chr15.8576_chr15_82775583_82780787_+_2.R 

fitVsDatCorrelation=0.841562908075418
cont.fitVsDatCorrelation=0.208950239561448

fstatistic=10559.1975717113,62,922
cont.fstatistic=3211.19551847508,62,922

residuals=-0.730137261014385,-0.0850892536600923,-0.00903636298661877,0.0732716036471237,1.13623650696307
cont.residuals=-0.535636424555397,-0.184179772525690,-0.0456525316966941,0.111284303586220,1.56916571421232

predictedValues:
Include	Exclude	Both
chr15.8576_chr15_82775583_82780787_+_2.R.tl.Lung	52.5816341789311	56.6891228408542	64.019482634667
chr15.8576_chr15_82775583_82780787_+_2.R.tl.cerebhem	55.2095000318485	69.6075400862842	66.6035728261525
chr15.8576_chr15_82775583_82780787_+_2.R.tl.cortex	55.6004794468291	52.8936297632829	60.9364258713075
chr15.8576_chr15_82775583_82780787_+_2.R.tl.heart	59.9071744038892	53.7972192983937	60.2247913050816
chr15.8576_chr15_82775583_82780787_+_2.R.tl.kidney	55.8515631435775	54.4424920735341	66.468100886089
chr15.8576_chr15_82775583_82780787_+_2.R.tl.liver	56.1921452606738	52.6966706270106	63.4765640584417
chr15.8576_chr15_82775583_82780787_+_2.R.tl.stomach	56.2022338319204	55.2782591726386	61.3664514177315
chr15.8576_chr15_82775583_82780787_+_2.R.tl.testicle	56.0855070377046	57.4508694589282	59.611661883398


diffExp=-4.10748866192314,-14.3980400544357,2.70684968354614,6.1099551054955,1.40907107004341,3.49547463366319,0.923974659281797,-1.3653624212236
diffExpScore=5.54426960853259
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,-1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	64.5999403342483	65.3352876967016	62.7797556829977
cerebhem	63.773768377541	61.7322157961503	59.9569685997956
cortex	63.5830815869038	58.9813191622461	56.1150053932943
heart	64.6107054886245	57.4722382901996	61.5140204510067
kidney	63.0297568744755	58.1597806378241	59.4675145280353
liver	64.9436494106685	61.3513309822965	58.0839170108511
stomach	62.3845237894914	63.266962139696	60.9294705464553
testicle	60.1038733708363	62.5536410623794	59.9924864054203
cont.diffExp=-0.735347362453297,2.04155258139067,4.60176242465766,7.13846719842484,4.86997623665143,3.59231842837197,-0.882438350204666,-2.44976769154309
cont.diffExpScore=1.37207509595338

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=-0.268506535100833
cont.tran.correlation=-0.165784475259958

tran.covariance=-0.000889216816843586
cont.tran.covariance=-0.000196667227049512

tran.mean=56.2803775410188
cont.tran.mean=62.2426296875177

weightedLogRatios:
wLogRatio
Lung	-0.300859918085437
cerebhem	-0.956383049430202
cortex	0.199298136795526
heart	0.434494340220751
kidney	0.102463753385128
liver	0.256684608838736
stomach	0.0666498757598629
testicle	-0.0971465443172231

cont.weightedLogRatios:
wLogRatio
Lung	-0.0472432185188878
cerebhem	0.134668997174168
cortex	0.309129955999824
heart	0.481172374596188
kidney	0.329966271606576
liver	0.235867225563442
stomach	-0.0581553820732076
testicle	-0.164436820149741

varWeightedLogRatios=0.187584640202730
cont.varWeightedLogRatios=0.0508632376137605

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.62761037929479	0.0729307769026853	49.7404598354309	2.79405198167183e-263	***
df.mm.trans1	0.188332936474524	0.0626350558245475	3.00682954609444	0.00271147709981903	** 
df.mm.trans2	0.421142775641433	0.0549976155068667	7.65747336061964	4.78283669329768e-14	***
df.mm.exp2	0.214487913617087	0.069977437755158	3.06510098822927	0.00223931846486797	** 
df.mm.exp3	0.0358818129633997	0.069977437755158	0.512762600553417	0.608240215899408	   
df.mm.exp4	0.139172166872327	0.069977437755158	1.98881484285367	0.0470168534361749	*  
df.mm.exp5	-0.0176414808146298	0.069977437755158	-0.252102411585218	0.801018091399204	   
df.mm.exp6	0.00189669206636224	0.069977437755158	0.0271043371579068	0.97838238075529	   
df.mm.exp7	0.0837110991221225	0.069977437755158	1.19625841996412	0.231903263587165	   
df.mm.exp8	0.149194551044718	0.069977437755158	2.13203792294783	0.033267497600794	*  
df.mm.trans1:exp2	-0.165719771792369	0.0642399714499367	-2.57969871486505	0.0100424514872171	*  
df.mm.trans2:exp2	-0.00919737288009	0.0455330608553079	-0.201993292507105	0.83996652669069	   
df.mm.trans1:exp3	0.0199431127236481	0.0642399714499367	0.310447098177653	0.756291145433695	   
df.mm.trans2:exp3	-0.105181257012739	0.0455330608553079	-2.30999750592164	0.0211083643500091	*  
df.mm.trans1:exp4	-0.00874279458000242	0.0642399714499367	-0.136095866524720	0.891775203802964	   
df.mm.trans2:exp4	-0.191532742252475	0.0455330608553079	-4.20645435766149	2.84731334551906e-05	***
df.mm.trans1:exp5	0.077972095508145	0.0642399714499368	1.21376292280749	0.225149091703596	   
df.mm.trans2:exp5	-0.0227959212424221	0.0455330608553079	-0.500645482957132	0.616740131588636	   
df.mm.trans1:exp6	0.064513392343711	0.0642399714499367	1.00425624245471	0.315518603231632	   
df.mm.trans2:exp6	-0.074926769781445	0.0455330608553079	-1.64554651881503	0.100197987741696	   
df.mm.trans1:exp7	-0.0171214937901806	0.0642399714499367	-0.26652399438757	0.789895276545258	   
df.mm.trans2:exp7	-0.108913766555525	0.0455330608553079	-2.39197111965798	0.0169576116761627	*  
df.mm.trans1:exp8	-0.0846840121426108	0.0642399714499367	-1.31824485956701	0.187749084688543	   
df.mm.trans2:exp8	-0.135846767988134	0.0455330608553079	-2.98347542283221	0.00292505785052655	** 
df.mm.trans1:probe2	-0.112386748418466	0.0460183292063378	-2.44221705474234	0.0147842874460894	*  
df.mm.trans1:probe3	-0.0451930978559282	0.0460183292063378	-0.982067333502932	0.326324302007148	   
df.mm.trans1:probe4	0.125861926117179	0.0460183292063378	2.73503902223040	0.00635698241571543	** 
df.mm.trans1:probe5	0.053101240764077	0.0460183292063378	1.15391500908216	0.248834034993849	   
df.mm.trans1:probe6	0.108482237417012	0.0460183292063378	2.35737018896531	0.0186130332535906	*  
df.mm.trans1:probe7	0.974723433699472	0.0460183292063378	21.1811999807509	1.90459229335481e-81	***
df.mm.trans1:probe8	0.104190661447052	0.0460183292063378	2.26411221884829	0.0237987978465180	*  
df.mm.trans1:probe9	0.994815707385252	0.0460183292063378	21.6178145652503	3.65424561529222e-84	***
df.mm.trans1:probe10	0.160812057748356	0.0460183292063378	3.49452186817353	0.00049751672633077	***
df.mm.trans1:probe11	0.346159941346324	0.0460183292063378	7.52221880534182	1.27741929276913e-13	***
df.mm.trans1:probe12	0.536019782436318	0.0460183292063378	11.6479627070532	2.38128393854236e-29	***
df.mm.trans1:probe13	0.191204877187516	0.0460183292063378	4.15497217054944	3.55576888807058e-05	***
df.mm.trans1:probe14	0.369623870370469	0.0460183292063378	8.03210105071706	2.91358204190692e-15	***
df.mm.trans1:probe15	0.174470351041959	0.0460183292063378	3.79132302391219	0.000159592810318753	***
df.mm.trans1:probe16	0.140398904590385	0.0460183292063378	3.0509344213881	0.00234659578168272	** 
df.mm.trans1:probe17	0.040836858981978	0.0460183292063378	0.88740420798141	0.375092741017077	   
df.mm.trans1:probe18	0.0634104161807825	0.0460183292063378	1.37793825361329	0.168556676770163	   
df.mm.trans1:probe19	0.312634581455460	0.0460183292063378	6.79369692136504	1.95836309124086e-11	***
df.mm.trans1:probe20	0.261895000030704	0.0460183292063378	5.69110188369541	1.69531913063152e-08	***
df.mm.trans1:probe21	0.097061987911863	0.0460183292063378	2.10920278041071	0.0351961689452115	*  
df.mm.trans1:probe22	0.226701411921321	0.0460183292063378	4.92632861364509	9.92895852477729e-07	***
df.mm.trans2:probe2	0.150966000688099	0.0460183292063378	3.28056240397592	0.00107485391005510	** 
df.mm.trans2:probe3	0.00452661534559247	0.0460183292063378	0.0983654866150389	0.921663459710187	   
df.mm.trans2:probe4	-0.155894521512152	0.0460183292063378	-3.38766148621237	0.000734742662073062	***
df.mm.trans2:probe5	-0.0490405218238201	0.0460183292063378	-1.06567367111334	0.286850166490093	   
df.mm.trans2:probe6	-0.162802765621435	0.0460183292063378	-3.53778088925083	0.000423630783519351	***
df.mm.trans3:probe2	-0.124509244459248	0.0460183292063378	-2.70564461175832	0.00694301075600392	** 
df.mm.trans3:probe3	0.302323484963419	0.0460183292063378	6.56963193096073	8.42081680632837e-11	***
df.mm.trans3:probe4	0.130215927651290	0.0460183292063378	2.82965352930190	0.00476101327286095	** 
df.mm.trans3:probe5	0.153964883953267	0.0460183292063378	3.34572955186870	0.000853800077464165	***
df.mm.trans3:probe6	-0.193309035066218	0.0460183292063378	-4.20069651376207	2.91930341020134e-05	***
df.mm.trans3:probe7	-0.299629530128815	0.0460183292063378	-6.51109102169553	1.22409531634180e-10	***
df.mm.trans3:probe8	-0.167176256324131	0.0460183292063378	-3.63281890514849	0.000295813826046099	***
df.mm.trans3:probe9	-0.260865582099666	0.0460183292063378	-5.66873214648869	1.92365340221916e-08	***
df.mm.trans3:probe10	-0.166178488577811	0.0460183292063378	-3.61113694138475	0.000321301781951115	***
df.mm.trans3:probe11	0.0725899096679004	0.0460183292063378	1.57741297695578	0.115043548992677	   
df.mm.trans3:probe12	-0.326470763779441	0.0460183292063378	-7.09436368964214	2.58866299058295e-12	***
df.mm.trans3:probe13	-0.133637602525410	0.0460183292063378	-2.90400813828340	0.00377211899916701	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.32826463659108	0.132036877029479	32.7807256121692	7.2905641515792e-157	***
df.mm.trans1	-0.0971357542309226	0.113397080284439	-0.856598370851105	0.391889461533809	   
df.mm.trans2	-0.147281135445391	0.0995699443224682	-1.47917262028795	0.139435750168525	   
df.mm.exp2	-0.0235923435831840	0.126690030411230	-0.186220995500628	0.852312422962173	   
df.mm.exp3	-0.00594817224584619	0.126690030411230	-0.0469505945064399	0.962562771315206	   
df.mm.exp4	-0.107696099319992	0.126690030411230	-0.85007556609163	0.395503762452516	   
df.mm.exp5	-0.086742292640131	0.126690030411230	-0.6846812835909	0.493717135187222	   
df.mm.exp6	0.0201349064433075	0.126690030411230	0.158930472886861	0.873758457196753	   
df.mm.exp7	-0.0371495897289685	0.126690030411230	-0.293232147852382	0.769410698856192	   
df.mm.exp8	-0.0702337051663349	0.126690030411230	-0.554374365041666	0.579457105159626	   
df.mm.trans1:exp2	0.0107208082602441	0.116302685518221	0.0921802296522589	0.926574869902565	   
df.mm.trans2:exp2	-0.0331340095308807	0.0824349254492408	-0.401941402267452	0.68782030619102	   
df.mm.trans1:exp3	-0.00991789274996892	0.116302685518221	-0.085276558368165	0.932060040792924	   
df.mm.trans2:exp3	-0.0963633421932487	0.0824349254492407	-1.16896256857276	0.242720846299576	   
df.mm.trans1:exp4	0.107862728847032	0.116302685518221	0.927431111039422	0.353945453852753	   
df.mm.trans2:exp4	-0.0205341656524934	0.0824349254492407	-0.249095459728866	0.803342419802741	   
df.mm.trans1:exp5	0.062135751689527	0.116302685518221	0.534258958962665	0.593291176233817	   
df.mm.trans2:exp5	-0.0295959296835304	0.0824349254492407	-0.359021731653704	0.719661031600022	   
df.mm.trans1:exp6	-0.0148284318639151	0.116302685518221	-0.127498619639286	0.898573567130819	   
df.mm.trans2:exp6	-0.083050324458786	0.0824349254492408	-1.00746527040804	0.313975559936895	   
df.mm.trans1:exp7	0.00225333097951630	0.116302685518221	0.019374711507958	0.98454637577709	   
df.mm.trans2:exp7	0.00498057366545972	0.0824349254492408	0.0604182467360452	0.951835619674817	   
df.mm.trans1:exp8	-0.00190549377292311	0.116302685518221	-0.0163839189476376	0.98693165344239	   
df.mm.trans2:exp8	0.0267258669747947	0.0824349254492407	0.324205630430892	0.745855893395635	   
df.mm.trans1:probe2	-0.0850777442906126	0.0833134752235936	-1.02117627505375	0.307438795107038	   
df.mm.trans1:probe3	-0.0199679690273339	0.0833134752235936	-0.239672741699282	0.810637238927552	   
df.mm.trans1:probe4	-0.159487737909114	0.0833134752235936	-1.91430902961479	0.0558899641064213	.  
df.mm.trans1:probe5	-0.100670215764709	0.0833134752235936	-1.20833053109997	0.227229966524280	   
df.mm.trans1:probe6	-0.0570024582390264	0.0833134752235936	-0.684192540114853	0.494025521672275	   
df.mm.trans1:probe7	-0.14634031082343	0.0833134752235936	-1.75650229966626	0.0793346283540651	.  
df.mm.trans1:probe8	-0.00797696840370761	0.0833134752235936	-0.0957464369635202	0.92374276475248	   
df.mm.trans1:probe9	-0.170246189003258	0.0833134752235936	-2.04344121459773	0.0412925852897301	*  
df.mm.trans1:probe10	-0.0944412895741508	0.0833134752235936	-1.13356560053092	0.257271470560937	   
df.mm.trans1:probe11	-0.103180152299292	0.0833134752235936	-1.23845694855941	0.215861897887211	   
df.mm.trans1:probe12	-0.0565208070064477	0.0833134752235936	-0.678411347681264	0.497681147459283	   
df.mm.trans1:probe13	-0.119209220220118	0.0833134752235936	-1.43085161074110	0.152811578117088	   
df.mm.trans1:probe14	-0.137542488181195	0.0833134752235936	-1.65090326399258	0.0990988790334675	.  
df.mm.trans1:probe15	-0.0691866622857285	0.0833134752235936	-0.830437838537498	0.406506257715071	   
df.mm.trans1:probe16	-0.143829792461931	0.0833134752235936	-1.72636889861965	0.0846160526315538	.  
df.mm.trans1:probe17	-0.175566994444355	0.0833134752235936	-2.10730609872143	0.0353605793526859	*  
df.mm.trans1:probe18	-0.082991625123503	0.0833134752235936	-0.99613687822736	0.319444998331105	   
df.mm.trans1:probe19	-0.138158557142871	0.0833134752235936	-1.65829785364355	0.0975974995307671	.  
df.mm.trans1:probe20	-0.0882339567802136	0.0833134752235936	-1.05905985248382	0.289849892003299	   
df.mm.trans1:probe21	-0.118203091313181	0.0833134752235936	-1.41877518607826	0.156302509134392	   
df.mm.trans1:probe22	-0.128204601372386	0.0833134752235936	-1.53882191360179	0.124190881228461	   
df.mm.trans2:probe2	0.0231120338265306	0.0833134752235936	0.277410512099074	0.781527097382191	   
df.mm.trans2:probe3	-0.00834057464500612	0.0833134752235936	-0.100110751863633	0.920278162783056	   
df.mm.trans2:probe4	0.00507857523456435	0.0833134752235936	0.0609574288065005	0.951406323402616	   
df.mm.trans2:probe5	0.00819962713367251	0.0833134752235936	0.0984189785825961	0.92162099712813	   
df.mm.trans2:probe6	-0.0556227903573345	0.0833134752235936	-0.66763257934033	0.504535226204798	   
df.mm.trans3:probe2	0.0490605008976394	0.0833134752235936	0.58886633603955	0.55609517959379	   
df.mm.trans3:probe3	0.0488067115114065	0.0833134752235936	0.585820137503817	0.558139756455431	   
df.mm.trans3:probe4	0.222729522878747	0.0833134752235936	2.67339133652742	0.00764157851389235	** 
df.mm.trans3:probe5	0.00551964755278544	0.0833134752235936	0.0662515582019837	0.947191912061447	   
df.mm.trans3:probe6	0.0309699436032458	0.0833134752235936	0.371727905001320	0.710180857379002	   
df.mm.trans3:probe7	0.0563808846527544	0.0833134752235936	0.676731879224117	0.498745824346413	   
df.mm.trans3:probe8	0.0557875839457251	0.0833134752235936	0.669610573751778	0.50327372151792	   
df.mm.trans3:probe9	0.0813738993399036	0.0833134752235936	0.976719541724977	0.328964211996646	   
df.mm.trans3:probe10	0.123485037097486	0.0833134752235936	1.48217364317214	0.138635788609846	   
df.mm.trans3:probe11	-0.0425228368906118	0.0833134752235936	-0.510395668605716	0.609896459192804	   
df.mm.trans3:probe12	0.0612861639252806	0.0833134752235936	0.73560926081649	0.462155609384386	   
df.mm.trans3:probe13	0.0323268085872143	0.0833134752235936	0.388014165781188	0.698095116868557