chr9.24631_chr9_120310790_120311327_+_1.R 

fitVsDatCorrelation=0.871363784105992
cont.fitVsDatCorrelation=0.28451663071062

fstatistic=9442.05418999495,46,554
cont.fstatistic=2464.25098159387,46,554

residuals=-0.552869607771412,-0.0845153583657724,-0.00192274956639172,0.0854022487034706,0.854060479906176
cont.residuals=-0.652882598108155,-0.214526131821782,-0.0299079827875588,0.172516298629843,1.1022350643454

predictedValues:
Include	Exclude	Both
chr9.24631_chr9_120310790_120311327_+_1.R.tl.Lung	52.8379088678879	64.3902478313391	67.6681249261944
chr9.24631_chr9_120310790_120311327_+_1.R.tl.cerebhem	47.9392743112183	56.3590873431787	67.0037709848862
chr9.24631_chr9_120310790_120311327_+_1.R.tl.cortex	56.1733830483102	67.8217878268871	60.2989789297338
chr9.24631_chr9_120310790_120311327_+_1.R.tl.heart	51.9815224319727	63.8283628321413	59.8517186339694
chr9.24631_chr9_120310790_120311327_+_1.R.tl.kidney	59.7458108729158	68.1036203466946	83.9149228083397
chr9.24631_chr9_120310790_120311327_+_1.R.tl.liver	50.911536188161	69.6762017653887	64.9909204897512
chr9.24631_chr9_120310790_120311327_+_1.R.tl.stomach	78.1438419547256	78.59765227739	104.64058822452
chr9.24631_chr9_120310790_120311327_+_1.R.tl.testicle	51.1213298695363	68.5050419584612	64.3825810263453


diffExp=-11.5523389634512,-8.41981303196046,-11.6484047785770,-11.8468404001686,-8.35780947377874,-18.7646655772278,-0.453810322664395,-17.3837120889249
diffExpScore=0.988817744226342
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,-1,0,-1
diffExp1.3Score=0.666666666666667
diffExp1.2=-1,0,-1,-1,0,-1,0,-1
diffExp1.2Score=0.833333333333333

cont.predictedValues:
Include	Exclude	Both
Lung	54.3078884076984	66.5098752700877	65.5344861021067
cerebhem	60.2239676390297	70.9541983073868	68.9624511021758
cortex	57.9195470984694	64.332430105743	62.0215690468245
heart	63.9160480955077	70.5287042275132	62.7164897416829
kidney	60.784575824128	75.8252839420425	65.8967808225408
liver	65.0883999157789	70.8792875887067	66.8502993729765
stomach	57.5272974204429	71.853030566757	63.307279304122
testicle	60.0878293339172	69.9795425671665	69.3671661596926
cont.diffExp=-12.2019868623893,-10.7302306683572,-6.41288300727354,-6.61265613200549,-15.0407081179145,-5.79088767292782,-14.3257331463140,-9.89171323324933
cont.diffExpScore=0.987805889095296

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=-1,0,0,0,-1,0,-1,0
cont.diffExp1.2Score=0.75

tran.correlation=0.822200604970849
cont.tran.correlation=0.456601189261551

tran.covariance=0.0116039430523998
cont.tran.covariance=0.00136641415348389

tran.mean=61.633538107888
cont.tran.mean=65.0448691443985

weightedLogRatios:
wLogRatio
Lung	-0.804002435279481
cerebhem	-0.639278992884421
cortex	-0.776876579637504
heart	-0.83223020416408
kidney	-0.544093477287837
liver	-1.28236694364480
stomach	-0.0252552778462281
testicle	-1.19440086588156

cont.weightedLogRatios:
wLogRatio
Lung	-0.830183174344453
cerebhem	-0.685378828807857
cortex	-0.431750459703455
heart	-0.414156057992869
kidney	-0.932556121469116
liver	-0.359539078672264
stomach	-0.925796178372849
testicle	-0.635795376289685

varWeightedLogRatios=0.152857966176082
cont.varWeightedLogRatios=0.0539164237580441

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24702924530995	0.0770041957471624	55.1532186538869	3.63436447218527e-227	***
df.mm.trans1	-0.257033467954477	0.0611688860638677	-4.20202956918495	3.08312881593756e-05	***
df.mm.trans2	-0.0963300768724232	0.0611688860638677	-1.57482149947676	0.115868513392467	   
df.mm.exp2	-0.220646169909109	0.0814172877804954	-2.71006534268226	0.00693540606881655	** 
df.mm.exp3	0.228435506999228	0.0814172877804954	2.8057371256962	0.00519662058926572	** 
df.mm.exp4	0.0976399666130397	0.0814172877804954	1.19925349117845	0.230942063736463	   
df.mm.exp5	-0.0362498642403658	0.0814172877804954	-0.445235468148939	0.656323513657363	   
df.mm.exp6	0.0821249343007297	0.0814172877804954	1.00869160026728	0.313562911227514	   
df.mm.exp7	0.154785722883174	0.0814172877804954	1.90114074176093	0.0578022073601548	.  
df.mm.exp8	0.0786902028640309	0.0814172877804954	0.966504842020568	0.334213345744656	   
df.mm.trans1:exp2	0.123352357285615	0.0627362336097301	1.96620597361592	0.0497736999227402	*  
df.mm.trans2:exp2	0.0874274730122398	0.0627362336097301	1.39357223062049	0.164005609594604	   
df.mm.trans1:exp3	-0.167221377605916	0.0627362336097301	-2.66546727440107	0.00791245294844484	** 
df.mm.trans2:exp3	-0.176514199750331	0.0627362336097301	-2.81359255399984	0.00507309974928768	** 
df.mm.trans1:exp4	-0.113980553102818	0.0627362336097301	-1.81682173991938	0.0697846174401813	.  
df.mm.trans2:exp4	-0.106404507004696	0.0627362336097301	-1.69606144459703	0.0904360433151293	.  
df.mm.trans1:exp5	0.159120037603484	0.0627362336097301	2.53633392456007	0.0114754524231171	*  
df.mm.trans2:exp5	0.0923180477425542	0.0627362336097301	1.47152677855746	0.141716503802915	   
df.mm.trans1:exp6	-0.119264296333046	0.0627362336097301	-1.90104329620687	0.0578149964622796	.  
df.mm.trans2:exp6	-0.00322830337681135	0.0627362336097301	-0.0514583549419622	0.958978833981504	   
df.mm.trans1:exp7	0.236536629038303	0.0627362336097301	3.7703351863574	0.000180542842410760	***
df.mm.trans2:exp7	0.0445939164084298	0.0627362336097301	0.710815964596151	0.477497425099731	   
df.mm.trans1:exp8	-0.111717282547912	0.0627362336097301	-1.78074576875117	0.0755018673724773	.  
df.mm.trans2:exp8	-0.0167450455246338	0.0627362336097301	-0.266911871515932	0.789636339532311	   
df.mm.trans1:probe2	-0.0838347117617863	0.0449411260038957	-1.86543416278709	0.0626489300714765	.  
df.mm.trans1:probe3	-0.0658006734769522	0.0449411260038957	-1.46415275556844	0.143719402044531	   
df.mm.trans1:probe4	-0.151541399630848	0.0449411260038957	-3.37199828098903	0.000798324233633206	***
df.mm.trans1:probe5	-0.0505470377530115	0.0449411260038957	-1.12473901407432	0.261186712072545	   
df.mm.trans1:probe6	-0.0808467696670523	0.0449411260038957	-1.79894846560017	0.0725709615151915	.  
df.mm.trans2:probe2	0.0409774463024810	0.0449411260038957	0.911802839540089	0.36226909880167	   
df.mm.trans2:probe3	0.1746213596528	0.0449411260038957	3.88555817755129	0.000114443867282208	***
df.mm.trans2:probe4	0.177185668056736	0.0449411260038957	3.9426174600382	9.09257188958563e-05	***
df.mm.trans2:probe5	-0.051387467464069	0.0449411260038957	-1.14343969618417	0.253349931120267	   
df.mm.trans2:probe6	-0.0703995882528972	0.0449411260038957	-1.56648474376887	0.117806165136039	   
df.mm.trans3:probe2	0.386602740083934	0.0449411260038957	8.60242665149113	8.04886423260144e-17	***
df.mm.trans3:probe3	0.532814129321065	0.0449411260038957	11.8558250915849	4.70309122910484e-29	***
df.mm.trans3:probe4	0.154284015835411	0.0449411260038957	3.43302514988246	0.00064149166226983	***
df.mm.trans3:probe5	-0.0371921243078036	0.0449411260038957	-0.827574375964225	0.40826791846398	   
df.mm.trans3:probe6	0.316721975983129	0.0449411260038957	7.04748643715946	5.43676809484418e-12	***
df.mm.trans3:probe7	0.248035355760066	0.0449411260038957	5.5191175169613	5.23946998974034e-08	***
df.mm.trans3:probe8	0.644631273131748	0.0449411260038957	14.3439056928807	6.58220947234922e-40	***
df.mm.trans3:probe9	0.217589725710613	0.0449411260038957	4.84166163731081	1.67254170978401e-06	***
df.mm.trans3:probe10	0.529870072045177	0.0449411260038957	11.7903158901547	8.7673598496608e-29	***
df.mm.trans3:probe11	0.765005698962675	0.0449411260038957	17.0223972335798	1.41212058624495e-52	***
df.mm.trans3:probe12	0.364465729739034	0.0449411260038957	8.10984864303223	3.27457418889925e-15	***
df.mm.trans3:probe13	0.0495154315286853	0.0449411260038957	1.10178439953625	0.271033848553723	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.01072554182847	0.150460772971482	26.6562869684888	2.34291658621166e-101	***
df.mm.trans1	-0.0452343714207656	0.119519693565700	-0.378467933369492	0.705227995431354	   
df.mm.trans2	0.209442879080009	0.119519693565700	1.75237128569843	0.0802631816065408	.  
df.mm.exp2	0.117099393277790	0.159083643869449	0.736086944135415	0.461989335058972	   
df.mm.exp3	0.0861931581382886	0.159083643869449	0.541810308349628	0.588167026445881	   
df.mm.exp4	0.265522427118166	0.159083643869449	1.6690743351093	0.0956676094034875	.  
df.mm.exp5	0.238234858660745	0.159083643869449	1.49754464296940	0.134821117834188	   
df.mm.exp6	0.224825399709874	0.159083643869449	1.41325276591210	0.158143017758166	   
df.mm.exp7	0.169438625758272	0.159083643869449	1.06509143012415	0.287298534875633	   
df.mm.exp8	0.0951532005274576	0.159083643869449	0.598133146896888	0.549995534050904	   
df.mm.trans1:exp2	-0.0136984775902578	0.122582180239020	-0.111749338799060	0.911062633292267	   
df.mm.trans2:exp2	-0.0524152556002634	0.122582180239020	-0.427592783046117	0.669113774316759	   
df.mm.trans1:exp3	-0.0218077204557177	0.122582180239020	-0.177902860050256	0.858864294472947	   
df.mm.trans2:exp3	-0.119479734745977	0.122582180239020	-0.974690893186974	0.330139003707985	   
df.mm.trans1:exp4	-0.102621444293184	0.122582180239020	-0.83716445647389	0.402861117486558	   
df.mm.trans2:exp4	-0.206853084939386	0.122582180239020	-1.6874645608036	0.0920769340398512	.  
df.mm.trans1:exp5	-0.125568279907613	0.122582180239020	-1.02435998170998	0.306112347562737	   
df.mm.trans2:exp5	-0.107153497329736	0.122582180239020	-0.874136005093072	0.382422959760317	   
df.mm.trans1:exp6	-0.0437485460023706	0.122582180239020	-0.356891563823275	0.72130888141275	   
df.mm.trans2:exp6	-0.161197581351757	0.122582180239020	-1.31501643254706	0.189048428259631	   
df.mm.trans1:exp7	-0.111848543792260	0.122582180239020	-0.912437220272713	0.361935484034671	   
df.mm.trans2:exp7	-0.0921662719835143	0.122582180239020	-0.75187332941706	0.45244654137924	   
df.mm.trans1:exp8	0.00598462265141873	0.122582180239020	0.0488213102406031	0.961079294648409	   
df.mm.trans2:exp8	-0.0443006871704511	0.122582180239020	-0.361395816945581	0.717941357437113	   
df.mm.trans1:probe2	0.0606115897897349	0.0878117937749398	0.690244296171439	0.490329628653126	   
df.mm.trans1:probe3	0.0630487144205308	0.0878117937749398	0.717998251830769	0.473061028261396	   
df.mm.trans1:probe4	0.141755400758569	0.0878117937749398	1.61430936170016	0.107029720502440	   
df.mm.trans1:probe5	0.225601654407955	0.0878117937749398	2.56914982270114	0.0104554194042005	*  
df.mm.trans1:probe6	0.063370730581309	0.0878117937749398	0.721665369275193	0.470804702403894	   
df.mm.trans2:probe2	-0.0805225234511906	0.0878117937749398	-0.916989848283575	0.359546967458002	   
df.mm.trans2:probe3	-0.0992232187113096	0.0878117937749398	-1.12995321523231	0.258984921302456	   
df.mm.trans2:probe4	-0.0884630141446169	0.0878117937749398	-1.00741609232293	0.314174658961664	   
df.mm.trans2:probe5	-0.158737232923048	0.0878117937749398	-1.8076983295648	0.0711957021983246	.  
df.mm.trans2:probe6	-0.006595706193696	0.0878117937749398	-0.0751118489914997	0.940152834624927	   
df.mm.trans3:probe2	0.151132810057128	0.0878117937749398	1.72109922323736	0.0857911229270678	.  
df.mm.trans3:probe3	-0.0616361438301504	0.0878117937749398	-0.70191190932875	0.483028873576904	   
df.mm.trans3:probe4	0.080664917377891	0.0878117937749398	0.918611429173555	0.358698615685945	   
df.mm.trans3:probe5	-0.0574068241185543	0.0878117937749398	-0.653748450529175	0.513545136180566	   
df.mm.trans3:probe6	0.133131013055193	0.0878117937749398	1.51609490402173	0.1300657142964	   
df.mm.trans3:probe7	0.00371608724571568	0.0878117937749398	0.0423187716132978	0.966259828416058	   
df.mm.trans3:probe8	0.0158126887651676	0.0878117937749398	0.180074772253204	0.857159715362591	   
df.mm.trans3:probe9	0.0838868108865627	0.0878117937749398	0.955302326491168	0.339841486571352	   
df.mm.trans3:probe10	-0.0317186707874446	0.0878117937749398	-0.361211967366695	0.71807870228969	   
df.mm.trans3:probe11	-0.0598602171694763	0.0878117937749398	-0.681687670825823	0.495721337329101	   
df.mm.trans3:probe12	-0.0343723943044287	0.0878117937749398	-0.391432549396777	0.695628043838944	   
df.mm.trans3:probe13	-0.123998097517596	0.0878117937749398	-1.41208933546445	0.158485103324261