chr9.24679_chr9_58554171_58557394_+_2.R 

fitVsDatCorrelation=0.915624878871123
cont.fitVsDatCorrelation=0.240503547888066

fstatistic=10179.3722900070,70,1106
cont.fstatistic=1733.22367137384,70,1106

residuals=-0.815810871769017,-0.0992089271605756,-0.00496978557582905,0.0894043832499506,1.20088037877914
cont.residuals=-0.66052131646335,-0.244767369275791,-0.109708613669148,0.116217203365612,1.97512636594955

predictedValues:
Include	Exclude	Both
chr9.24679_chr9_58554171_58557394_+_2.R.tl.Lung	50.3434601782478	53.0386301123437	59.7148985796404
chr9.24679_chr9_58554171_58557394_+_2.R.tl.cerebhem	54.4377695265925	46.9038016386102	59.0957666953324
chr9.24679_chr9_58554171_58557394_+_2.R.tl.cortex	51.4474392215777	51.7692425786813	58.1583042292829
chr9.24679_chr9_58554171_58557394_+_2.R.tl.heart	52.1539851429896	58.2571351023194	56.299327388009
chr9.24679_chr9_58554171_58557394_+_2.R.tl.kidney	60.540463089775	51.896431420251	71.9561143664459
chr9.24679_chr9_58554171_58557394_+_2.R.tl.liver	53.4942706333185	53.2180364606143	63.1924275181762
chr9.24679_chr9_58554171_58557394_+_2.R.tl.stomach	54.6563844252281	58.2965470248122	58.8571968565857
chr9.24679_chr9_58554171_58557394_+_2.R.tl.testicle	52.3682506391394	52.2150731110484	61.0348203596591


diffExp=-2.69516993409586,7.53396788798234,-0.321803357103626,-6.10314995932978,8.64403166952397,0.276234172704129,-3.64016259958409,0.153177528091028
diffExpScore=6.05878631875396
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=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	62.7922700363077	50.954203984662	56.0745090338112
cerebhem	60.8458300010203	67.8747279481667	61.7860461301488
cortex	58.0551120775827	57.8480148272758	61.4612004158762
heart	66.1364180642028	62.9212488408992	63.7151130581205
kidney	64.529562301675	60.3622951860125	63.684623275278
liver	58.0929687907003	69.8556513029254	58.0481266196373
stomach	60.2188441629131	65.6838249874214	59.2297841804031
testicle	59.627396597756	61.886403841103	59.9478678601474
cont.diffExp=11.8380660516457,-7.02889794714635,0.207097250306937,3.21516922330358,4.16726711566252,-11.7626825122251,-5.46498082450825,-2.25900724334703
cont.diffExpScore=5.68043334661212

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

tran.correlation=-0.140744821100271
cont.tran.correlation=-0.285896784129442

tran.covariance=-0.000561346603824225
cont.tran.covariance=-0.00132543364497356

tran.mean=53.4398075190968
cont.tran.mean=61.730298309414

weightedLogRatios:
wLogRatio
Lung	-0.205735941554872
cerebhem	0.584305229890802
cortex	-0.0245908520344620
heart	-0.443718965660781
kidney	0.620296595378497
liver	0.0205896004169505
stomach	-0.260054694152488
testicle	0.0115907344938161

cont.weightedLogRatios:
wLogRatio
Lung	0.843009806095804
cerebhem	-0.455101553126351
cortex	0.0145075313714521
heart	0.207655161106112
kidney	0.275963755039396
liver	-0.765984752611025
stomach	-0.359754181475532
testicle	-0.152709431487343

varWeightedLogRatios=0.146104809974884
cont.varWeightedLogRatios=0.251071058220873

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.46826868336292	0.0754671710812007	45.9573167202883	9.27072331073931e-259	***
df.mm.trans1	0.320174444776823	0.0648392891501766	4.93796969357969	9.1092351136551e-07	***
df.mm.trans2	0.367736888730721	0.0561228786949311	6.55235257495682	8.66346170345049e-11	***
df.mm.exp2	-0.0343100509372006	0.0704391570412285	-0.487087755992291	0.626292661700395	   
df.mm.exp3	0.0238805184678341	0.0704391570412285	0.339023342568633	0.734656502129905	   
df.mm.exp4	0.188076888391552	0.0704391570412285	2.67006160055932	0.00769490458453459	** 
df.mm.exp5	-0.0238021234555483	0.0704391570412285	-0.337910396082916	0.735494839072302	   
df.mm.exp6	0.00747975619024087	0.0704391570412285	0.106187474473366	0.915452864844803	   
df.mm.exp7	0.191187082928766	0.0704391570412285	2.71421594123937	0.00674659421931323	** 
df.mm.exp8	0.00191949220888786	0.0704391570412285	0.0272503574647318	0.978264967120063	   
df.mm.trans1:exp2	0.112499533153597	0.0651052066945489	1.72796522529151	0.0842735901586557	.  
df.mm.trans2:exp2	-0.0886117366026512	0.0427636713298824	-2.07212650006341	0.0384849548016527	*  
df.mm.trans1:exp3	-0.00218855310583586	0.0651052066945489	-0.0336156387015833	0.973189716874593	   
df.mm.trans2:exp3	-0.0481048362670694	0.0427636713298824	-1.12489958815708	0.260875649032426	   
df.mm.trans1:exp4	-0.152745016436691	0.0651052066945489	-2.34612597350805	0.0191455189465465	*  
df.mm.trans2:exp4	-0.094230830519786	0.0427636713298824	-2.20352527248846	0.0277632734139894	*  
df.mm.trans1:exp5	0.208245352834886	0.0651052066945489	3.19859752249772	0.0014201872655108	** 
df.mm.trans2:exp5	0.00203163440180437	0.0427636713298824	0.0475084186793081	0.962116597775902	   
df.mm.trans1:exp6	0.0532260775070399	0.0651052066945489	0.817539490455168	0.413796269977815	   
df.mm.trans2:exp6	-0.00410290418575514	0.0427636713298824	-0.0959436843975582	0.923582680366503	   
df.mm.trans1:exp7	-0.108989774750215	0.0651052066945489	-1.67405619740303	0.0944022950701864	.  
df.mm.trans2:exp7	-0.096664737130687	0.0427636713298824	-2.26044055911401	0.0239876980339538	*  
df.mm.trans1:exp8	0.0375122881469607	0.0651052066945489	0.576179541568086	0.564611058766611	   
df.mm.trans2:exp8	-0.017568800185486	0.0427636713298824	-0.410834702426713	0.681273328063763	   
df.mm.trans1:probe2	0.0815839237034256	0.0484737809986129	1.68305261159141	0.0926471322772983	.  
df.mm.trans1:probe3	0.854704926127998	0.0484737809986129	17.6323139751045	1.63758316043381e-61	***
df.mm.trans1:probe4	0.200705529121191	0.0484737809986129	4.14049667648031	3.7290910801826e-05	***
df.mm.trans1:probe5	0.0370089887039109	0.0484737809986129	0.763484670299804	0.445337227521266	   
df.mm.trans1:probe6	-0.0141992854892341	0.0484737809986129	-0.292927128784123	0.769632800150993	   
df.mm.trans1:probe7	0.0951349330754742	0.0484737809986129	1.96260599267461	0.0499423556053675	*  
df.mm.trans1:probe8	0.345444738791553	0.0484737809986129	7.12642446442207	1.85457517036519e-12	***
df.mm.trans1:probe9	0.113775873928485	0.0484737809986129	2.34716317944624	0.0190925743138345	*  
df.mm.trans1:probe10	0.129986911719985	0.0484737809986129	2.68159217296676	0.00743636188474392	** 
df.mm.trans1:probe11	0.000275780685573208	0.0484737809986129	0.00568927531320695	0.995461665536653	   
df.mm.trans1:probe12	0.506794328196001	0.0484737809986129	10.4550195539833	1.83757439938725e-24	***
df.mm.trans1:probe13	1.36597237374455	0.0484737809986129	28.1796126814129	4.01114177541177e-132	***
df.mm.trans1:probe14	-0.000233636781114169	0.0484737809986129	-0.0048198588247295	0.996155193143622	   
df.mm.trans1:probe15	0.810086296620911	0.0484737809986129	16.7118446288333	4.48214845539673e-56	***
df.mm.trans1:probe16	0.0189709171966658	0.0484737809986129	0.391364502744456	0.695603211446849	   
df.mm.trans1:probe17	0.0275410216613485	0.0484737809986129	0.568163264634475	0.570039440593564	   
df.mm.trans1:probe18	0.0455490148793712	0.0484737809986129	0.939662925833547	0.347595656865165	   
df.mm.trans1:probe19	0.0488197787918369	0.0484737809986129	1.00713783381647	0.314088828188327	   
df.mm.trans1:probe20	0.0704898800311616	0.0484737809986129	1.45418571811386	0.146178534660872	   
df.mm.trans1:probe21	0.142764216403720	0.0484737809986129	2.94518425141635	0.00329517369769679	** 
df.mm.trans1:probe22	0.0877029266070653	0.0484737809986129	1.80928586135204	0.0706780131176049	.  
df.mm.trans1:probe23	0.125299914900897	0.0484737809986129	2.58490079213095	0.0098678387190531	** 
df.mm.trans1:probe24	0.222100316734660	0.0484737809986129	4.58186492077059	5.13209992158007e-06	***
df.mm.trans1:probe25	0.0553226466102603	0.0484737809986129	1.14129010509503	0.253996265802461	   
df.mm.trans1:probe26	0.236698284698386	0.0484737809986129	4.88301675301869	1.19837485321802e-06	***
df.mm.trans2:probe2	0.732050449361891	0.0484737809986129	15.1019878020829	5.42552913840675e-47	***
df.mm.trans2:probe3	0.485119137939874	0.0484737809986129	10.0078666847498	1.24819151259847e-22	***
df.mm.trans2:probe4	1.84644108265137	0.0484737809986129	38.0915423681147	1.68819881846407e-203	***
df.mm.trans2:probe5	0.0588842984591712	0.0484737809986129	1.21476594658164	0.224714651427062	   
df.mm.trans2:probe6	-0.0171512102758923	0.0484737809986129	-0.353824478358374	0.72353786486345	   
df.mm.trans3:probe2	-0.209745641910782	0.0484737809986129	-4.32699157337827	1.64832129085669e-05	***
df.mm.trans3:probe3	0.0580851968327375	0.0484737809986129	1.19828071250311	0.231064458972595	   
df.mm.trans3:probe4	0.364731866096685	0.0484737809986129	7.52431228971228	1.09479466249935e-13	***
df.mm.trans3:probe5	-0.364803256949343	0.0484737809986129	-7.52578506223358	1.08311820040472e-13	***
df.mm.trans3:probe6	-0.237929837257146	0.0484737809986129	-4.90842332402241	1.05601699649901e-06	***
df.mm.trans3:probe7	-0.273298584702258	0.0484737809986129	-5.63807029433248	2.18199060054051e-08	***
df.mm.trans3:probe8	-0.252974409765439	0.0484737809986129	-5.21878847809867	2.14961079676441e-07	***
df.mm.trans3:probe9	0.232885973024963	0.0484737809986129	4.80436987227439	1.76603903881114e-06	***
df.mm.trans3:probe10	0.170292530512363	0.0484737809986129	3.51308536293541	0.000460822915122692	***
df.mm.trans3:probe11	0.0121998026751172	0.0484737809986129	0.251678380018805	0.80133642547555	   
df.mm.trans3:probe12	-0.230912190390607	0.0484737809986129	-4.76365131074084	2.15396106531182e-06	***
df.mm.trans3:probe13	-0.325313060640651	0.0484737809986129	-6.71111380088053	3.07861236017199e-11	***
df.mm.trans3:probe14	-0.281124533782744	0.0484737809986129	-5.79951734713635	8.6724235763223e-09	***
df.mm.trans3:probe15	-0.0910545380268555	0.0484737809986129	-1.87842862989089	0.0605854316580987	.  
df.mm.trans3:probe16	-0.0733643718164968	0.0484737809986129	-1.51348564739763	0.130442038930305	   
df.mm.trans3:probe17	0.370151063409785	0.0484737809986129	7.63610875372765	4.82600126123601e-14	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.85373098985969	0.182203834135847	21.1506580426098	1.18552254214111e-83	***
df.mm.trans1	0.276124222734906	0.156544453920148	1.76387100162459	0.078029747127042	.  
df.mm.trans2	0.072069727758282	0.135500026494365	0.531879805656563	0.594916060927524	   
df.mm.exp2	0.158251589158854	0.170064470449005	0.930538805319165	0.352295243085581	   
df.mm.exp3	-0.0432721040611711	0.170064470449005	-0.254445293287445	0.799198862263713	   
df.mm.exp4	0.135103766487399	0.170064470449005	0.794426761396415	0.427117456044309	   
df.mm.exp5	0.0694670459065782	0.170064470449005	0.40847477267398	0.68300421900279	   
df.mm.exp6	0.203125269664719	0.170064470449005	1.19440156505604	0.232577010884694	   
df.mm.exp7	0.157335582235852	0.170064470449005	0.925152571965524	0.355088360565575	   
df.mm.exp8	0.0758624150885213	0.170064470449005	0.4460803299374	0.655626535100455	   
df.mm.trans1:exp2	-0.189740278531173	0.157186470779327	-1.20710311511191	0.227650531390417	   
df.mm.trans2:exp2	0.128484912726376	0.103246282673642	1.24445073855600	0.213597365509993	   
df.mm.trans1:exp3	-0.0351671056245969	0.157186470779327	-0.223728578230933	0.823009825223668	   
df.mm.trans2:exp3	0.170163973017498	0.103246282673642	1.64813655863408	0.0996086728497442	.  
df.mm.trans1:exp4	-0.0832161945808738	0.157186470779327	-0.529410668540937	0.59662684129606	   
df.mm.trans2:exp4	0.0758528913503316	0.103246282673642	0.73467915150127	0.462690656950809	   
df.mm.trans1:exp5	-0.0421755741518576	0.157186470779327	-0.268315548677645	0.788506474230712	   
df.mm.trans2:exp5	0.099970343989949	0.103246282673642	0.96827063794589	0.33312091081927	   
df.mm.trans1:exp6	-0.280912609527496	0.157186470779327	-1.78712969465335	0.0741903008305063	.  
df.mm.trans2:exp6	0.112378450804332	0.103246282673642	1.08845033345711	0.276633470766686	   
df.mm.trans1:exp7	-0.199182230245773	0.157186470779327	-1.2671715909024	0.205360692267113	   
df.mm.trans2:exp7	0.0965898496966308	0.103246282673642	0.935528594302499	0.349720169871427	   
df.mm.trans1:exp8	-0.127579249480467	0.157186470779327	-0.811642686854235	0.417171329090941	   
df.mm.trans2:exp8	0.118510825090323	0.103246282673642	1.14784592744062	0.251280389977253	   
df.mm.trans1:probe2	-0.0137178078784747	0.117032460955844	-0.117213700937643	0.906711991201837	   
df.mm.trans1:probe3	-0.0815336751016484	0.117032460955844	-0.696675729415028	0.486152143411274	   
df.mm.trans1:probe4	0.0253673590206593	0.117032460955844	0.216754897004433	0.82843933749377	   
df.mm.trans1:probe5	0.121721657258405	0.117032460955844	1.04006748439076	0.298535857298104	   
df.mm.trans1:probe6	0.168309277391854	0.117032460955844	1.43814182849113	0.150676703591959	   
df.mm.trans1:probe7	0.0408215017693795	0.117032460955844	0.348804950660495	0.727302135676658	   
df.mm.trans1:probe8	-0.0518944576243545	0.117032460955844	-0.443419348790197	0.657549167900354	   
df.mm.trans1:probe9	-0.0440544435551953	0.117032460955844	-0.376429267533021	0.706669990686411	   
df.mm.trans1:probe10	-0.0350378520109614	0.117032460955844	-0.299385757804248	0.764701977403813	   
df.mm.trans1:probe11	-0.0582327479934839	0.117032460955844	-0.497577744822908	0.618880601474033	   
df.mm.trans1:probe12	-0.0422931401148748	0.117032460955844	-0.361379567424732	0.717884741490138	   
df.mm.trans1:probe13	-0.0033211355658059	0.117032460955844	-0.0283779007865088	0.977365869257655	   
df.mm.trans1:probe14	0.0634848384431067	0.117032460955844	0.542454955869546	0.587614411932465	   
df.mm.trans1:probe15	0.0725334714388194	0.117032460955844	0.619772248198609	0.535535401045003	   
df.mm.trans1:probe16	-0.0626984636353276	0.117032460955844	-0.535735667892889	0.592248962872192	   
df.mm.trans1:probe17	0.138590189186706	0.117032460955844	1.18420298141894	0.236587150762712	   
df.mm.trans1:probe18	0.0502335462618789	0.117032460955844	0.429227462633908	0.667841295496371	   
df.mm.trans1:probe19	-0.0356124731209468	0.117032460955844	-0.304295687111828	0.760959873414636	   
df.mm.trans1:probe20	-0.133805437879039	0.117032460955844	-1.14331901411117	0.253153573981193	   
df.mm.trans1:probe21	-0.0170044181661856	0.117032460955844	-0.145296595724850	0.884503176406515	   
df.mm.trans1:probe22	-0.00201304665295097	0.117032460955844	-0.0172007547009584	0.986279562442052	   
df.mm.trans1:probe23	0.116045591232571	0.117032460955844	0.991567555572075	0.321625401369362	   
df.mm.trans1:probe24	-0.0981874888334997	0.117032460955844	-0.838976537206592	0.401663769621466	   
df.mm.trans1:probe25	0.196992840575144	0.117032460955844	1.68323248922765	0.092612308271974	.  
df.mm.trans1:probe26	0.114307198071658	0.117032460955844	0.97671361550524	0.328924533062284	   
df.mm.trans2:probe2	0.089026121924232	0.117032460955844	0.760695974408513	0.447000820043738	   
df.mm.trans2:probe3	-0.0451709716790292	0.117032460955844	-0.385969596042862	0.699593416875707	   
df.mm.trans2:probe4	0.0495064497853445	0.117032460955844	0.423014686532339	0.67236678120274	   
df.mm.trans2:probe5	-0.00772460166634046	0.117032460955844	-0.0660039240673143	0.947386629856064	   
df.mm.trans2:probe6	0.0322736657284752	0.117032460955844	0.275766786965643	0.782778709933333	   
df.mm.trans3:probe2	-0.233152102017251	0.117032460955844	-1.99220028454515	0.0465945952879758	*  
df.mm.trans3:probe3	-0.173711855813282	0.117032460955844	-1.48430490476333	0.138012977724699	   
df.mm.trans3:probe4	-0.114569606971271	0.117032460955844	-0.978955804530995	0.327815898278955	   
df.mm.trans3:probe5	-0.215832408113218	0.117032460955844	-1.84420977180554	0.0654198870827579	.  
df.mm.trans3:probe6	-0.0852429876803752	0.117032460955844	-0.72837046221336	0.466541023488128	   
df.mm.trans3:probe7	-0.307436109928291	0.117032460955844	-2.62693023300848	0.00873503231801217	** 
df.mm.trans3:probe8	-0.247402183292148	0.117032460955844	-2.11396206891259	0.0347418785998480	*  
df.mm.trans3:probe9	-0.335566357997185	0.117032460955844	-2.86729301645458	0.00421855092075298	** 
df.mm.trans3:probe10	-0.229092652780143	0.117032460955844	-1.95751376078966	0.0505382923756292	.  
df.mm.trans3:probe11	-0.162323879850733	0.117032460955844	-1.38699877388699	0.16572158861935	   
df.mm.trans3:probe12	-0.0936540313576538	0.117032460955844	-0.800239784695198	0.423743733595416	   
df.mm.trans3:probe13	-0.107791173496673	0.117032460955844	-0.921036545043196	0.357232199356886	   
df.mm.trans3:probe14	-0.210379161841014	0.117032460955844	-1.7976137570959	0.0725109137202803	.  
df.mm.trans3:probe15	-0.247900671453523	0.117032460955844	-2.11822146974296	0.0343788626734128	*  
df.mm.trans3:probe16	-0.0909971514167017	0.117032460955844	-0.77753770768808	0.437007877665252	   
df.mm.trans3:probe17	-0.124089129697132	0.117032460955844	-1.06029667908932	0.289241137707394