chr7.22035_chr7_89825084_89826860_+_2.R 

fitVsDatCorrelation=0.915423248592151
cont.fitVsDatCorrelation=0.287465724865801

fstatistic=12241.0739773093,53,715
cont.fstatistic=2150.58390444845,53,715

residuals=-0.362675993231755,-0.0830165305754092,-0.0067618401163613,0.074390260234503,1.06222673779867
cont.residuals=-0.714670468533434,-0.241358719419699,-0.0719818178132157,0.216963782266378,1.39752903720149

predictedValues:
Include	Exclude	Both
chr7.22035_chr7_89825084_89826860_+_2.R.tl.Lung	60.1020877033256	88.605651045276	52.8853964225788
chr7.22035_chr7_89825084_89826860_+_2.R.tl.cerebhem	57.3113411821144	69.2771689404257	50.9572936753983
chr7.22035_chr7_89825084_89826860_+_2.R.tl.cortex	54.5510990403401	73.7586051525666	46.9115579989801
chr7.22035_chr7_89825084_89826860_+_2.R.tl.heart	58.3862283737868	80.328976063979	53.6916678870323
chr7.22035_chr7_89825084_89826860_+_2.R.tl.kidney	59.3924661944496	93.8287714658013	53.5331225773054
chr7.22035_chr7_89825084_89826860_+_2.R.tl.liver	62.2102080295117	97.405130916153	52.0262302689069
chr7.22035_chr7_89825084_89826860_+_2.R.tl.stomach	60.4800521313895	77.1256724756023	51.2896278130777
chr7.22035_chr7_89825084_89826860_+_2.R.tl.testicle	56.5627706245725	77.6316501527878	54.5889194156991


diffExp=-28.5035633419504,-11.9658277583113,-19.2075061122265,-21.9427476901922,-34.4363052713518,-35.1949228866412,-16.6456203442128,-21.0688795282153
diffExpScore=0.99473588273189
diffExp1.5=0,0,0,0,-1,-1,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=-1,0,0,0,-1,-1,0,0
diffExp1.4Score=0.75
diffExp1.3=-1,0,-1,-1,-1,-1,0,-1
diffExp1.3Score=0.857142857142857
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	61.4504224329359	66.3984601391999	60.4380535323187
cerebhem	63.1794790934593	65.3089577966306	60.6795457746233
cortex	57.3406717306445	54.574375877269	75.3146017298509
heart	59.1846035625086	60.6520320127726	52.7862349326471
kidney	61.6000756875721	70.2530443702244	66.1632909287234
liver	58.7050728429945	64.0865038030437	67.5424030449394
stomach	60.6128646144888	57.0682505331389	67.8540887589659
testicle	64.9863227941442	59.5870866322961	61.2646844260657
cont.diffExp=-4.94803770626398,-2.12947870317129,2.76629585337550,-1.46742845026401,-8.65296868265227,-5.38143096004911,3.54461408134991,5.39923616184811
cont.diffExpScore=2.88894746102988

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=0.73220515896519
cont.tran.correlation=0.348193806697244

tran.covariance=0.00363771588405523
cont.tran.covariance=0.00126738747939332

tran.mean=70.4348674682551
cont.tran.mean=61.5617639952077

weightedLogRatios:
wLogRatio
Lung	-1.66521466312902
cerebhem	-0.785640893463298
cortex	-1.25187848294105
heart	-1.34849990583181
kidney	-1.97227025815889
liver	-1.95247190771549
stomach	-1.02691947950789
testicle	-1.32781522973123

cont.weightedLogRatios:
wLogRatio
Lung	-0.321927500918664
cerebhem	-0.137987243460176
cortex	0.198983739560567
heart	-0.100242280467942
kidney	-0.550260508867182
liver	-0.361038012456714
stomach	0.245518847760543
testicle	0.358297788157484

varWeightedLogRatios=0.178192954433154
cont.varWeightedLogRatios=0.105460750729773

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.76864172801102	0.0723364192682211	65.9231100495734	4.59127680982816e-306	***
df.mm.trans1	-0.793462663074208	0.0642361402575892	-12.3522780150301	6.57992617619332e-32	***
df.mm.trans2	-0.126634551377647	0.0584311228604598	-2.16724487188214	0.0305456221544935	*  
df.mm.exp2	-0.256486947628853	0.0787738366500394	-3.25599156441144	0.001183257479589	** 
df.mm.exp3	-0.160441530920005	0.0787738366500395	-2.03673627873150	0.0420443716821185	*  
df.mm.exp4	-0.142160353630210	0.0787738366500395	-1.80466459011984	0.0715478199684614	.  
df.mm.exp5	0.0332253771446328	0.0787738366500394	0.421781882888856	0.673311011046323	   
df.mm.exp6	0.145536996396288	0.0787738366500395	1.84752961878511	0.0650833081702201	.  
df.mm.exp7	-0.101851724077175	0.0787738366500394	-1.29296386222321	0.196441176661884	   
df.mm.exp8	-0.224617682786657	0.0787738366500394	-2.85142494435739	0.0044778762076366	** 
df.mm.trans1:exp2	0.208940900056135	0.0747994535935147	2.79334794598354	0.00535609593500563	** 
df.mm.trans2:exp2	0.0104067098977278	0.0629867766869503	0.16522055017119	0.868817092183134	   
df.mm.trans1:exp3	0.0635348122920809	0.0747994535935148	0.849402091054707	0.395941897210576	   
df.mm.trans2:exp3	-0.0229564377583213	0.0629867766869504	-0.364464399764680	0.715619015389811	   
df.mm.trans1:exp4	0.113195822040193	0.0747994535935148	1.51332418356071	0.130639213749983	   
df.mm.trans2:exp4	0.0440951199877704	0.0629867766869503	0.700069479772349	0.484111629654528	   
df.mm.trans1:exp5	-0.0451025686611319	0.0747994535935147	-0.602979921567801	0.546713253324314	   
df.mm.trans2:exp5	0.0240505267532109	0.0629867766869503	0.381834537632304	0.702697550921905	   
df.mm.trans1:exp6	-0.111062471984658	0.0747994535935148	-1.4848032525506	0.138036672255606	   
df.mm.trans2:exp6	-0.0508537454511424	0.0629867766869504	-0.807371771124117	0.419720824005091	   
df.mm.trans1:exp7	0.108120739810886	0.0747994535935148	1.44547499502403	0.148762653750582	   
df.mm.trans2:exp7	-0.0369077115670735	0.0629867766869504	-0.585959680878861	0.558087524361587	   
df.mm.trans1:exp8	0.163924110660187	0.0747994535935147	2.19151481441302	0.028736424618522	*  
df.mm.trans2:exp8	0.0923972524895983	0.0629867766869503	1.46693095518795	0.142834529306047	   
df.mm.trans1:probe2	-0.18505917458449	0.0409693480222289	-4.51701536680744	7.33545899977183e-06	***
df.mm.trans1:probe3	0.424950926821080	0.0409693480222289	10.3724112619638	1.41035171375337e-23	***
df.mm.trans1:probe4	-0.0828122372663188	0.0409693480222289	-2.02132182385199	0.0436185743006882	*  
df.mm.trans1:probe5	-0.142444831586208	0.0409693480222289	-3.47686352023276	0.00053798896579522	***
df.mm.trans1:probe6	-0.0449702126818432	0.0409693480222289	-1.09765507270078	0.272724647308354	   
df.mm.trans1:probe7	0.118416588460063	0.0409693480222289	2.89037034213513	0.00396448501896356	** 
df.mm.trans1:probe8	0.671143288993835	0.0409693480222289	16.3815955438122	1.88468221797655e-51	***
df.mm.trans1:probe9	0.225275018945431	0.0409693480222289	5.4986234787823	5.33125884073172e-08	***
df.mm.trans1:probe10	0.00333866366400093	0.0409693480222289	0.081491745052654	0.93507369525767	   
df.mm.trans1:probe11	-0.0444934626443142	0.0409693480222289	-1.08601832326385	0.277836888777045	   
df.mm.trans1:probe12	-0.129136604072108	0.0409693480222289	-3.15202975653999	0.00168910473759992	** 
df.mm.trans1:probe13	-0.168595649625696	0.0409693480222289	-4.11516555094362	4.31970240462504e-05	***
df.mm.trans1:probe14	-0.190473763979419	0.0409693480222289	-4.64917732828145	3.96907427988615e-06	***
df.mm.trans1:probe15	-0.129453237193336	0.0409693480222289	-3.15975829351979	0.00164554339353843	** 
df.mm.trans1:probe16	-0.119447981342596	0.0409693480222289	-2.91554508697055	0.00366175379396579	** 
df.mm.trans1:probe17	0.518755836758809	0.0409693480222289	12.6620476478500	2.68531248971769e-33	***
df.mm.trans1:probe18	0.627425976206692	0.0409693480222289	15.3145218680626	5.37977222346055e-46	***
df.mm.trans1:probe19	0.0796312617368217	0.0409693480222289	1.94367900835561	0.0523261723756503	.  
df.mm.trans1:probe20	0.915768612850853	0.0409693480222289	22.3525307835990	2.46392618693851e-84	***
df.mm.trans1:probe21	0.298597305488897	0.0409693480222289	7.28830991713331	8.32808452472174e-13	***
df.mm.trans1:probe22	0.496087017240715	0.0409693480222289	12.1087359498997	7.85313813057493e-31	***
df.mm.trans2:probe2	-0.0304043055984202	0.0409693480222289	-0.742123247407395	0.458256378113113	   
df.mm.trans2:probe3	-0.612081074750876	0.0409693480222289	-14.9399759649282	4.00711503978966e-44	***
df.mm.trans2:probe4	-0.0572801334817655	0.0409693480222289	-1.39812167503097	0.162510067739346	   
df.mm.trans2:probe5	-0.539538965266897	0.0409693480222289	-13.1693324720266	1.28322042564799e-35	***
df.mm.trans2:probe6	-0.338810915971094	0.0409693480222289	-8.26986350349691	6.53353039618743e-16	***
df.mm.trans3:probe2	0.236215376021993	0.0409693480222289	5.76566109604256	1.21010710727244e-08	***
df.mm.trans3:probe3	0.133605551094712	0.0409693480222289	3.26111001381377	0.00116241352103018	** 
df.mm.trans3:probe4	0.108509981398579	0.0409693480222289	2.64856500376096	0.00826177867719113	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.17787618140807	0.172135263159699	24.270890837353	2.18813590965217e-95	***
df.mm.trans1	0.0112731456272517	0.152859445068787	0.0737484400926531	0.941231180562622	   
df.mm.trans2	-0.0171821552458044	0.139045543200127	-0.123572139389425	0.901688781217729	   
df.mm.exp2	0.0072164436516034	0.187454054804324	0.0384971328528283	0.969302063462193	   
df.mm.exp3	-0.485385032527087	0.187454054804324	-2.58935467164881	0.00981121988575345	** 
df.mm.exp4	0.00727847314911005	0.187454054804324	0.0388280379248546	0.96903832917919	   
df.mm.exp5	-0.0316446927260314	0.187454054804324	-0.168813060667395	0.865991428713668	   
df.mm.exp6	-0.192281302346655	0.187454054804324	-1.02575163043216	0.305355566971654	   
df.mm.exp7	-0.280890202983432	0.187454054804324	-1.49844826390468	0.134458176188401	   
df.mm.exp8	-0.0658734978837318	0.187454054804324	-0.351411432270669	0.72538323537479	   
df.mm.trans1:exp2	0.0205323964815346	0.177996419490698	0.115352862379389	0.908197827309511	   
df.mm.trans2:exp2	-0.0237611031947444	0.149886398722429	-0.158527414076757	0.874085983891162	   
df.mm.trans1:exp3	0.416164497378071	0.177996419490698	2.33804982464728	0.0196594791106520	*  
df.mm.trans2:exp3	0.289275633303384	0.149886398722429	1.92996586594282	0.0540063193894485	.  
df.mm.trans1:exp4	-0.0448477504477292	0.177996419490698	-0.251958722406058	0.801145374500093	   
df.mm.trans2:exp4	-0.0977991999386683	0.149886398722429	-0.652488823350679	0.514295595766423	   
df.mm.trans1:exp5	0.0340770815535049	0.177996419490698	0.191448129411871	0.848228868242468	   
df.mm.trans2:exp5	0.0880744706930716	0.149886398722429	0.587608158203699	0.556980856046229	   
df.mm.trans1:exp6	0.146576734853645	0.177996419490698	0.823481367058084	0.410508888377628	   
df.mm.trans2:exp6	0.156841229471445	0.149886398722429	1.04640067950325	0.295729688763424	   
df.mm.trans1:exp7	0.26716665049113	0.177996419490698	1.50096643098538	0.133805696826455	   
df.mm.trans2:exp7	0.129464266768521	0.149886398722429	0.863749265257036	0.388015298218481	   
df.mm.trans1:exp8	0.121819616681053	0.177996419490698	0.684393635723775	0.493948401702517	   
df.mm.trans2:exp8	-0.0423614843028367	0.149886398722429	-0.282623938288657	0.777546923908643	   
df.mm.trans1:probe2	-0.0785039947586995	0.0974926541102078	-0.805229845009214	0.420954745347225	   
df.mm.trans1:probe3	-0.113194784040958	0.0974926541102078	-1.16105962109720	0.246005132375476	   
df.mm.trans1:probe4	-0.0930742993606246	0.0974926541102077	-0.954680126519188	0.340062130665842	   
df.mm.trans1:probe5	-0.195310521755245	0.0974926541102078	-2.00333577475962	0.0455181887091462	*  
df.mm.trans1:probe6	0.0513126874989575	0.0974926541102078	0.526323628864925	0.598826588454967	   
df.mm.trans1:probe7	-0.141697745723481	0.0974926541102078	-1.45341971676454	0.146546010267065	   
df.mm.trans1:probe8	0.0105772709733885	0.0974926541102077	0.108493004626089	0.91363506789953	   
df.mm.trans1:probe9	-0.138367872476211	0.0974926541102078	-1.41926459730798	0.156257682959386	   
df.mm.trans1:probe10	-0.180989684459347	0.0974926541102078	-1.85644432507451	0.0638014011554997	.  
df.mm.trans1:probe11	0.0172120692163040	0.0974926541102077	0.1765473447553	0.859913951159646	   
df.mm.trans1:probe12	-0.153314310583136	0.0974926541102077	-1.57257294903292	0.116260112153805	   
df.mm.trans1:probe13	-0.0715442885127959	0.0974926541102077	-0.733842864016408	0.463285072703392	   
df.mm.trans1:probe14	0.0103369132019993	0.0974926541102077	0.106027610965584	0.915590184542428	   
df.mm.trans1:probe15	-0.165960051546838	0.0974926541102078	-1.70228262899924	0.0891370677522881	.  
df.mm.trans1:probe16	-0.150784129652285	0.0974926541102077	-1.54662042005581	0.122397279046977	   
df.mm.trans1:probe17	-0.0484238798266215	0.0974926541102077	-0.496692599750973	0.619558514020657	   
df.mm.trans1:probe18	-0.100569758956353	0.0974926541102077	-1.03156242769498	0.302625951032341	   
df.mm.trans1:probe19	-0.0269988522055068	0.0974926541102077	-0.276932169422598	0.781912230177586	   
df.mm.trans1:probe20	-0.124791780587102	0.0974926541102077	-1.28001213759177	0.200956004727628	   
df.mm.trans1:probe21	-0.0493783735757087	0.0974926541102077	-0.506483016862895	0.612673748147966	   
df.mm.trans1:probe22	-0.100418645242629	0.0974926541102077	-1.03001242667077	0.303352466949194	   
df.mm.trans2:probe2	0.09603636561819	0.0974926541102078	0.985062582352395	0.324926544528859	   
df.mm.trans2:probe3	0.161100614402912	0.0974926541102078	1.65243849265608	0.0988842171966167	.  
df.mm.trans2:probe4	-0.0637160218027643	0.0974926541102077	-0.653546899346266	0.513613878035881	   
df.mm.trans2:probe5	0.149790283806657	0.0974926541102077	1.53642636128595	0.124876226095944	   
df.mm.trans2:probe6	0.00658715174011659	0.0974926541102078	0.0675656212279372	0.94615031217865	   
df.mm.trans3:probe2	0.0192200817393443	0.0974926541102077	0.197143896786496	0.843770959976246	   
df.mm.trans3:probe3	-0.180036853257083	0.0974926541102077	-1.84667096100970	0.0652078967193756	.  
df.mm.trans3:probe4	-0.120576187929855	0.0974926541102078	-1.23677203200923	0.216577800752495