chr19.12293_chr19_11274410_11276311_-_2.R 

fitVsDatCorrelation=0.863041750559789
cont.fitVsDatCorrelation=0.28554356365056

fstatistic=12082.4284410346,46,554
cont.fstatistic=3347.92453556904,46,554

residuals=-0.44022849828479,-0.0740382672600129,-9.78538830002824e-05,0.0721298841336577,0.537913528641442
cont.residuals=-0.63578169390283,-0.173152514888041,-0.0316016634744769,0.150388415349363,0.683729017187511

predictedValues:
Include	Exclude	Both
chr19.12293_chr19_11274410_11276311_-_2.R.tl.Lung	49.1587809668051	87.8949619946976	73.1450677467778
chr19.12293_chr19_11274410_11276311_-_2.R.tl.cerebhem	51.9994814664328	45.2583581603113	62.4583098361943
chr19.12293_chr19_11274410_11276311_-_2.R.tl.cortex	59.9976701616829	62.5250257693462	71.0431950105053
chr19.12293_chr19_11274410_11276311_-_2.R.tl.heart	50.6428596710745	71.7463174727845	58.9470044662178
chr19.12293_chr19_11274410_11276311_-_2.R.tl.kidney	50.0232556117625	96.5367524697344	74.3580069718804
chr19.12293_chr19_11274410_11276311_-_2.R.tl.liver	52.1088114012775	59.0020691238598	52.3808655503506
chr19.12293_chr19_11274410_11276311_-_2.R.tl.stomach	49.3049066223549	94.3544626622036	72.3463890780367
chr19.12293_chr19_11274410_11276311_-_2.R.tl.testicle	48.0155868729236	68.0776757837414	63.721081427514


diffExp=-38.7361810278925,6.74112330612153,-2.52735560766330,-21.1034578017100,-46.5134968579719,-6.89325772258233,-45.0495560398488,-20.0620889108178
diffExpScore=1.0712683695849
diffExp1.5=-1,0,0,0,-1,0,-1,0
diffExp1.5Score=0.75
diffExp1.4=-1,0,0,-1,-1,0,-1,-1
diffExp1.4Score=0.833333333333333
diffExp1.3=-1,0,0,-1,-1,0,-1,-1
diffExp1.3Score=0.833333333333333
diffExp1.2=-1,0,0,-1,-1,0,-1,-1
diffExp1.2Score=0.833333333333333

cont.predictedValues:
Include	Exclude	Both
Lung	56.3613308187138	59.8960397039181	56.1032090792322
cerebhem	56.6353873867856	57.3120357786683	62.2421483634924
cortex	56.8232589717229	50.8039595501048	59.316451704115
heart	57.525933790893	52.3515768709161	57.4809720234673
kidney	59.3523499621908	63.6608316995563	56.861458052378
liver	55.232314407201	67.2483548421445	55.7944511984642
stomach	57.1188500927609	53.8908719029854	59.3998087367919
testicle	56.1954721209615	60.7956916164083	54.975580301723
cont.diffExp=-3.53470888520429,-0.676648391882658,6.01929942161809,5.17435691997698,-4.30848173736549,-12.0160404349435,3.22797818977548,-4.60021949544685
cont.diffExpScore=3.37682817412633

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,-1,0,0
cont.diffExp1.2Score=0.5

tran.correlation=-0.437993920640708
cont.tran.correlation=-0.171227420481959

tran.covariance=-0.00776850392360503
cont.tran.covariance=-0.000361806378651727

tran.mean=62.290436013187
cont.tran.mean=57.5752662197457

weightedLogRatios:
wLogRatio
Lung	-2.43219716188043
cerebhem	0.538975354773451
cortex	-0.169787037565389
heart	-1.42782725811940
kidney	-2.78832051287946
liver	-0.498873708158848
stomach	-2.74057681769475
testicle	-1.41258487962581

cont.weightedLogRatios:
wLogRatio
Lung	-0.24709160583617
cerebhem	-0.0480121821644989
cortex	0.446089721254316
heart	0.377496779330155
kidney	-0.288617445236842
liver	-0.809024515906118
stomach	0.233625842181316
testicle	-0.320095350692631

varWeightedLogRatios=1.55242707201826
cont.varWeightedLogRatios=0.177998702919886

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.96591825653045	0.0715127533315504	55.4574963453511	2.74999032616671e-228	***
df.mm.trans1	-0.127356425732918	0.0636741778200231	-2.00012674043306	0.0459742351092973	*  
df.mm.trans2	0.592767260845782	0.0593033358878831	9.99551293314171	9.71377367484476e-22	***
df.mm.exp2	-0.449631457365077	0.0814522819475006	-5.52018245056514	5.20946289880657e-08	***
df.mm.exp3	-0.112168729106771	0.0814522819475006	-1.37710971902627	0.169034492699454	   
df.mm.exp4	0.0425426885090025	0.0814522819475006	0.522301984570831	0.601668868321521	   
df.mm.exp5	0.0947671635453387	0.0814522819475006	1.16346849074677	0.245140333246432	   
df.mm.exp6	-0.00638806731787632	0.0814522819475006	-0.0784271129689613	0.937516625099488	   
df.mm.exp7	0.084863352503531	0.0814522819475006	1.04187814600736	0.297922623996492	   
df.mm.exp8	-0.141093703904796	0.0814522819475006	-1.73222530457449	0.0837900340104653	.  
df.mm.trans1:exp2	0.50580971696487	0.076793947877595	6.58658306994582	1.04747330083327e-10	***
df.mm.trans2:exp2	-0.214123666678202	0.0683279158976247	-3.13376551684999	0.00181709971591063	** 
df.mm.trans1:exp3	0.311418972803776	0.076793947877595	4.05525411065152	5.72610948386176e-05	***
df.mm.trans2:exp3	-0.228406869842349	0.0683279158976247	-3.34280457470076	0.000885353696239225	***
df.mm.trans1:exp4	-0.0127999288021955	0.076793947877595	-0.166678874520135	0.867683544826222	   
df.mm.trans2:exp4	-0.245548647464937	0.0683279158976247	-3.59367974625249	0.000355094712736877	***
df.mm.trans1:exp5	-0.0773346411456574	0.076793947877595	-1.00704083177133	0.314354787822498	   
df.mm.trans2:exp5	-0.000985860955858247	0.0683279158976247	-0.0144283773755862	0.988493414265556	   
df.mm.trans1:exp6	0.0646666394292621	0.076793947877595	0.842079893227222	0.400106597389965	   
df.mm.trans2:exp6	-0.39218190735281	0.0683279158976247	-5.73970246568641	1.56322101756729e-08	***
df.mm.trans1:exp7	-0.0818952377313831	0.076793947877595	-1.06642827976391	0.286694601558994	   
df.mm.trans2:exp7	-0.0139472706484671	0.0683279158976247	-0.204122582479527	0.838332669544192	   
df.mm.trans1:exp8	0.117563901487137	0.076793947877595	1.53090060787768	0.126364751081469	   
df.mm.trans2:exp8	-0.114399439757009	0.0683279158976247	-1.67427087822220	0.0946417765836033	.  
df.mm.trans1:probe2	0.00595385075649818	0.0383969739387975	0.155060416114777	0.8768301646819	   
df.mm.trans1:probe3	-0.00929074243552462	0.0383969739387975	-0.241965485361776	0.808896447542319	   
df.mm.trans1:probe4	0.0916915131955963	0.0383969739387975	2.38798800503777	0.0172749348796995	*  
df.mm.trans1:probe5	-0.148806297961635	0.0383969739387975	-3.8754694106578	0.000119159571746174	***
df.mm.trans1:probe6	-0.0267367692096773	0.0383969739387975	-0.696324904464974	0.486517414581921	   
df.mm.trans1:probe7	-0.0683014829696637	0.0383969739387975	-1.77882463025686	0.0758167730985307	.  
df.mm.trans1:probe8	0.0261415684383614	0.0383969739387975	0.68082366282378	0.496267525311681	   
df.mm.trans1:probe9	0.0480250633751538	0.0383969739387975	1.25075125585946	0.2115532184039	   
df.mm.trans1:probe10	-0.0445685460291136	0.0383969739387975	-1.16073068935467	0.246251354085377	   
df.mm.trans1:probe11	0.123221275224446	0.0383969739387975	3.20914026769018	0.00140834377062015	** 
df.mm.trans1:probe12	0.294414721747698	0.0383969739387975	7.66765428486571	7.91059956711401e-14	***
df.mm.trans1:probe13	0.090891959072858	0.0383969739387975	2.36716464213389	0.0182676892411085	*  
df.mm.trans1:probe14	0.264411983349777	0.0383969739387975	6.886271396575	1.55844808186695e-11	***
df.mm.trans1:probe15	0.214749782219633	0.0383969739387975	5.59288298504803	3.51198001722304e-08	***
df.mm.trans1:probe16	0.211581591590898	0.0383969739387975	5.51037151855108	5.49234671396079e-08	***
df.mm.trans2:probe2	-0.203096640943633	0.0383969739387975	-5.28939184810128	1.76971097019591e-07	***
df.mm.trans2:probe3	-0.177265812430313	0.0383969739387975	-4.61666100856967	4.85163482746394e-06	***
df.mm.trans2:probe4	-0.239391172259098	0.0383969739387975	-6.23463642318984	8.9835884249935e-10	***
df.mm.trans2:probe5	-0.0391386297652877	0.0383969739387975	-1.01931547594538	0.308498138817142	   
df.mm.trans2:probe6	-0.0839950102711616	0.0383969739387975	-2.18754244553346	0.0291201307929566	*  
df.mm.trans3:probe2	-0.122622821829792	0.0383969739387975	-3.19355431564075	0.00148515244855149	** 
df.mm.trans3:probe3	-0.294030357216261	0.0383969739387975	-7.65764400301252	8.48838217039818e-14	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.18445777672441	0.135677984342407	30.8410962692680	2.45441527071069e-122	***
df.mm.trans1	-0.082489476464344	0.120806201674649	-0.682824849393921	0.49500295359207	   
df.mm.trans2	-0.118680223494816	0.112513596571297	-1.05480783755421	0.291973009977583	   
df.mm.exp2	-0.143088411489725	0.154535812423413	-0.92592396057476	0.354888662959212	   
df.mm.exp3	-0.212167346657357	0.154535812423414	-1.37293319477325	0.170328574472627	   
df.mm.exp4	-0.138436718223802	0.154535812423413	-0.89582289084228	0.370736430826079	   
df.mm.exp5	0.099242779338622	0.154535812423413	0.642199227365539	0.521009483599622	   
df.mm.exp6	0.101065645588320	0.154535812423413	0.653994980214745	0.513386412884578	   
df.mm.exp7	-0.149396382573702	0.154535812423413	-0.966742790754354	0.334094457637168	   
df.mm.exp8	0.0322653455237436	0.154535812423413	0.208788791528397	0.834689864993017	   
df.mm.trans1:exp2	0.147939120603917	0.145697761201024	1.01538362281216	0.310366231146766	   
df.mm.trans2:exp2	0.0989886738375345	0.129635533124092	0.763592137525895	0.445435394257129	   
df.mm.trans1:exp3	0.220329777930661	0.145697761201024	1.51223859662926	0.131043385733171	   
df.mm.trans2:exp3	0.0475312542949005	0.129635533124092	0.366652978156859	0.714017877376155	   
df.mm.trans1:exp4	0.158889287222497	0.145697761201024	1.09054034813392	0.275949277493371	   
df.mm.trans2:exp4	0.00380838897606587	0.129635533124092	0.0293776627772290	0.97657396741273	   
df.mm.trans1:exp5	-0.0475343636595226	0.145697761201024	-0.326253219457078	0.744355985290847	   
df.mm.trans2:exp5	-0.0382836806672958	0.129635533124092	-0.295317801722227	0.767861763737753	   
df.mm.trans1:exp6	-0.121300757235793	0.145697761201024	-0.832550591277997	0.405456982760295	   
df.mm.trans2:exp6	0.0147165214714342	0.129635533124092	0.113522281405261	0.909657625119407	   
df.mm.trans1:exp7	0.162747269398264	0.145697761201024	1.11701969925067	0.264470103879311	   
df.mm.trans2:exp7	0.0437471058885321	0.129635533124092	0.337462305544389	0.73589624285412	   
df.mm.trans1:exp8	-0.0352124586873613	0.145697761201024	-0.241681535784050	0.809116367471657	   
df.mm.trans2:exp8	-0.0173568084437802	0.129635533124092	-0.133889281939124	0.893538748592574	   
df.mm.trans1:probe2	-0.00970559263004644	0.072848880600512	-0.133229125142909	0.894060556620255	   
df.mm.trans1:probe3	-0.0638742214290072	0.072848880600512	-0.876804432717093	0.380972912364365	   
df.mm.trans1:probe4	-0.0634928588625353	0.072848880600512	-0.871569450884452	0.383820844451842	   
df.mm.trans1:probe5	-0.0985860468456305	0.072848880600512	-1.35329528790230	0.176513240768315	   
df.mm.trans1:probe6	-0.0811543073898356	0.072848880600512	-1.11400898299136	0.265758406128011	   
df.mm.trans1:probe7	-0.102909073970487	0.072848880600512	-1.41263768395865	0.158323801498292	   
df.mm.trans1:probe8	-0.100843534558073	0.072848880600512	-1.38428392758809	0.166828872939144	   
df.mm.trans1:probe9	-0.137942839465633	0.072848880600512	-1.89354782569801	0.058805819889548	.  
df.mm.trans1:probe10	-0.088890675780775	0.072848880600512	-1.22020647466408	0.222905759049512	   
df.mm.trans1:probe11	-0.145767907958479	0.072848880600512	-2.00096290782888	0.0458837585436341	*  
df.mm.trans1:probe12	-0.153253819260280	0.072848880600512	-2.10372236329466	0.0358528443203292	*  
df.mm.trans1:probe13	-0.134152224548673	0.072848880600512	-1.84151387698509	0.0660806853526935	.  
df.mm.trans1:probe14	0.0408584249389675	0.072848880600512	0.560865515051996	0.575115985313814	   
df.mm.trans1:probe15	-0.0895986137550257	0.072848880600512	-1.22992437243292	0.219247461293087	   
df.mm.trans1:probe16	-0.104201721503302	0.072848880600512	-1.43038191725584	0.153171188139441	   
df.mm.trans2:probe2	0.0473517162023902	0.072848880600512	0.649999228705477	0.515962152065025	   
df.mm.trans2:probe3	0.111361110103920	0.072848880600512	1.52865918029134	0.126919696336542	   
df.mm.trans2:probe4	0.064215501675542	0.072848880600512	0.881489202664436	0.378435368395158	   
df.mm.trans2:probe5	0.0457731368455899	0.072848880600512	0.62832999585265	0.530046727433641	   
df.mm.trans2:probe6	-0.0272059536116966	0.072848880600512	-0.373457400957036	0.70895090744494	   
df.mm.trans3:probe2	0.0503041065769819	0.072848880600512	0.690526829819652	0.490152139163873	   
df.mm.trans3:probe3	0.0814107043202346	0.072848880600512	1.1175285556778	0.264252788571914