chr9.24631_chr9_120308824_120310862_+_2.R 

fitVsDatCorrelation=0.855010141443355
cont.fitVsDatCorrelation=0.260687612128172

fstatistic=8104.23733725514,71,1129
cont.fstatistic=2327.31228023466,71,1129

residuals=-0.917201142651166,-0.106063266505077,9.0945195148729e-05,0.0933451430220958,1.05229279017420
cont.residuals=-0.785466514978223,-0.250063446243284,-0.0753889287399827,0.203896849084687,1.27057390629783

predictedValues:
Include	Exclude	Both
chr9.24631_chr9_120308824_120310862_+_2.R.tl.Lung	63.6766632740254	59.4035546383068	64.764091066731
chr9.24631_chr9_120308824_120310862_+_2.R.tl.cerebhem	61.4349862044989	52.8837087049493	66.4141916425557
chr9.24631_chr9_120308824_120310862_+_2.R.tl.cortex	60.1753856015657	56.439889068585	59.9078363986914
chr9.24631_chr9_120308824_120310862_+_2.R.tl.heart	60.3943296153565	58.5722710244102	60.7558912497547
chr9.24631_chr9_120308824_120310862_+_2.R.tl.kidney	73.84863170459	60.1690832645305	78.163701394941
chr9.24631_chr9_120308824_120310862_+_2.R.tl.liver	62.6795089597175	56.0308657977999	63.9032352440249
chr9.24631_chr9_120308824_120310862_+_2.R.tl.stomach	91.9179957756741	62.7780145302766	92.4962163589587
chr9.24631_chr9_120308824_120310862_+_2.R.tl.testicle	62.0619715207251	58.8873095453799	63.3514109624369


diffExp=4.27310863571862,8.55127749954963,3.73549653298060,1.82205859094627,13.6795484400595,6.64864316191765,29.1399812453975,3.17466197534527
diffExpScore=0.986115888803838
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,1,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,0,0,1,0
diffExp1.3Score=0.5
diffExp1.2=0,0,0,0,1,0,1,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	65.4791685357064	72.8777665543003	69.5012284239158
cerebhem	60.8757722789114	52.7680431002231	69.7424270222026
cortex	66.5269045811906	63.6690075282284	68.9783731366767
heart	60.8260227513146	68.1977060622141	66.8012290676278
kidney	65.6863112262034	58.9512336013276	69.8904103353415
liver	67.9584805161884	63.740767139324	60.8297486900633
stomach	64.2214815503154	60.4062002458478	66.5656812444928
testicle	59.6929483126863	58.8231471687988	66.5266719918784
cont.diffExp=-7.39859801859392,8.10772917868832,2.85789705296222,-7.37168331089953,6.73507762487581,4.21771337686442,3.81528130446755,0.869801143887486
cont.diffExpScore=3.22395987316601

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=0.732305668304633
cont.tran.correlation=0.338655380383938

tran.covariance=0.00550721170747539
cont.tran.covariance=0.00170299269013168

tran.mean=62.5846355768995
cont.tran.mean=63.1688100720488

weightedLogRatios:
wLogRatio
Lung	0.286128505487863
cerebhem	0.605987238159727
cortex	0.260528675406698
heart	0.125156895413820
kidney	0.860322687027001
liver	0.457718775891352
stomach	1.65108960268727
testicle	0.215380737799863

cont.weightedLogRatios:
wLogRatio
Lung	-0.45339092612241
cerebhem	0.577059367106625
cortex	0.183346789964633
heart	-0.476472301133077
kidney	0.446869995725763
liver	0.268263020695878
stomach	0.253051024917919
testicle	0.059915625565304

varWeightedLogRatios=0.25224957719067
cont.varWeightedLogRatios=0.149475271475977

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.15429726348118	0.086260989815307	48.1596289629406	5.31583778530681e-276	***
df.mm.trans1	-0.0416937395998341	0.0734765445460333	-0.567442846658539	0.570526158171749	   
df.mm.trans2	-0.0769842394652676	0.0639086185970449	-1.20459870914543	0.228610711084148	   
df.mm.exp2	-0.17725686423959	0.0799041356814978	-2.21836908349957	0.0267280323226008	*  
df.mm.exp3	-0.0297886773382894	0.0799041356814978	-0.372805200684839	0.709363408307387	   
df.mm.exp4	-0.00312834819363463	0.0799041356814978	-0.0391512675401984	0.968776708441935	   
df.mm.exp5	-0.0270501383692485	0.0799041356814978	-0.338532394331525	0.735024965498831	   
df.mm.exp6	-0.0608536019159085	0.0799041356814978	-0.761582631448192	0.446468195627775	   
df.mm.exp7	0.0659131056766896	0.0799041356814978	0.824902304674476	0.4096013082767	   
df.mm.exp8	-0.0123590519554230	0.0799041356814978	-0.154673495308013	0.877106371757829	   
df.mm.trans1:exp2	0.141418203176416	0.07251182158635	1.9502779006594	0.0513902056130328	.  
df.mm.trans2:exp2	0.0609981247097277	0.0474701301712259	1.28497909084525	0.199063145537662	   
df.mm.trans1:exp3	-0.0267660728386118	0.07251182158635	-0.369127023057029	0.712102261989835	   
df.mm.trans2:exp3	-0.0213892281279861	0.0474701301712259	-0.450582883401303	0.652376720486248	   
df.mm.trans1:exp4	-0.0497945736413645	0.07251182158635	-0.686709733006323	0.492406678294506	   
df.mm.trans2:exp4	-0.0109643248970274	0.0474701301712259	-0.23097313737036	0.817377520089999	   
df.mm.trans1:exp5	0.175249477311390	0.07251182158635	2.41684008865639	0.0158136335558594	*  
df.mm.trans2:exp5	0.0398547247550764	0.0474701301712259	0.839574793903438	0.401324579935911	   
df.mm.trans1:exp6	0.04507004346242	0.07251182158635	0.621554423491468	0.534360377697276	   
df.mm.trans2:exp6	0.00240224879679009	0.0474701301712259	0.0506054815549298	0.959648846157797	   
df.mm.trans1:exp7	0.301165581790815	0.07251182158635	4.15333079768483	3.52365464336636e-05	***
df.mm.trans2:exp7	-0.0106622475686882	0.0474701301712259	-0.224609613039384	0.822323628744457	   
df.mm.trans1:exp8	-0.0133256633790249	0.07251182158635	-0.183772288262765	0.854225096180279	   
df.mm.trans2:exp8	0.00363059479116345	0.0474701301712259	0.0764816691689659	0.939049447721612	   
df.mm.trans1:probe2	0.816443221101909	0.0556636616689969	14.6674364679218	1.02642912175274e-44	***
df.mm.trans1:probe3	0.664065134498545	0.055663661668997	11.9299577962980	5.50924114291477e-31	***
df.mm.trans1:probe4	0.318709641360531	0.0556636616689969	5.72563197972373	1.32001509597291e-08	***
df.mm.trans1:probe5	0.535246272203698	0.055663661668997	9.61572157050199	4.29891217656469e-21	***
df.mm.trans1:probe6	-0.104979672685271	0.055663661668997	-1.88596419167555	0.0595562951297805	.  
df.mm.trans1:probe7	0.382035837355796	0.0556636616689969	6.86328972800184	1.10761359803544e-11	***
df.mm.trans1:probe8	0.286785646253815	0.0556636616689969	5.15211607815493	3.03789839616421e-07	***
df.mm.trans1:probe9	-0.0558198326955315	0.055663661668997	-1.00280561899544	0.316169533036297	   
df.mm.trans1:probe10	0.371883102675362	0.055663661668997	6.6808954266566	3.72101200671732e-11	***
df.mm.trans1:probe11	-0.226104567506456	0.055663661668997	-4.06197797139152	5.20205585803596e-05	***
df.mm.trans1:probe12	-0.169447936465267	0.0556636616689969	-3.04413923526781	0.00238748824435575	** 
df.mm.trans1:probe13	-0.270916353291915	0.055663661668997	-4.86702356921675	1.29375827535757e-06	***
df.mm.trans1:probe14	-0.0934629689573113	0.055663661668997	-1.67906612958895	0.0934158601075207	.  
df.mm.trans1:probe15	-0.322610151524561	0.055663661668997	-5.79570480725751	8.81904011921735e-09	***
df.mm.trans1:probe16	-0.174619356978614	0.055663661668997	-3.13704402015421	0.00175075794027931	** 
df.mm.trans1:probe17	0.100927817240058	0.0556636616689969	1.81317243986254	0.070070683356314	.  
df.mm.trans1:probe18	-0.0286007006911821	0.055663661668997	-0.513812778994952	0.607483435502077	   
df.mm.trans1:probe19	0.109158211782345	0.055663661668997	1.96103182056998	0.050120837863295	.  
df.mm.trans1:probe20	-0.112054277301919	0.055663661668997	-2.01305975823595	0.0443453527031399	*  
df.mm.trans1:probe21	-0.0470818111237859	0.0556636616689969	-0.845826697563611	0.397828656023038	   
df.mm.trans1:probe22	-0.166114065586016	0.055663661668997	-2.98424610608282	0.00290394461014939	** 
df.mm.trans2:probe2	0.0689474938193268	0.055663661668997	1.23864459778665	0.215734611206791	   
df.mm.trans2:probe3	0.0358326537717329	0.055663661668997	0.643735117262159	0.519877954380314	   
df.mm.trans2:probe4	0.0790106888159027	0.055663661668997	1.41943031498248	0.156049632904816	   
df.mm.trans2:probe5	0.0882566599597042	0.055663661668997	1.58553457162989	0.113124960370285	   
df.mm.trans2:probe6	-0.0748982935443076	0.055663661668997	-1.34555096266733	0.178717538523216	   
df.mm.trans3:probe2	-0.148418790615091	0.055663661668997	-2.66634975430939	0.00777754748718577	** 
df.mm.trans3:probe3	0.499708425877689	0.055663661668997	8.97728268127952	1.1339582807602e-18	***
df.mm.trans3:probe4	-0.191143830242998	0.055663661668997	-3.43390687051153	0.000616536662160939	***
df.mm.trans3:probe5	-0.250446592799415	0.055663661668997	-4.4992834695046	7.52334349635468e-06	***
df.mm.trans3:probe6	0.238881786385958	0.055663661668997	4.2915212406698	1.92663742813264e-05	***
df.mm.trans3:probe7	0.161034370326660	0.055663661668997	2.89298916920428	0.00388921712133766	** 
df.mm.trans3:probe8	0.0629681261837362	0.055663661668997	1.13122500920214	0.258200628543921	   
df.mm.trans3:probe9	0.750835071365943	0.055663661668997	13.4887833256599	1.48195946658561e-38	***
df.mm.trans3:probe10	-0.230480004008607	0.055663661668997	-4.14058287036798	3.72220340175164e-05	***
df.mm.trans3:probe11	-0.15186734851434	0.055663661668997	-2.72830324058479	0.00646490953047285	** 
df.mm.trans3:probe12	0.234735391569594	0.055663661668997	4.21703108511696	2.67343951679647e-05	***
df.mm.trans3:probe13	0.380946780806725	0.055663661668997	6.84372478174395	1.26310260196164e-11	***
df.mm.trans3:probe14	0.00241666732107079	0.055663661668997	0.0434155290652897	0.965377975968746	   
df.mm.trans3:probe15	-0.189059472822144	0.055663661668997	-3.39646130264269	0.000706399108594352	***
df.mm.trans3:probe16	0.164854627468790	0.055663661668997	2.96162024785748	0.00312427849241277	** 
df.mm.trans3:probe17	0.096168007245726	0.055663661668997	1.72766225509180	0.0843222622371857	.  
df.mm.trans3:probe18	0.492763924617408	0.055663661668997	8.8525244269344	3.24630551429818e-18	***
df.mm.trans3:probe19	0.0657223771962733	0.055663661668997	1.18070524334332	0.237968518919397	   
df.mm.trans3:probe20	0.0363785674513406	0.055663661668997	0.653542479250918	0.513539690036851	   
df.mm.trans3:probe21	0.568903524721934	0.055663661668997	10.2203755136504	1.63660632175256e-23	***
df.mm.trans3:probe22	0.378002723530838	0.055663661668997	6.79083467017719	1.79864018542503e-11	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24509653121397	0.160579541779124	26.4360981740318	2.89483100244991e-120	***
df.mm.trans1	-0.125920931233213	0.136780598970379	-0.920605204108534	0.357453246607431	   
df.mm.trans2	0.0273490761572031	0.118969382475475	0.229883316094719	0.8182240831434	   
df.mm.exp2	-0.399239044670039	0.148745910769912	-2.68403374992677	0.0073804067487564	** 
df.mm.exp3	-0.111659904308109	0.148745910769912	-0.750675455413565	0.453004419918676	   
df.mm.exp4	-0.100464081389281	0.148745910769912	-0.675407349817398	0.499555301997219	   
df.mm.exp5	-0.214498578389307	0.148745910769912	-1.44204689244268	0.149566478190025	   
df.mm.exp6	0.0364710916245302	0.148745910769912	0.245190549681367	0.806353452763481	   
df.mm.exp7	-0.163930870855092	0.148745910769912	-1.10208657170193	0.270658918137787	   
df.mm.exp8	-0.263024852167679	0.148745910769912	-1.76828291148481	0.0772836357736944	.  
df.mm.trans1:exp2	0.326342257865163	0.134984714513901	2.41762379570434	0.0157797994126541	*  
df.mm.trans2:exp2	0.0763612008746741	0.0883682388459934	0.86412496018796	0.387702797459934	   
df.mm.trans1:exp3	0.127534295883996	0.134984714513901	0.94480546440584	0.344960349889788	   
df.mm.trans2:exp3	-0.0234257964895401	0.0883682388459934	-0.265092942843030	0.790986255179547	   
df.mm.trans1:exp4	0.0267497301375429	0.134984714513901	0.198168586968328	0.842948839749816	   
df.mm.trans2:exp4	0.0340914032622605	0.0883682388459934	0.385787967571408	0.699726387891392	   
df.mm.trans1:exp5	0.217657075016307	0.134984714513901	1.61245720154405	0.107141962288661	   
df.mm.trans2:exp5	0.00242552442556181	0.0883682388459934	0.0274479208507139	0.978107328089895	   
df.mm.trans1:exp6	0.000693791993302589	0.134984714513901	0.00513978190642573	0.995899973435008	   
df.mm.trans2:exp6	-0.170430354221175	0.0883682388459934	-1.92863812209948	0.0540262737607874	.  
df.mm.trans1:exp7	0.144536574737466	0.134984714513901	1.07076253232051	0.284505067412909	   
df.mm.trans2:exp7	-0.0237609833550001	0.0883682388459934	-0.268886012274278	0.78806652826546	   
df.mm.trans1:exp8	0.170506692440486	0.134984714513901	1.26315555842382	0.206794076043590	   
df.mm.trans2:exp8	0.048776681982721	0.0883682388459934	0.551970737673387	0.581077642137166	   
df.mm.trans1:probe2	0.129645006533489	0.103620945037772	1.25114672990322	0.211140143659116	   
df.mm.trans1:probe3	0.289426594162264	0.103620945037772	2.79312830100866	0.00530830158155603	** 
df.mm.trans1:probe4	0.0934354869315013	0.103620945037772	0.901704639901152	0.367406105600799	   
df.mm.trans1:probe5	0.112148975380663	0.103620945037772	1.08230025637946	0.279350235966126	   
df.mm.trans1:probe6	0.0559752854511409	0.103620945037772	0.540192771169349	0.589170635709542	   
df.mm.trans1:probe7	0.0882138321565215	0.103620945037772	0.85131275462085	0.394776166985026	   
df.mm.trans1:probe8	0.100222581840074	0.103620945037772	0.96720389689112	0.333649253550632	   
df.mm.trans1:probe9	0.0224938907668318	0.103620945037772	0.217078610493585	0.828186303853975	   
df.mm.trans1:probe10	0.100205376615203	0.103620945037772	0.967037856860656	0.333732211536041	   
df.mm.trans1:probe11	0.185989299993861	0.103620945037772	1.79490063448142	0.072936935953636	.  
df.mm.trans1:probe12	0.0357895770909809	0.103620945037772	0.345389410200175	0.729865977493047	   
df.mm.trans1:probe13	0.167390786008361	0.103620945037772	1.61541458579965	0.106500338854536	   
df.mm.trans1:probe14	0.209856832901019	0.103620945037772	2.0252356589155	0.0430780947101807	*  
df.mm.trans1:probe15	0.076264562847519	0.103620945037772	0.735995631189418	0.461886238448545	   
df.mm.trans1:probe16	0.234132665008945	0.103620945037772	2.25951099870396	0.0240416308170452	*  
df.mm.trans1:probe17	0.187157695633469	0.103620945037772	1.80617630504379	0.071157019902097	.  
df.mm.trans1:probe18	0.0229036225586790	0.103620945037772	0.221032751152097	0.82510689867983	   
df.mm.trans1:probe19	0.106158540256795	0.103620945037772	1.02448921130856	0.305823719981555	   
df.mm.trans1:probe20	0.125238142403093	0.103620945037772	1.20861802946731	0.227062696713433	   
df.mm.trans1:probe21	0.194148335011804	0.103620945037772	1.87363987986244	0.0612382319024891	.  
df.mm.trans1:probe22	0.215686906377664	0.103620945037772	2.08149912451620	0.0376131223970461	*  
df.mm.trans2:probe2	0.099472274413699	0.103620945037772	0.959963011121343	0.337279366735222	   
df.mm.trans2:probe3	0.0825456899192143	0.103620945037772	0.796612015930994	0.425843876221332	   
df.mm.trans2:probe4	0.0575900517199867	0.103620945037772	0.555776167636706	0.578473995876308	   
df.mm.trans2:probe5	0.126569399529710	0.103620945037772	1.22146540435018	0.222164850170923	   
df.mm.trans2:probe6	0.0912865728861177	0.103620945037772	0.88096641902698	0.378523494353131	   
df.mm.trans3:probe2	0.0943884876498884	0.103620945037772	0.91090162915887	0.362541645331350	   
df.mm.trans3:probe3	-0.061778462509303	0.103620945037772	-0.596196671307943	0.551163360348312	   
df.mm.trans3:probe4	0.084758247840039	0.103620945037772	0.817964435753242	0.413550089050054	   
df.mm.trans3:probe5	0.0686787795023346	0.103620945037772	0.662788584656314	0.507601250335682	   
df.mm.trans3:probe6	0.00887469812159297	0.103620945037772	0.0856457940849501	0.931763179115171	   
df.mm.trans3:probe7	0.135439263942468	0.103620945037772	1.30706455044487	0.191456935497247	   
df.mm.trans3:probe8	0.253754976800159	0.103620945037772	2.44887726808185	0.0144814646949233	*  
df.mm.trans3:probe9	0.216901314450917	0.103620945037772	2.09321884076479	0.0365523342208759	*  
df.mm.trans3:probe10	0.129122371513509	0.103620945037772	1.24610301002796	0.212985084865879	   
df.mm.trans3:probe11	0.0418939015513932	0.103620945037772	0.404299550984813	0.686069031270657	   
df.mm.trans3:probe12	0.148485290271269	0.103620945037772	1.43296599174176	0.152144395828575	   
df.mm.trans3:probe13	0.182530201963106	0.103620945037772	1.76151840630839	0.0784213374050363	.  
df.mm.trans3:probe14	0.164454141714881	0.103620945037772	1.58707432802252	0.112775820422987	   
df.mm.trans3:probe15	0.189123827083243	0.103620945037772	1.82515057177199	0.0682424205104599	.  
df.mm.trans3:probe16	0.216747289335217	0.103620945037772	2.09173241236324	0.0366854461961082	*  
df.mm.trans3:probe17	0.089850995847852	0.103620945037772	0.867112298725894	0.386064734008426	   
df.mm.trans3:probe18	0.0551247273757052	0.103620945037772	0.531984410638323	0.594841457031195	   
df.mm.trans3:probe19	0.0824020399691072	0.103620945037772	0.795225713672751	0.426649363456508	   
df.mm.trans3:probe20	0.05946710375326	0.103620945037772	0.573890768237859	0.566156027718032	   
df.mm.trans3:probe21	-0.0726629789959859	0.103620945037772	-0.701238335256435	0.483298797501052	   
df.mm.trans3:probe22	-0.00152168548229860	0.103620945037772	-0.0146851148842921	0.988285989230406