chr14.7725_chr14_15848460_15850129_-_1.R 

fitVsDatCorrelation=0.894062364133713
cont.fitVsDatCorrelation=0.237918447310949

fstatistic=7933.40759966941,50,646
cont.fstatistic=1677.19996948815,50,646

residuals=-0.601530493072974,-0.100015520504195,0.00215521318132325,0.0940684876038148,0.829842725403196
cont.residuals=-0.670680901530499,-0.288568113026359,-0.0968432026902543,0.269240790255459,1.27074762191764

predictedValues:
Include	Exclude	Both
chr14.7725_chr14_15848460_15850129_-_1.R.tl.Lung	63.4602575240185	48.3089114795481	81.708250361632
chr14.7725_chr14_15848460_15850129_-_1.R.tl.cerebhem	92.626300042741	59.1275428746217	83.9344282139501
chr14.7725_chr14_15848460_15850129_-_1.R.tl.cortex	60.4795833509976	76.2692604419891	133.518684800716
chr14.7725_chr14_15848460_15850129_-_1.R.tl.heart	58.3141383668089	53.6548657739247	83.9527481787504
chr14.7725_chr14_15848460_15850129_-_1.R.tl.kidney	60.0512806623589	43.5818895648586	78.8282254922967
chr14.7725_chr14_15848460_15850129_-_1.R.tl.liver	59.1362091983907	46.3812821365061	75.6519966939382
chr14.7725_chr14_15848460_15850129_-_1.R.tl.stomach	60.7394367673497	47.6405432580196	76.9542047582003
chr14.7725_chr14_15848460_15850129_-_1.R.tl.testicle	68.680886310494	48.3728930785623	77.6535739450464


diffExp=15.1513460444704,33.4987571681193,-15.7896770909915,4.65927259288418,16.4693910975003,12.7549270618846,13.0988935093301,20.3079932319317
diffExpScore=1.30231419679981
diffExp1.5=0,1,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,1,0,0,0,0,0,1
diffExp1.4Score=0.666666666666667
diffExp1.3=1,1,0,0,1,0,0,1
diffExp1.3Score=0.8
diffExp1.2=1,1,-1,0,1,1,1,1
diffExp1.2Score=1.16666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	71.8119448352229	73.2831597110918	75.3086518868551
cerebhem	59.2865213900093	66.1830195320202	79.8437270556347
cortex	68.2515486504777	64.5087072031511	70.9490108634671
heart	69.5320688419848	85.1218654926029	72.657924613159
kidney	60.6860614879606	70.7429746309385	73.9048084586046
liver	66.2673687961028	79.6867133389203	72.5936029609826
stomach	62.4933984741664	64.1068941041786	70.5486210679376
testicle	66.0610270802316	72.7323867264242	66.6453835620636
cont.diffExp=-1.47121487586892,-6.89649814201084,3.74284144732655,-15.5897966506181,-10.0569131429778,-13.4193445428176,-1.61349563001222,-6.67135964619264
cont.diffExpScore=1.12242731961286

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,-1,0,-1,0,0
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.186588092775924
cont.tran.correlation=0.491824513143765

tran.covariance=0.00615505736073686
cont.tran.covariance=0.00336161999509718

tran.mean=59.1765800519494
cont.tran.mean=68.7972287684677

weightedLogRatios:
wLogRatio
Lung	1.09501443771358
cerebhem	1.93202403572199
cortex	-0.978491513842955
heart	0.335105548430713
kidney	1.26136697945561
liver	0.961675775884796
stomach	0.968026203574624
testicle	1.42112602332013

cont.weightedLogRatios:
wLogRatio
Lung	-0.0868834454939828
cerebhem	-0.455287858672627
cortex	0.23659765105578
heart	-0.87855803070169
kidney	-0.641323323097398
liver	-0.790342557229704
stomach	-0.105731665891340
testicle	-0.407794363684585

varWeightedLogRatios=0.765188637291467
cont.varWeightedLogRatios=0.147429650088601

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.95382444212399	0.0880575436156883	44.9004625813748	8.26010404385445e-201	***
df.mm.trans1	0.212176627250949	0.06949670125602	3.05304602112419	0.00235838814269861	** 
df.mm.trans2	-0.0872479547665605	0.0694967012560199	-1.25542584309357	0.209778129366075	   
df.mm.exp2	0.553359185765808	0.0920254067166747	6.01311317720633	3.04512947904941e-09	***
df.mm.exp3	-0.0825405168754841	0.0920254067166746	-0.896931834592241	0.370089420096268	   
df.mm.exp4	-0.00671229476215506	0.0920254067166747	-0.0729395826830811	0.941876772867997	   
df.mm.exp5	-0.122305472382424	0.0920254067166747	-1.32904028078870	0.184303884418778	   
df.mm.exp6	-0.0342793546537649	0.0920254067166747	-0.372498811760792	0.709643670414937	   
df.mm.exp7	0.00219192289257051	0.0920254067166746	0.0238186710689467	0.981004602275217	   
df.mm.exp8	0.131278052336635	0.0920254067166747	1.42654139786430	0.154195227820504	   
df.mm.trans1:exp2	-0.175199910898317	0.0697817196820729	-2.51068491428030	0.0122928565321408	*  
df.mm.trans2:exp2	-0.351278377750445	0.0697817196820729	-5.03395988735843	6.23823277183441e-07	***
df.mm.trans1:exp3	0.0344325154858713	0.0697817196820729	0.493431741761978	0.62187526080187	   
df.mm.trans2:exp3	0.539194450104372	0.0697817196820729	7.72687248982905	4.22562117963071e-14	***
df.mm.trans1:exp4	-0.077856974901846	0.0697817196820729	-1.11572164252420	0.264956159227034	   
df.mm.trans2:exp4	0.111668408165130	0.0697817196820729	1.60025302720962	0.110031365825481	   
df.mm.trans1:exp5	0.0670905030820648	0.0697817196820729	0.961433787927993	0.336693824661937	   
df.mm.trans2:exp5	0.0193311131695671	0.0697817196820729	0.277022596428407	0.781851373205376	   
df.mm.trans1:exp6	-0.0362910759516855	0.0697817196820729	-0.520065657840312	0.603195982297243	   
df.mm.trans2:exp6	-0.00644071605522239	0.0697817196820729	-0.0922980414436107	0.926489859153197	   
df.mm.trans1:exp7	-0.0460125803631255	0.0697817196820729	-0.659378710825125	0.509887591368386	   
df.mm.trans2:exp7	-0.0161238213917309	0.0697817196820729	-0.231060820300666	0.817340713773293	   
df.mm.trans1:exp8	-0.0522209556614842	0.0697817196820729	-0.748347216139185	0.454523109648214	   
df.mm.trans2:exp8	-0.129954502188875	0.0697817196820729	-1.86230008060779	0.0630145915369254	.  
df.mm.trans1:probe2	-0.167737344708054	0.0519556571480575	-3.22847123711773	0.00130754457038406	** 
df.mm.trans1:probe3	-0.218849208887784	0.0519556571480575	-4.21223060010832	2.88809884367656e-05	***
df.mm.trans1:probe4	-0.00433876840314889	0.0519556571480575	-0.0835090660249903	0.933472639164826	   
df.mm.trans1:probe5	-0.00318625016531662	0.0519556571480575	-0.0613263375003957	0.95111828407898	   
df.mm.trans1:probe6	0.0356053931274764	0.0519556571480575	0.685303489204498	0.4933982604956	   
df.mm.trans2:probe2	0.0404523772879512	0.0519556571480575	0.778594276513036	0.436503844115373	   
df.mm.trans2:probe3	0.0453448093340973	0.0519556571480575	0.872759807558178	0.38311829229408	   
df.mm.trans2:probe4	0.0225601975279244	0.0519556571480575	0.434220232527035	0.664273510496798	   
df.mm.trans2:probe5	0.0943014655147912	0.0519556571480575	1.81503748948957	0.0699817516417441	.  
df.mm.trans2:probe6	0.0512510065239719	0.0519556571480575	0.986437461043413	0.324287802013725	   
df.mm.trans3:probe2	0.586855131977284	0.0519556571480575	11.2953076563911	3.99828536805443e-27	***
df.mm.trans3:probe3	0.738844941066833	0.0519556571480575	14.2206832060916	3.99426008013902e-40	***
df.mm.trans3:probe4	-0.0316195398133048	0.0519556571480575	-0.608587044201922	0.54301212245345	   
df.mm.trans3:probe5	0.606860408928104	0.0519556571480575	11.6803528670370	9.88322191203602e-29	***
df.mm.trans3:probe6	0.465956616957711	0.0519556571480575	8.96835190881869	3.22531070212934e-18	***
df.mm.trans3:probe7	-0.0292473351818534	0.0519556571480575	-0.562928789419555	0.573678686888191	   
df.mm.trans3:probe8	-0.0420700807234376	0.0519556571480575	-0.809730509298553	0.418393233850885	   
df.mm.trans3:probe9	0.679072760407137	0.0519556571480575	13.0702371538097	8.32380243674318e-35	***
df.mm.trans3:probe10	-0.106323485772101	0.0519556571480575	-2.04642750392150	0.0411185732414363	*  
df.mm.trans3:probe11	0.3734993602216	0.0519556571480575	7.18881024172676	1.81195420461265e-12	***
df.mm.trans3:probe12	0.53594115711069	0.0519556571480575	10.3153571050680	3.37548251020032e-23	***
df.mm.trans3:probe13	0.659202363523963	0.0519556571480575	12.6877880044023	4.29028666746076e-33	***
df.mm.trans3:probe14	0.330162467028836	0.0519556571480575	6.35469716200443	3.94456972519499e-10	***
df.mm.trans3:probe15	0.462659321026384	0.0519556571480575	8.90488825322618	5.37592952982831e-18	***
df.mm.trans3:probe16	-0.0753005112200954	0.0519556571480575	-1.44932266000433	0.147732755028993	   
df.mm.trans3:probe17	0.360338142681147	0.0519556571480575	6.93549388961235	9.84640526308614e-12	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.28064166440781	0.190937412434231	22.4190828284231	8.78981150832052e-83	***
df.mm.trans1	-0.0328688177759014	0.150691465667629	-0.21811996870744	0.827404521926353	   
df.mm.trans2	0.00434609968061908	0.150691465667629	0.0288410472442084	0.977000270996584	   
df.mm.exp2	-0.352052035567249	0.199541030957842	-1.76430899388121	0.0781525257470509	.  
df.mm.exp3	-0.118747762933337	0.199541030957842	-0.5951044873494	0.551982025865876	   
df.mm.exp4	0.153322910836254	0.199541030957842	0.768377862438966	0.442543522705542	   
df.mm.exp5	-0.184797253160518	0.199541030957842	-0.926111548454219	0.354733856702455	   
df.mm.exp6	0.04013702453988	0.199541030957842	0.201146723294018	0.840647164616456	   
df.mm.exp7	-0.207475930917113	0.199541030957842	-1.03976575605119	0.298837738768537	   
df.mm.exp8	0.0311933215858488	0.199541030957842	0.15632535041096	0.875825414634334	   
df.mm.trans1:exp2	0.160383195632338	0.151309478373095	1.05996793695151	0.289555330272707	   
df.mm.trans2:exp2	0.250145125305826	0.151309478373095	1.65320195400466	0.0987756187468091	.  
df.mm.trans1:exp3	0.0678970627654474	0.151309478373095	0.448729739177533	0.653777109461578	   
df.mm.trans2:exp3	-0.00878286474282654	0.151309478373095	-0.0580457010179494	0.953730175635673	   
df.mm.trans1:exp4	-0.185585667326173	0.151309478373095	-1.22653034906749	0.220446023853777	   
df.mm.trans2:exp4	-0.0035698072160779	0.151309478373095	-0.0235927534379278	0.981184738019358	   
df.mm.trans1:exp5	0.0164604705091705	0.151309478373095	0.108786777181154	0.913405393312597	   
df.mm.trans2:exp5	0.149519648486282	0.151309478373095	0.988171065646005	0.323438845174889	   
df.mm.trans1:exp6	-0.120490248352034	0.151309478373095	-0.796316593299811	0.426140579020969	   
df.mm.trans2:exp6	0.0436350011743006	0.151309478373095	0.288382470440527	0.77314648894654	   
df.mm.trans1:exp7	0.0684860328424644	0.151309478373095	0.452622225513152	0.650972754303311	   
df.mm.trans2:exp7	0.0736970036231562	0.151309478373095	0.487061381848374	0.626380053394365	   
df.mm.trans1:exp8	-0.114665178881654	0.151309478373095	-0.757818876349016	0.448835768566814	   
df.mm.trans2:exp8	-0.0387373894646409	0.151309478373095	-0.256014295212381	0.79802129990616	   
df.mm.trans1:probe2	-0.0111511868392947	0.112656773398830	-0.0989837228855923	0.921181900604876	   
df.mm.trans1:probe3	0.0937545169894713	0.112656773398830	0.832213760086665	0.405595832717564	   
df.mm.trans1:probe4	0.102628644871740	0.112656773398830	0.910985125664947	0.362643007134019	   
df.mm.trans1:probe5	0.188484233382854	0.112656773398830	1.67308389630137	0.0947949233160102	.  
df.mm.trans1:probe6	0.230677290036667	0.112656773398830	2.04761136926955	0.0410019730754477	*  
df.mm.trans2:probe2	0.00702506058580008	0.112656773398830	0.0623580844174352	0.950296962189107	   
df.mm.trans2:probe3	0.097361616010899	0.112656773398830	0.864232243419734	0.387781103525952	   
df.mm.trans2:probe4	-0.00761132387155063	0.112656773398830	-0.0675620616667662	0.946155161885084	   
df.mm.trans2:probe5	0.0200485771184755	0.112656773398830	0.177961577574206	0.85880894004356	   
df.mm.trans2:probe6	0.0980667647064932	0.112656773398830	0.870491509279388	0.384355208514964	   
df.mm.trans3:probe2	0.09541788544489	0.112656773398830	0.846978681939433	0.397320665206521	   
df.mm.trans3:probe3	0.0811186515951866	0.112656773398830	0.720051259661138	0.47175387252854	   
df.mm.trans3:probe4	0.0461166757169276	0.112656773398830	0.409355552494518	0.682414442920524	   
df.mm.trans3:probe5	0.185122639798744	0.112656773398830	1.64324464667002	0.100818916900927	   
df.mm.trans3:probe6	0.00371429209246908	0.112656773398830	0.0329699846747756	0.973708707369358	   
df.mm.trans3:probe7	0.127855216751472	0.112656773398830	1.13490927259950	0.256834254042006	   
df.mm.trans3:probe8	0.0369726071766344	0.112656773398830	0.328188053511379	0.742875824586071	   
df.mm.trans3:probe9	0.0598389181792977	0.112656773398830	0.531161299706809	0.595489580961356	   
df.mm.trans3:probe10	0.140407966601391	0.112656773398830	1.24633399630856	0.213093560669127	   
df.mm.trans3:probe11	-0.00885076037524347	0.112656773398830	-0.0785639434560215	0.937403796478749	   
df.mm.trans3:probe12	0.0504071350512927	0.112656773398830	0.447439896692589	0.654707465358369	   
df.mm.trans3:probe13	0.186412292166458	0.112656773398830	1.65469227053501	0.09847266804351	.  
df.mm.trans3:probe14	0.0731270754000538	0.112656773398830	0.64911388098404	0.516495473470972	   
df.mm.trans3:probe15	0.0706946976660224	0.112656773398830	0.62752283358718	0.530538314238101	   
df.mm.trans3:probe16	-0.0176241771134241	0.112656773398830	-0.156441344640953	0.87573402651127	   
df.mm.trans3:probe17	0.050362257256817	0.112656773398830	0.447041538093086	0.6549949078485