chr15.8395_chr15_85934786_85938552_+_2.R 

fitVsDatCorrelation=0.84301388542738
cont.fitVsDatCorrelation=0.260584319471702

fstatistic=4749.28440301292,53,715
cont.fstatistic=1464.90058241977,53,715

residuals=-0.932902355823827,-0.106649864652143,-0.0104334371326778,0.0812897036834606,1.69040776705598
cont.residuals=-0.709074377899266,-0.296003803925760,-0.058415083202421,0.235059818034819,2.44591711943367

predictedValues:
Include	Exclude	Both
chr15.8395_chr15_85934786_85938552_+_2.R.tl.Lung	69.2320679283937	60.4575155765381	70.0472309158702
chr15.8395_chr15_85934786_85938552_+_2.R.tl.cerebhem	85.4747097655261	116.312090003825	57.5941852227373
chr15.8395_chr15_85934786_85938552_+_2.R.tl.cortex	60.6823707022268	54.4825628318059	60.4426680313615
chr15.8395_chr15_85934786_85938552_+_2.R.tl.heart	64.724268768309	57.0410958037007	61.8254815042683
chr15.8395_chr15_85934786_85938552_+_2.R.tl.kidney	66.0789733366606	53.7662009037523	73.1593452712906
chr15.8395_chr15_85934786_85938552_+_2.R.tl.liver	67.296303131355	57.2988220021355	66.9198571556156
chr15.8395_chr15_85934786_85938552_+_2.R.tl.stomach	72.0113879446693	63.272145133365	60.752356571543
chr15.8395_chr15_85934786_85938552_+_2.R.tl.testicle	68.3061849337779	64.2559772344922	58.0559806408663


diffExp=8.77455235185553,-30.8373802382984,6.19980787042092,7.68317296460828,12.3127724329083,9.99748112921947,8.73924281130432,4.05020769928566
diffExpScore=3.17317590238013
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,-1,0,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,-1,0,0,1,0,0,0
diffExp1.2Score=2

cont.predictedValues:
Include	Exclude	Both
Lung	74.7675351736545	68.4830552040947	52.9190418578367
cerebhem	61.6181820066654	71.3343392601736	60.5049881561343
cortex	70.746569299366	61.7961217421039	63.8850694818955
heart	67.1520903242853	69.8042731883659	79.4929728698083
kidney	63.9643071770935	59.984083280784	70.3427462542626
liver	68.4317179099445	67.5177701012831	80.5745592391447
stomach	65.8058842561772	62.4273026555644	51.400313637147
testicle	63.3745443809554	67.4875398847152	62.2111917122628
cont.diffExp=6.28447996955977,-9.71615725350828,8.9504475572621,-2.65218286408056,3.98022389630957,0.91394780866139,3.37858160061278,-4.11299550375972
cont.diffExpScore=4.98221985252584

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=0.940676198245015
cont.tran.correlation=-0.0422954005871026

tran.covariance=0.023642896190221
cont.tran.covariance=-0.000177221571637912

tran.mean=67.5432922500333
cont.tran.mean=66.5434572403267

weightedLogRatios:
wLogRatio
Lung	0.565091714216207
cerebhem	-1.41775250916382
cortex	0.436669136836694
heart	0.518972138590874
kidney	0.842916321475713
liver	0.663997987233861
stomach	0.54496213887808
testicle	0.256326249219828

cont.weightedLogRatios:
wLogRatio
Lung	0.374937585711679
cerebhem	-0.61411350921116
cortex	0.566952954469861
heart	-0.163707547909467
kidney	0.265091902545447
liver	0.0567285364963529
stomach	0.219277963155246
testicle	-0.262872989842450

varWeightedLogRatios=0.510960775717372
cont.varWeightedLogRatios=0.147453312849737

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.91299423831933	0.118863085901678	32.9201804633955	2.22646666376989e-145	***
df.mm.trans1	0.2787893434519	0.105552720671984	2.64123313617151	0.0084409323716351	** 
df.mm.trans2	0.23972151817072	0.0960139255738025	2.49673697578852	0.0127581339854236	*  
df.mm.exp2	1.06084061855439	0.129441039620991	8.19555082113505	1.15163223611679e-15	***
df.mm.exp3	-0.088396674074236	0.129441039620991	-0.682910723933192	0.494884463287466	   
df.mm.exp4	-0.000642705681063248	0.129441039620991	-0.00496523886817595	0.996039713824645	   
df.mm.exp5	-0.20737956728461	0.129441039620991	-1.60211605138391	0.109571616835029	   
df.mm.exp6	-0.036345691768874	0.129441039620991	-0.280789553879479	0.778953045380814	   
df.mm.exp7	0.22722826740534	0.129441039620991	1.75545768228280	0.0796092541576013	.  
df.mm.exp8	0.23523202044405	0.129441039620991	1.81729087724280	0.0695910482965868	.  
df.mm.trans1:exp2	-0.850084243235398	0.122910339878967	-6.91629560273363	1.02988468224311e-11	***
df.mm.trans2:exp2	-0.40650450559994	0.103499768494899	-3.92758854934034	9.41143652743714e-05	***
df.mm.trans1:exp3	-0.0434142679384603	0.122910339878967	-0.353219004855176	0.724028373792939	   
df.mm.trans2:exp3	-0.0156635199792450	0.103499768494899	-0.151338695796378	0.87975123417584	   
df.mm.trans1:exp4	-0.0666852309131708	0.122910339878967	-0.542551838835018	0.587607471201434	   
df.mm.trans2:exp4	-0.0575262037407313	0.103499768494899	-0.555809975010395	0.578514639320735	   
df.mm.trans1:exp5	0.160765995051312	0.122910339878967	1.30799406469481	0.191295681140444	   
df.mm.trans2:exp5	0.090083704551569	0.103499768494899	0.870375903845708	0.384387124233502	   
df.mm.trans1:exp6	0.00798683107483769	0.122910339878967	0.0649809534551975	0.948207328528628	   
df.mm.trans2:exp6	-0.0173151396368391	0.103499768494899	-0.167296409341172	0.867184132794249	   
df.mm.trans1:exp7	-0.187868159650520	0.122910339878967	-1.52849760106039	0.126831292079681	   
df.mm.trans2:exp7	-0.181723976878167	0.103499768494899	-1.75579114350506	0.0795522320827335	.  
df.mm.trans1:exp8	-0.248695867220328	0.122910339878967	-2.02339255969209	0.0434042416664829	*  
df.mm.trans2:exp8	-0.174298166596912	0.103499768494899	-1.68404402378449	0.0926096188585849	.  
df.mm.trans1:probe2	0.150520276838315	0.0673207657023373	2.23586697608059	0.0256682990118595	*  
df.mm.trans1:probe3	0.0705693541737837	0.0673207657023373	1.04825537020494	0.294875170368381	   
df.mm.trans1:probe4	0.472065154978733	0.0673207657023373	7.0121774470896	5.4429964982194e-12	***
df.mm.trans1:probe5	-0.326014174256699	0.0673207657023373	-4.84269854710491	1.57085256930811e-06	***
df.mm.trans1:probe6	-0.326558124956618	0.0673207657023373	-4.85077853095899	1.51014693076797e-06	***
df.mm.trans1:probe7	-0.386546819609507	0.0673207657023372	-5.7418660583667	1.38443964843402e-08	***
df.mm.trans1:probe8	0.476938507757923	0.0673207657023373	7.08456748496793	3.34685170041765e-12	***
df.mm.trans1:probe9	0.265432044989073	0.0673207657023373	3.94279598902212	8.84589796773737e-05	***
df.mm.trans1:probe10	0.113794001969083	0.0673207657023373	1.69032542606883	0.0914015800740972	.  
df.mm.trans1:probe11	-0.343680697890201	0.0673207657023373	-5.10512164121551	4.24268962495069e-07	***
df.mm.trans1:probe12	-0.403375567305238	0.0673207657023373	-5.99184461283145	3.2877214576357e-09	***
df.mm.trans1:probe13	-0.375515441315202	0.0673207657023373	-5.57800312277441	3.452533472272e-08	***
df.mm.trans1:probe14	-0.406626505631681	0.0673207657023373	-6.04013488838799	2.47546723604356e-09	***
df.mm.trans1:probe15	-0.327086041424741	0.0673207657023372	-4.8586203382025	1.45339584355626e-06	***
df.mm.trans1:probe16	-0.335733730742166	0.0673207657023373	-4.98707534353713	7.70155986964831e-07	***
df.mm.trans1:probe17	0.586179016624268	0.0673207657023373	8.70725415120935	2.14111080000133e-17	***
df.mm.trans1:probe18	0.371147341496294	0.0673207657023373	5.51311824255452	4.92661276896604e-08	***
df.mm.trans1:probe19	0.341122851393285	0.0673207657023373	5.06712673028081	5.14701792842635e-07	***
df.mm.trans1:probe20	0.538830049242776	0.0673207657023373	8.00392038951613	4.87379165401636e-15	***
df.mm.trans1:probe21	0.332079440501662	0.0673207657023373	4.93279357471914	1.00898920641058e-06	***
df.mm.trans1:probe22	0.700154218080203	0.0673207657023373	10.4002711611448	1.09431418392971e-23	***
df.mm.trans2:probe2	-0.0926818867182232	0.0673207657023373	-1.37672062626295	0.169029562294273	   
df.mm.trans2:probe3	-0.120147373697489	0.0673207657023373	-1.78470004676904	0.0747338653203738	.  
df.mm.trans2:probe4	0.0887638090517804	0.0673207657023373	1.31852049105108	0.187751657713394	   
df.mm.trans2:probe5	-0.190785240194842	0.0673207657023373	-2.83397311668156	0.00472694293457777	** 
df.mm.trans2:probe6	-0.192897908460459	0.0673207657023373	-2.86535523546134	0.00428768622139834	** 
df.mm.trans3:probe2	-0.0188560396249432	0.0673207657023373	-0.280092471145029	0.779487574746776	   
df.mm.trans3:probe3	-0.297051778251714	0.0673207657023373	-4.41248365422856	1.17945610560198e-05	***
df.mm.trans3:probe4	-0.413433614320099	0.0673207657023373	-6.14124943480471	1.35792684979168e-09	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.43295534080679	0.213344944234973	20.7783472755953	2.19524956407485e-75	***
df.mm.trans1	-0.168785360946898	0.189454439406375	-0.890902115969201	0.373281369880118	   
df.mm.trans2	-0.250036845597367	0.172333449379464	-1.45088980982912	0.147249110645984	   
df.mm.exp2	-0.286597873841291	0.232331099013368	-1.23357516517752	0.217766607975516	   
df.mm.exp3	-0.346347908067371	0.232331099013368	-1.49075138687069	0.136467792540974	   
df.mm.exp4	-0.495220226965589	0.232331099013368	-2.13152793176902	0.0333860490774217	*  
df.mm.exp5	-0.573182073854567	0.232331099013368	-2.46709147543604	0.0138548378700447	*  
df.mm.exp6	-0.523162585028131	0.232331099013368	-2.25179748750738	0.0246377832874570	*  
df.mm.exp7	-0.191139172182624	0.232331099013368	-0.82270162278889	0.41095197798939	   
df.mm.exp8	-0.341736536263509	0.232331099013368	-1.47090311075336	0.141757261487160	   
df.mm.trans1:exp2	0.09317109425162	0.22060927838497	0.42233533844861	0.672907235053739	   
df.mm.trans2:exp2	0.327389356489676	0.185769637144891	1.76234050688449	0.0784390158876885	.  
df.mm.trans1:exp3	0.291068183923547	0.22060927838497	1.31938323743403	0.187463356973025	   
df.mm.trans2:exp3	0.24360217019564	0.185769637144891	1.31131316150250	0.190172926996796	   
df.mm.trans1:exp4	0.387796509604928	0.22060927838497	1.75784315348791	0.07920206910832	.  
df.mm.trans2:exp4	0.514329109939651	0.185769637144891	2.76863925582467	0.00577488189206124	** 
df.mm.trans1:exp5	0.41712353226049	0.22060927838497	1.89077964133764	0.0590578257945772	.  
df.mm.trans2:exp5	0.440674976846398	0.185769637144891	2.37215824727425	0.0179482678975935	*  
df.mm.trans1:exp6	0.434615245285936	0.22060927838497	1.9700678433276	0.049216108905758	*  
df.mm.trans2:exp6	0.508967063635269	0.185769637144891	2.73977530159193	0.00630141045297137	** 
df.mm.trans1:exp7	0.0634646638781209	0.22060927838497	0.287679033006822	0.773675801950633	   
df.mm.trans2:exp7	0.0985555490372335	0.185769637144891	0.530525604463365	0.595912290358274	   
df.mm.trans1:exp8	0.176415039870727	0.22060927838497	0.799671895770755	0.42416650458608	   
df.mm.trans2:exp8	0.327093177417789	0.185769637144891	1.76074617168290	0.0787088333410242	.  
df.mm.trans1:probe2	0.206516645651948	0.120832678166385	1.709112541291	0.0878640457001276	.  
df.mm.trans1:probe3	-0.0380052119427132	0.120832678166385	-0.314527597330753	0.753212116277759	   
df.mm.trans1:probe4	0.181371871595643	0.120832678166385	1.50101673113540	0.133792688661501	   
df.mm.trans1:probe5	0.0289197487467245	0.120832678166385	0.239337149400119	0.810912750664472	   
df.mm.trans1:probe6	0.0279639519275781	0.120832678166385	0.231427063869860	0.817049253987799	   
df.mm.trans1:probe7	0.0675136906828647	0.120832678166385	0.558737021370157	0.576516148492125	   
df.mm.trans1:probe8	0.00245252556248967	0.120832678166385	0.0202968733268709	0.98381221260602	   
df.mm.trans1:probe9	0.0737998615416878	0.120832678166385	0.61076078641629	0.541552053807679	   
df.mm.trans1:probe10	2.47686528070497e-05	0.120832678166385	0.000204983065698036	0.999836504307363	   
df.mm.trans1:probe11	0.0571125981126233	0.120832678166385	0.472658547168673	0.636601046092816	   
df.mm.trans1:probe12	0.0299019379619504	0.120832678166385	0.247465655944296	0.804618911200136	   
df.mm.trans1:probe13	0.183548395609025	0.120832678166385	1.51902944132614	0.129197126347741	   
df.mm.trans1:probe14	0.0541597279892824	0.120832678166385	0.4482208688175	0.654129590149784	   
df.mm.trans1:probe15	0.155051835298760	0.120832678166385	1.28319456004489	0.199839678714445	   
df.mm.trans1:probe16	0.0306012680707662	0.120832678166385	0.25325324684626	0.80014532025527	   
df.mm.trans1:probe17	-0.0333398465468215	0.120832678166385	-0.275917467466152	0.782691184522529	   
df.mm.trans1:probe18	-0.00252974172034815	0.120832678166385	-0.0209359070636896	0.983302624168245	   
df.mm.trans1:probe19	-0.0188988929555145	0.120832678166385	-0.156405479397643	0.875757568603067	   
df.mm.trans1:probe20	0.150791951195556	0.120832678166385	1.24794015562510	0.212461500763379	   
df.mm.trans1:probe21	0.102758903954290	0.120832678166385	0.850423126538603	0.395374571677472	   
df.mm.trans1:probe22	0.045842528856021	0.120832678166385	0.379388502776513	0.704512033868418	   
df.mm.trans2:probe2	-0.105103278076858	0.120832678166385	-0.86982494861309	0.384687984612115	   
df.mm.trans2:probe3	0.092985941902616	0.120832678166385	0.769543002055914	0.441825174231793	   
df.mm.trans2:probe4	0.151973163497280	0.120832678166385	1.25771575871235	0.208905182341093	   
df.mm.trans2:probe5	0.178087047631562	0.120832678166385	1.47383183368938	0.140966991693361	   
df.mm.trans2:probe6	0.118735626791790	0.120832678166385	0.982644997972258	0.326114572270477	   
df.mm.trans3:probe2	-0.0261831778121470	0.120832678166385	-0.216689543006679	0.828512108762665	   
df.mm.trans3:probe3	-0.0688351131368296	0.120832678166385	-0.56967299062961	0.569078445151379	   
df.mm.trans3:probe4	-0.0864613117019565	0.120832678166385	-0.715545769687406	0.474505466557839