chr6.19925_chr6_48750710_48752381_+_2.R 

fitVsDatCorrelation=0.934940106876992
cont.fitVsDatCorrelation=0.283990347992652

fstatistic=8908.61047296028,60,876
cont.fstatistic=1207.25979079933,60,876

residuals=-0.757774295314638,-0.0923591998718766,-0.00933879296064475,0.084638773203353,0.967101075568616
cont.residuals=-0.887586106133518,-0.333209922020397,-0.111577782278985,0.181053151574533,1.66962337119968

predictedValues:
Include	Exclude	Both
chr6.19925_chr6_48750710_48752381_+_2.R.tl.Lung	72.6965088011869	169.637562994360	63.440290431069
chr6.19925_chr6_48750710_48752381_+_2.R.tl.cerebhem	70.6799566556777	107.704399049218	65.7994271743523
chr6.19925_chr6_48750710_48752381_+_2.R.tl.cortex	68.5135509671303	134.71813580824	66.4008997581682
chr6.19925_chr6_48750710_48752381_+_2.R.tl.heart	67.6928109481078	158.545969577260	60.481177053024
chr6.19925_chr6_48750710_48752381_+_2.R.tl.kidney	72.6801285578406	191.276053198795	57.2852687806388
chr6.19925_chr6_48750710_48752381_+_2.R.tl.liver	69.2411375425708	233.123747920969	54.1468187440049
chr6.19925_chr6_48750710_48752381_+_2.R.tl.stomach	68.361707521946	198.906888875589	56.5472792187957
chr6.19925_chr6_48750710_48752381_+_2.R.tl.testicle	70.969344672191	269.020984937319	58.8293857635012


diffExp=-96.9410541931729,-37.0244423935401,-66.2045848411096,-90.8531586291527,-118.595924640954,-163.882610378398,-130.545181353643,-198.051640265128
diffExpScore=0.998892701191587
diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.888888888888889
diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.4Score=0.888888888888889
diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.3Score=0.888888888888889
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	86.5279711696253	70.1219691985065	64.5337136854978
cerebhem	78.7607415398497	84.1460478950342	106.088956101125
cortex	84.5138045146982	99.221979930111	107.425345804036
heart	80.7022195746616	59.529517975293	78.4314620102584
kidney	75.6865023193721	77.4889543747542	73.8889228021087
liver	88.5741332642352	72.6009553025798	72.4362254022504
stomach	83.4410646042126	84.6698603359202	70.6993128862544
testicle	80.8467435855216	83.0559237304786	94.2918673388213
cont.diffExp=16.4060019711188,-5.38530635518453,-14.7081754154128,21.1727015993686,-1.80245205538210,15.9731779616554,-1.22879573170766,-2.20918014495696
cont.diffExpScore=2.69990647178128

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=0,0,0,1,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=1,0,0,1,0,1,0,0
cont.diffExp1.2Score=0.75

tran.correlation=0.116152898413547
cont.tran.correlation=-0.0267389833705543

tran.covariance=0.000869527578755964
cont.tran.covariance=-0.000241351057447593

tran.mean=126.485555501775
cont.tran.mean=80.6180243321784

weightedLogRatios:
wLogRatio
Lung	-3.99109856014555
cerebhem	-1.88237543745275
cortex	-3.086712301741
heart	-3.94937570938106
kidney	-4.61558527622734
liver	-5.8811982015676
stomach	-5.08253905132031
testicle	-6.56745505899138

cont.weightedLogRatios:
wLogRatio
Lung	0.915632540018736
cerebhem	-0.290978749479296
cortex	-0.724750607490093
heart	1.28978549159691
kidney	-0.102105921662607
liver	0.871891395329181
stomach	-0.0647839394431713
testicle	-0.118781641913142

varWeightedLogRatios=2.26214099702831
cont.varWeightedLogRatios=0.500936642194306

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.14933666630517	0.0936726737429619	54.9715990859295	3.3096962238781e-286	***
df.mm.trans1	-0.872523244627973	0.0837002655646394	-10.4243784501992	4.58330399438425e-24	***
df.mm.trans2	-0.181317061669743	0.0754141697243754	-2.40428373517102	0.0164108922849934	*  
df.mm.exp2	-0.518917054596957	0.101417207619955	-5.11665689457275	3.82255092679263e-07	***
df.mm.exp3	-0.33535272884317	0.101417207619955	-3.30666498036361	0.000982550084486665	***
df.mm.exp4	-0.0911660137373133	0.101417207619955	-0.898920566605855	0.368941989663206	   
df.mm.exp5	0.221883815537478	0.101417207619955	2.18783203309002	0.0289454235867420	*  
df.mm.exp6	0.427606971134226	0.101417207619955	4.21631576306673	2.74124573599449e-05	***
df.mm.exp7	0.212714183091509	0.101417207619955	2.09741707628771	0.036242748129383	*  
df.mm.exp8	0.512537533362827	0.101417207619955	5.05375315876851	5.27421471706901e-07	***
df.mm.trans1:exp2	0.490785727406467	0.0974643573658277	5.035540588077	5.78565083265377e-07	***
df.mm.trans2:exp2	0.0646433045674668	0.0805340277071467	0.802683119271461	0.422375627380478	   
df.mm.trans1:exp3	0.27609091748991	0.0974643573658277	2.8327372688009	0.00472103894836907	** 
df.mm.trans2:exp3	0.104873262959216	0.0805340277071467	1.30222299747104	0.193182445664412	   
df.mm.trans1:exp4	0.0198526367866224	0.0974643573658277	0.203691250044429	0.838642087815144	   
df.mm.trans2:exp4	0.0235464151286982	0.0805340277071467	0.292378461615284	0.770066507733473	   
df.mm.trans1:exp5	-0.222109164585484	0.0974643573658277	-2.27887579201705	0.0229143244563509	*  
df.mm.trans2:exp5	-0.101830304987004	0.0805340277071467	-1.2644382491001	0.206409080989403	   
df.mm.trans1:exp6	-0.476305173375689	0.0974643573658277	-4.88696777210463	1.21754784547289e-06	***
df.mm.trans2:exp6	-0.109701730353282	0.0805340277071467	-1.36217861538231	0.173491668651498	   
df.mm.trans1:exp7	-0.274194708172147	0.0974643573658277	-2.81328185587856	0.00501361032802549	** 
df.mm.trans2:exp7	-0.0535415417159469	0.0805340277071467	-0.6648312923159	0.506333383320861	   
df.mm.trans1:exp8	-0.536582876133797	0.0974643573658277	-5.50542670814275	4.83909436792118e-08	***
df.mm.trans2:exp8	-0.0514123246386014	0.0805340277071467	-0.63839256650067	0.523385024182087	   
df.mm.trans1:probe2	0.0423470580368641	0.0533834270820086	0.79326226043543	0.427839841526901	   
df.mm.trans1:probe3	0.154238528527979	0.0533834270820086	2.88925865121088	0.00395675672522419	** 
df.mm.trans1:probe4	-0.104705838685075	0.0533834270820086	-1.96139222242559	0.0501496827227683	.  
df.mm.trans1:probe5	-0.332026718947936	0.0533834270820086	-6.21965911701155	7.70736500778832e-10	***
df.mm.trans1:probe6	-0.358593780923041	0.0533834270820086	-6.71732409334011	3.32809829241182e-11	***
df.mm.trans1:probe7	-0.399572346113706	0.0533834270820086	-7.48495119093563	1.74301400201118e-13	***
df.mm.trans1:probe8	-0.0469827521067762	0.0533834270820086	-0.88009996125952	0.379046535419882	   
df.mm.trans1:probe9	-0.220669600307891	0.0533834270820086	-4.13367242175917	3.91307843864893e-05	***
df.mm.trans1:probe10	0.934464693327314	0.0533834270820086	17.504771506928	4.63055708339175e-59	***
df.mm.trans1:probe11	0.0761682959518797	0.0533834270820086	1.42681540162022	0.153989425067954	   
df.mm.trans1:probe12	0.0514069476129362	0.0533834270820086	0.96297578523694	0.335825416852025	   
df.mm.trans1:probe13	0.268723264813153	0.0533834270820086	5.03383314826032	5.83598201352578e-07	***
df.mm.trans1:probe14	0.00530315324038377	0.0533834270820086	0.0993408166215513	0.920890399799703	   
df.mm.trans1:probe15	0.207654906844303	0.0533834270820086	3.8898759070919	0.000107888298333800	***
df.mm.trans1:probe16	-0.0760593700932425	0.0533834270820086	-1.42477495827307	0.154578420534516	   
df.mm.trans1:probe17	0.344988177936602	0.0533834270820086	6.46245842191107	1.70787247909977e-10	***
df.mm.trans1:probe18	0.164460853427087	0.0533834270820086	3.08074738578396	0.00212932306077259	** 
df.mm.trans1:probe19	0.212899529155335	0.0533834270820086	3.98812029861393	7.21559818873079e-05	***
df.mm.trans1:probe20	0.0696091238849813	0.0533834270820086	1.30394633109722	0.192594415694538	   
df.mm.trans1:probe21	0.193880341281972	0.0533834270820086	3.63184516018669	0.000297746451196093	***
df.mm.trans1:probe22	0.104032163963508	0.0533834270820086	1.94877267440496	0.0516415011902149	.  
df.mm.trans1:probe23	-0.277925804242785	0.0533834270820086	-5.20621884795501	2.40262190635415e-07	***
df.mm.trans1:probe24	0.186548571826319	0.0533834270820086	3.49450348213388	0.000498756085893215	***
df.mm.trans1:probe25	-0.118923130677662	0.0533834270820086	-2.22771630032238	0.0261527268728774	*  
df.mm.trans1:probe26	-0.341745594213858	0.0533834270820086	-6.401717028936	2.5016023505298e-10	***
df.mm.trans1:probe27	0.0462158533754349	0.0533834270820086	0.865734103290845	0.386873027861852	   
df.mm.trans1:probe28	-0.148472713379266	0.0533834270820086	-2.78125106413979	0.0055312283271007	** 
df.mm.trans1:probe29	-0.324425802845371	0.0533834270820086	-6.07727567484533	1.82198012070901e-09	***
df.mm.trans2:probe2	0.637755346731954	0.0533834270820086	11.9466917279818	1.38834909486081e-30	***
df.mm.trans2:probe3	0.284092796017727	0.0533834270820086	5.32174143824259	1.30627520862507e-07	***
df.mm.trans2:probe4	0.226640101896550	0.0533834270820086	4.24551427821187	2.41379728638196e-05	***
df.mm.trans2:probe5	0.121753053603541	0.0533834270820086	2.28072756394043	0.0228039591833431	*  
df.mm.trans2:probe6	0.386204442939157	0.0533834270820086	7.23453820875648	1.01974513757231e-12	***
df.mm.trans3:probe2	-0.170192540348238	0.0533834270820086	-3.18811566905932	0.00148284868810285	** 
df.mm.trans3:probe3	0.360158298560107	0.0533834270820086	6.74663127203927	2.7479218420541e-11	***
df.mm.trans3:probe4	0.0284454231960925	0.0533834270820086	0.532851200287201	0.594271729883901	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.61281593056613	0.253141179015937	18.2223056260464	3.74054577962299e-63	***
df.mm.trans1	-0.0245277259601086	0.226191727665634	-0.108437767434035	0.913673276006907	   
df.mm.trans2	-0.413490538509605	0.203799369396891	-2.02890980346631	0.0427694718369132	*  
df.mm.exp2	-0.408825417901726	0.274070019393978	-1.49168237666315	0.136142444923562	   
df.mm.exp3	-0.186037789670355	0.274070019393978	-0.678796572064762	0.49744605364851	   
df.mm.exp4	-0.42850286979603	0.274070019393978	-1.56347954710089	0.118301004124404	   
df.mm.exp5	-0.169343771309677	0.274070019393978	-0.617885063401422	0.53681170137058	   
df.mm.exp6	-0.0574046702324325	0.274070019393978	-0.209452571132608	0.834143655664953	   
df.mm.exp7	0.0609483228719254	0.274070019393978	0.222382305830802	0.824068121477775	   
df.mm.exp8	-0.277841565387739	0.274070019393978	-1.0137612497788	0.310976605920155	   
df.mm.trans1:exp2	0.314772359022680	0.263387830727635	1.19509074566236	0.232375019429063	   
df.mm.trans2:exp2	0.591143229509883	0.217635281561726	2.7162104658211	0.00673350698692015	** 
df.mm.trans1:exp3	0.162484949939278	0.263387830727635	0.616903785912953	0.537458486744049	   
df.mm.trans2:exp3	0.533161208370677	0.217635281561726	2.44979216855269	0.0144886553062008	*  
df.mm.trans1:exp4	0.358801220927659	0.263387830727635	1.36225436056190	0.173467779977204	   
df.mm.trans2:exp4	0.264739016832373	0.217635281561726	1.21643427909591	0.224147187617726	   
df.mm.trans1:exp5	0.0354758831697509	0.263387830727635	0.134690669161689	0.892887390827159	   
df.mm.trans2:exp5	0.269243030391518	0.217635281561726	1.23712951530404	0.216370532382249	   
df.mm.trans1:exp6	0.0807768078151712	0.263387830727635	0.306683902563065	0.759156864827616	   
df.mm.trans2:exp6	0.092146607491147	0.217635281561726	0.42339921555877	0.672107946615425	   
df.mm.trans1:exp7	-0.0972754811307815	0.263387830727635	-0.369324128840912	0.711975396477947	   
df.mm.trans2:exp7	0.127575232346894	0.217635281561726	0.586188192610264	0.557900059804093	   
df.mm.trans1:exp8	0.209929145575238	0.263387830727635	0.79703433904022	0.425647057202548	   
df.mm.trans2:exp8	0.447119583258661	0.217635281561726	2.05444438994533	0.0402288988037746	*  
df.mm.trans1:probe2	-0.116241177300448	0.144263456261878	-0.805756220684456	0.420602090014935	   
df.mm.trans1:probe3	-0.284078297015817	0.144263456261878	-1.96916325434583	0.0492491599027009	*  
df.mm.trans1:probe4	-0.259257317053650	0.144263456261878	-1.79711011902437	0.0726624844940929	.  
df.mm.trans1:probe5	-0.210204267238400	0.144263456261878	-1.45708603332517	0.145450987679509	   
df.mm.trans1:probe6	-0.322957862881647	0.144263456261878	-2.23866716665507	0.0254280129463524	*  
df.mm.trans1:probe7	-0.0190097131294575	0.144263456261878	-0.131770814467037	0.895195829752572	   
df.mm.trans1:probe8	-0.254747875345750	0.144263456261878	-1.76585174060513	0.0777690199489202	.  
df.mm.trans1:probe9	-0.048579421050189	0.144263456261878	-0.336741003639923	0.73639280503503	   
df.mm.trans1:probe10	-0.0943003225086947	0.144263456261878	-0.65366742869042	0.513497633840402	   
df.mm.trans1:probe11	-0.193963054554333	0.144263456261878	-1.34450580611514	0.179132917644210	   
df.mm.trans1:probe12	-0.310298101908746	0.144263456261878	-2.15091271170898	0.0317560246857900	*  
df.mm.trans1:probe13	-0.171413064656255	0.144263456261878	-1.18819463430221	0.235078771921224	   
df.mm.trans1:probe14	-0.127676760959144	0.144263456261878	-0.885024969368369	0.376386021353114	   
df.mm.trans1:probe15	0.0753807737937184	0.144263456261878	0.522521612520371	0.601439317701503	   
df.mm.trans1:probe16	-0.0338567289019587	0.144263456261878	-0.234686799964777	0.814506677156131	   
df.mm.trans1:probe17	-0.213522131002826	0.144263456261878	-1.48008467657411	0.139210187980457	   
df.mm.trans1:probe18	-0.259555021933649	0.144263456261878	-1.79917373851411	0.0723352695334726	.  
df.mm.trans1:probe19	-0.2462427996273	0.144263456261878	-1.70689657663755	0.0881956622904815	.  
df.mm.trans1:probe20	0.0152449376346624	0.144263456261878	0.105674285295013	0.915864975951204	   
df.mm.trans1:probe21	-0.0789982000482407	0.144263456261878	-0.547596751770852	0.584108309165583	   
df.mm.trans1:probe22	-0.0247280113307873	0.144263456261878	-0.171408698859253	0.863942001302507	   
df.mm.trans1:probe23	0.0577651142305402	0.144263456261878	0.400414046130162	0.688949209883134	   
df.mm.trans1:probe24	-0.356669376306188	0.144263456261878	-2.47234736743541	0.0136118416740797	*  
df.mm.trans1:probe25	-0.127033823002856	0.144263456261878	-0.88056827622551	0.378793051748967	   
df.mm.trans1:probe26	-0.208914456580281	0.144263456261878	-1.44814537231830	0.147934207423618	   
df.mm.trans1:probe27	-0.105762441211274	0.144263456261878	-0.733120111993478	0.463681307183955	   
df.mm.trans1:probe28	-0.0856430308948533	0.144263456261878	-0.593657140304386	0.552894709276675	   
df.mm.trans1:probe29	-0.212813304174303	0.144263456261878	-1.47517125742494	0.140525818288658	   
df.mm.trans2:probe2	0.0487760895030343	0.144263456261878	0.338104262624155	0.735365629293904	   
df.mm.trans2:probe3	0.00308416839685111	0.144263456261878	0.0213787224898625	0.982948415176832	   
df.mm.trans2:probe4	0.171844774746623	0.144263456261878	1.19118714606891	0.233902772703074	   
df.mm.trans2:probe5	0.183744333522206	0.144263456261878	1.27367206001678	0.203117500941131	   
df.mm.trans2:probe6	0.101658142498025	0.144263456261878	0.704670088546107	0.481202868631538	   
df.mm.trans3:probe2	0.0810488666359775	0.144263456261878	0.561811485292931	0.574388174026973	   
df.mm.trans3:probe3	0.0790551082778299	0.144263456261878	0.547991226096254	0.58383753297118	   
df.mm.trans3:probe4	-0.190543519124112	0.144263456261878	-1.32080239903738	0.186912191867531