	81.5072823477081
chr14.7550_chr14_69522911_69528691_-_2.R.tl.testicle	59.7983138591514	59.3336608374605	92.8454451289779


diffExp=10.1768237511773,12.3362950619453,25.2395628667965,4.98894699541749,3.64647959541024,2.01692074140069,4.46561969951875,0.464653021690872
diffExpScore=0.984456434134022
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,1,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,1,1,0,0,0,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	65.8424120660151	62.0892778755569	68.6957518096683
cerebhem	70.1065151344871	61.275090579703	71.9288893169532
cortex	66.1317433923963	61.1708546155469	100.775581496322
heart	73.7637889494378	70.4746972496999	65.0031047305733
kidney	65.4923371263395	69.8390656304307	68.0688296072411
liver	70.0509545769872	68.9357443941955	56.1039903192999
stomach	64.7603203736876	71.4294555006656	64.9542088485317
testicle	71.2525604954958	54.8884466721247	69.462654014618
cont.diffExp=3.75313419045817,8.83142455478418,4.96088877684949,3.28909169973784,-4.34672850409122,1.11521018279177,-6.66913512697802,16.3641138233711
cont.diffExpScore=1.74322310982099

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

tran.correlation=-0.102292849825597
cont.tran.correlation=-0.150272053396223

tran.covariance=-0.000339674566067792
cont.tran.covariance=-0.000765329474163874

tran.mean=61.7134061327809
cont.tran.mean=66.7189540395481

weightedLogRatios:
wLogRatio
Lung	0.660503552781316
cerebhem	0.782467245799903
cortex	1.59026591572096
heart	0.352558043617932
kidney	0.246412596081104
liver	0.136523052493401
stomach	0.314314697232357
testicle	0.0318819925514676

cont.weightedLogRatios:
wLogRatio
Lung	0.244031893708483
cerebhem	0.563167711650356
cortex	0.323816193743786
heart	0.195140346097285
kidney	-0.270797342549609
liver	0.0680630550431584
stomach	-0.413603558292758
testicle	1.07913683541733

varWeightedLogRatios=0.252050366652002
cont.varWeightedLogRatios=0.219024150354264

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	2.28173324322149	0.0812428351793184	28.08534731937	2.01487344077149e-116	***
df.mm.trans1	1.69059330627718	0.0729679468636671	23.1689855469810	2.38090626665290e-88	***
df.mm.trans2	1.71719056381797	0.0671039370970799	25.5900121230398	3.71584750123462e-102	***
df.mm.exp2	0.196103678739367	0.0919157754849872	2.13351492390332	0.0332335889119392	*  
df.mm.exp3	0.180602253311720	0.0919157754849873	1.96486677459646	0.049829338157525	*  
df.mm.exp4	0.0526431028748183	0.0919157754849873	0.572731966814734	0.567012225790177	   
df.mm.exp5	-0.0256336611134274	0.0919157754849873	-0.278882063260339	0.780418654377127	   
df.mm.exp6	0.124232275829261	0.0919157754849873	1.35158818139495	0.176948735035181	   
df.mm.exp7	0.0763180574815341	0.0919157754849873	0.830304233183555	0.406653151399238	   
df.mm.exp8	0.0142939305224559	0.0919157754849873	0.155511178000022	0.876463692876135	   
df.mm.trans1:exp2	-0.152413687913337	0.0880026550797723	-1.73192147185988	0.0837331689912032	.  
df.mm.trans2:exp2	-0.180404418857808	0.0765964795708227	-2.35525731559244	0.0187880853323285	*  
df.mm.trans1:exp3	-0.0378233026427594	0.0880026550797723	-0.429797289734878	0.667476903061518	   
df.mm.trans2:exp3	-0.25840783468429	0.0765964795708228	-3.37362547380994	0.000783201734240315	***
df.mm.trans1:exp4	-0.200049711624060	0.0880026550797723	-2.27322359129642	0.0233183749838552	*  
df.mm.trans2:exp4	-0.128344916439239	0.0765964795708228	-1.67559811049238	0.0942686798006233	.  
df.mm.trans1:exp5	-0.0758201741396144	0.0880026550797723	-0.861566893304357	0.389224335854093	   
df.mm.trans2:exp5	0.0229912076220263	0.0765964795708227	0.300160108543477	0.764145177023335	   
df.mm.trans1:exp6	-0.241134538731852	0.0880026550797723	-2.74008254084231	0.00630070705865115	** 
df.mm.trans2:exp6	-0.115583800754828	0.0765964795708228	-1.50899625416801	0.131756161914048	   
df.mm.trans1:exp7	-0.223097393541410	0.0880026550797723	-2.53512116582366	0.0114599529345130	*  
df.mm.trans2:exp7	-0.141840586253789	0.0765964795708227	-1.85178988706185	0.0644817623429963	.  
df.mm.trans1:exp8	-0.161838932783417	0.0880026550797723	-1.83902329579390	0.0663400476500031	.  
df.mm.trans2:exp8	-0.0108310599026007	0.0765964795708227	-0.141404147596445	0.887591831942206	   
df.mm.trans1:probe2	0.147179918276324	0.0440013275398861	3.34489722254195	0.000867548178745454	***
df.mm.trans1:probe3	0.128440533134894	0.0440013275398862	2.91901495513893	0.00362541851343947	** 
df.mm.trans1:probe4	0.331182024686676	0.0440013275398861	7.52663710853877	1.62597679071976e-13	***
df.mm.trans1:probe5	0.0849973978120783	0.0440013275398862	1.93170075914255	0.0538044260459382	.  
df.mm.trans1:probe6	0.87118680164737	0.0440013275398862	19.7991026715651	1.80909029608903e-69	***
df.mm.trans1:probe7	0.297105596170773	0.0440013275398862	6.75219619002298	3.08629415431128e-11	***
df.mm.trans1:probe8	0.0123570793864658	0.0440013275398862	0.280834240177513	0.77892148284393	   
df.mm.trans1:probe9	0.97604500439408	0.0440013275398862	22.1821717426439	9.16998784009992e-83	***
df.mm.trans1:probe10	0.133575019397042	0.0440013275398862	3.03570430405673	0.00248980172023942	** 
df.mm.trans1:probe11	0.639302857414238	0.0440013275398862	14.5291720308831	6.13707847755018e-42	***
df.mm.trans1:probe12	0.0842069204105055	0.0440013275398862	1.91373590567634	0.0560661643196951	.  
df.mm.trans1:probe13	0.332075637178342	0.0440013275398861	7.54694587060637	1.40811796948327e-13	***
df.mm.trans1:probe14	0.198953162523281	0.0440013275398862	4.5215263640156	7.22203989858123e-06	***
df.mm.trans1:probe15	0.0741220924112994	0.0440013275398862	1.68454218441726	0.092527849842352	.  
df.mm.trans1:probe16	0.361226800548223	0.0440013275398861	8.20945232210958	1.08716970152404e-15	***
df.mm.trans1:probe17	0.155188783908486	0.0440013275398862	3.52691140438457	0.000448194463198558	***
df.mm.trans1:probe18	0.398363320582151	0.0440013275398862	9.05343867684548	1.39099241889892e-18	***
df.mm.trans1:probe19	0.432477047458078	0.0440013275398862	9.8287272597866	1.98068553632316e-21	***
df.mm.trans1:probe20	0.263156112308173	0.0440013275398861	5.98064029021915	3.56246113635509e-09	***
df.mm.trans1:probe21	0.258880941810440	0.0440013275398861	5.88348025581208	6.25690857011439e-09	***
df.mm.trans1:probe22	0.474874873193255	0.0440013275398861	10.7922851364608	3.33555830790696e-25	***
df.mm.trans2:probe2	0.126613707897754	0.0440013275398862	2.87749745238893	0.00413193044303995	** 
df.mm.trans2:probe3	0.0577769151935588	0.0440013275398862	1.31307209177235	0.189593903016023	   
df.mm.trans2:probe4	0.183758072447461	0.0440013275398862	4.17619382689963	3.34313517852164e-05	***
df.mm.trans2:probe5	0.0272913211322501	0.0440013275398862	0.620238585017945	0.535304915411581	   
df.mm.trans2:probe6	0.331670916466109	0.0440013275398862	7.53774795011486	1.50297367607638e-13	***
df.mm.trans3:probe2	-1.52190821361476	0.0440013275398862	-34.5877794763167	5.43845353084517e-153	***
df.mm.trans3:probe3	-1.47870624875039	0.0440013275398862	-33.6059462617344	1.46192138540882e-147	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.07284558193268	0.197680123306149	20.6032124718226	6.44652241268447e-74	***
df.mm.trans1	0.0795634606581858	0.177545659276526	0.448129574005897	0.65419995239254	   
df.mm.trans2	0.0230409043210311	0.163277346616476	0.141115132003903	0.887820057994567	   
df.mm.exp2	0.0035610098630409	0.223649529112913	0.0159222774899878	0.987300986783166	   
df.mm.exp3	-0.393726515974556	0.223649529112913	-1.76046208340450	0.0787711998905324	.  
df.mm.exp4	0.295536508341820	0.223649529112913	1.32142691967222	0.186795777645423	   
df.mm.exp5	0.121457139227472	0.223649529112913	0.543069058581171	0.587257131324474	   
df.mm.exp6	0.369040645640712	0.223649529112913	1.65008460829084	0.099379414317543	.  
df.mm.exp7	0.179570714304794	0.223649529112913	0.802911211201944	0.422301731776773	   
df.mm.exp8	-0.0554057628211305	0.223649529112913	-0.247734761798483	0.80441312257979	   
df.mm.trans1:exp2	0.059190529471056	0.214128121809643	0.276425763093721	0.782303609407884	   
df.mm.trans2:exp2	-0.0167609172244355	0.186374607594094	-0.0899313347499524	0.928367802945797	   
df.mm.trans1:exp3	0.398111189457295	0.214128121809644	1.85921954618931	0.0634202752990167	.  
df.mm.trans2:exp3	0.378824045262955	0.186374607594094	2.03259473032934	0.0424747957942993	*  
df.mm.trans1:exp4	-0.181932752757747	0.214128121809643	-0.849644368148347	0.395816683927161	   
df.mm.trans2:exp4	-0.168856082228126	0.186374607594094	-0.90600369013722	0.365249244769069	   
df.mm.trans1:exp5	-0.126788184833048	0.214128121809644	-0.592113654953557	0.553967888610024	   
df.mm.trans2:exp5	-0.00383692152565333	0.186374607594094	-0.020587147440223	0.983580927642967	   
df.mm.trans1:exp6	-0.307081936835372	0.214128121809644	-1.43410372369662	0.151994376072671	   
df.mm.trans2:exp6	-0.264439130604660	0.186374607594094	-1.41885814821181	0.156390607401556	   
df.mm.trans1:exp7	-0.196141829380750	0.214128121809643	-0.9160021940281	0.359984838829022	   
df.mm.trans2:exp7	-0.0394337030285951	0.186374607594094	-0.211583023769406	0.832494652271417	   
df.mm.trans1:exp8	0.134372327137765	0.214128121809644	0.627532367080771	0.530517334534883	   
df.mm.trans2:exp8	-0.0678646689637517	0.186374607594094	-0.364130445878949	0.71587183341152	   
df.mm.trans1:probe2	-0.0261829639882693	0.107064060904822	-0.244554183420574	0.806874138006757	   
df.mm.trans1:probe3	0.0801282158889849	0.107064060904822	0.748413755389099	0.454464912758015	   
df.mm.trans1:probe4	0.054978423873866	0.107064060904822	0.513509607325103	0.607758802093715	   
df.mm.trans1:probe5	0.0798540462389106	0.107064060904822	0.745852955361927	0.456009523905002	   
df.mm.trans1:probe6	0.0301941337269819	0.107064060904822	0.282019320692721	0.778013016496594	   
df.mm.trans1:probe7	0.0824455929989414	0.107064060904822	0.770058526663156	0.441527970686901	   
df.mm.trans1:probe8	0.0741565081513215	0.107064060904822	0.692636796368535	0.488769878537778	   
df.mm.trans1:probe9	-0.104339604172321	0.107064060904822	-0.974553022653203	0.330122566140121	   
df.mm.trans1:probe10	0.0834382972104779	0.107064060904822	0.779330584935062	0.436051438356834	   
df.mm.trans1:probe11	0.173795113692217	0.107064060904822	1.62328154026138	0.10498465537916	   
df.mm.trans1:probe12	0.00346691586964045	0.107064060904822	0.0323816959709989	0.97417699665457	   
df.mm.trans1:probe13	0.06638472569952	0.107064060904822	0.620046775159546	0.535431111768156	   
df.mm.trans1:probe14	0.0137088433765117	0.107064060904822	0.128043371983607	0.898151850581193	   
df.mm.trans1:probe15	-0.0237354651639979	0.107064060904822	-0.221694048996501	0.824617468071632	   
df.mm.trans1:probe16	0.055901995609037	0.107064060904822	0.52213595427445	0.601742767884407	   
df.mm.trans1:probe17	0.141934417808956	0.107064060904822	1.32569619169530	0.185377807548919	   
df.mm.trans1:probe18	0.069128908405939	0.107064060904822	0.645677997095528	0.518701949624162	   
df.mm.trans1:probe19	0.0586511145631246	0.107064060904822	0.547813281762818	0.58399676864657	   
df.mm.trans1:probe20	-0.054886538653613	0.107064060904822	-0.512651380769185	0.608358799017485	   
df.mm.trans1:probe21	0.068648674039411	0.107064060904822	0.641192510906517	0.521609910669606	   
df.mm.trans1:probe22	-0.0562926458146693	0.107064060904822	-0.525784706267704	0.599206245895385	   
df.mm.trans2:probe2	0.107903403207912	0.107064060904822	1.00783962700458	0.313883729811533	   
df.mm.trans2:probe3	0.121477678291686	0.107064060904822	1.13462610389566	0.256924879123798	   
df.mm.trans2:probe4	0.0130442014237692	0.107064060904822	0.121835481612875	0.903064683750074	   
df.mm.trans2:probe5	-0.0711063941510678	0.107064060904822	-0.664148114223691	0.506816743100252	   
df.mm.trans2:probe6	0.122862570154983	0.107064060904822	1.14756127421886	0.251546301817934	   
df.mm.trans3:probe2	-0.0068673361405748	0.107064060904822	-0.0641423095905147	0.948875436780732	   
df.mm.trans3:probe3	0.169579576859047	0.107064060904822	1.58390757296046	0.113671626728348