chr11.4367_chr11_117075204_117076929_-_2.R 

fitVsDatCorrelation=0.923623899476136
cont.fitVsDatCorrelation=0.265811776630649

fstatistic=5753.72989891955,52,692
cont.fstatistic=898.396352936327,52,692

residuals=-1.21588984426481,-0.132889139475600,0.0131300583655841,0.144441134124959,1.13743656689209
cont.residuals=-1.26384940741030,-0.479858312652109,-0.107697525161207,0.421639559419342,1.80387376319521

predictedValues:
Include	Exclude	Both
chr11.4367_chr11_117075204_117076929_-_2.R.tl.Lung	99.2527303653495	254.089347026398	79.5138699282063
chr11.4367_chr11_117075204_117076929_-_2.R.tl.cerebhem	89.6563278834538	118.126116361439	64.730680382506
chr11.4367_chr11_117075204_117076929_-_2.R.tl.cortex	116.331043452097	144.602566429264	95.8478394647515
chr11.4367_chr11_117075204_117076929_-_2.R.tl.heart	156.667427880224	189.319884027523	121.879714597250
chr11.4367_chr11_117075204_117076929_-_2.R.tl.kidney	200.836352561776	254.202794711529	162.648265804820
chr11.4367_chr11_117075204_117076929_-_2.R.tl.liver	251.995998742619	227.274429752715	219.293552708902
chr11.4367_chr11_117075204_117076929_-_2.R.tl.stomach	172.006654661959	203.090142756938	142.917192829915
chr11.4367_chr11_117075204_117076929_-_2.R.tl.testicle	159.140768982214	211.417405088716	128.759294998679


diffExp=-154.836616661048,-28.4697884779854,-28.2715229771672,-32.6524561472993,-53.3664421497537,24.7215689899040,-31.0834880949791,-52.2766361065021
diffExpScore=1.13560565518307
diffExp1.5=-1,0,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=-1,0,0,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=-1,-1,0,0,0,0,0,-1
diffExp1.3Score=0.75
diffExp1.2=-1,-1,-1,-1,-1,0,0,-1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	164.607975733554	153.603978267345	162.564815353383
cerebhem	137.126784256448	179.994473277638	181.217822196472
cortex	141.200457808285	133.389169489704	161.002129160688
heart	135.451572077028	157.204983796189	164.858482083737
kidney	151.067565528999	181.529019898412	190.485907434591
liver	141.903301925848	128.327048420036	152.786561770626
stomach	133.690111168145	162.806693593745	110.956712376186
testicle	141.145522678986	128.876092506534	145.257218053297
cont.diffExp=11.0039974662095,-42.8676890211897,7.8112883185814,-21.7534117191616,-30.4614543694130,13.5762535058116,-29.1165824256002,12.2694301724517
cont.diffExpScore=2.09664698167470

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

tran.correlation=0.522232736297891
cont.tran.correlation=0.0448146231794524

tran.covariance=0.0557353576144072
cont.tran.covariance=0.000398888286142352

tran.mean=178.000624417763
cont.tran.mean=148.245296901681

weightedLogRatios:
wLogRatio
Lung	-4.76370083414947
cerebhem	-1.27787748265225
cortex	-1.05842307792719
heart	-0.974730418434094
kidney	-1.27725270425461
liver	0.565608657275922
stomach	-0.868888960399278
testicle	-1.48039039192470

cont.weightedLogRatios:
wLogRatio
Lung	0.350717230017789
cerebhem	-1.37558339304841
cortex	0.280093568868908
heart	-0.74216239147725
kidney	-0.938568679252793
liver	0.493251671266882
stomach	-0.984021692124106
testicle	0.445999060840847

varWeightedLogRatios=2.25623350482989
cont.varWeightedLogRatios=0.596161401246052

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	6.29010426312148	0.133630306586930	47.0709408949054	6.76821003469543e-218	***
df.mm.trans1	-1.84402851818917	0.120019557280208	-15.3644002692323	4.69683630272422e-46	***
df.mm.trans2	-0.262896375986606	0.110374283069771	-2.38186259221652	0.0174946195313469	*  
df.mm.exp2	-0.661922588598128	0.151185433535449	-4.37821669137803	1.38152872281087e-05	***
df.mm.exp3	-0.591756844184088	0.151185433535449	-3.91411282387424	9.97079254811493e-05	***
df.mm.exp4	-0.264895178476845	0.151185433535449	-1.75212103628181	0.0801959059345723	.  
df.mm.exp5	-0.0103911511387566	0.151185433535449	-0.0687311660638264	0.945223464919818	   
df.mm.exp6	-0.194263740588097	0.151185433535449	-1.28493688872841	0.199244257258169	   
df.mm.exp7	-0.260506215314921	0.151185433535449	-1.72309070538756	0.085318849368497	.  
df.mm.exp8	-0.193745101845089	0.151185433535449	-1.28150640782242	0.200445082370516	   
df.mm.trans1:exp2	0.560236941301769	0.144749032364733	3.87040197885471	0.000118935507994128	***
df.mm.trans2:exp2	-0.104010540065730	0.125987861279541	-0.8255600103803	0.409338239423012	   
df.mm.trans1:exp3	0.75052736456457	0.144749032364733	5.18502509000142	2.83876345827768e-07	***
df.mm.trans2:exp3	0.0280599371127618	0.125987861279541	0.222719370166167	0.823819645837963	   
df.mm.trans1:exp4	0.721351014143737	0.144749032364733	4.98346000908734	7.9001720944063e-07	***
df.mm.trans2:exp4	-0.0293526941710774	0.125987861279541	-0.232980335351116	0.815845569630507	   
df.mm.trans1:exp5	0.715212132057832	0.144749032364733	4.94104948664297	9.7549498814368e-07	***
df.mm.trans2:exp5	0.0108375388662070	0.125987861279541	0.0860205003572587	0.931475003078593	   
df.mm.trans1:exp6	1.12600752080074	0.144749032364733	7.77903314727155	2.66053485748406e-14	***
df.mm.trans2:exp6	0.0827360044179504	0.125987861279541	0.656698221381632	0.511593300109809	   
df.mm.trans1:exp7	0.81036995210781	0.144749032364733	5.59844814759017	3.11987982916096e-08	***
df.mm.trans2:exp7	0.0364701836722412	0.125987861279541	0.289473789790918	0.772305540764774	   
df.mm.trans1:exp8	0.665864822726997	0.144749032364733	4.60013315356178	5.02141087984452e-06	***
df.mm.trans2:exp8	0.00989353927169414	0.125987861279541	0.078527718235826	0.937430983535602	   
df.mm.trans1:probe2	0.418027727223439	0.0723745161823667	5.7758966729409	1.15668382827579e-08	***
df.mm.trans1:probe3	-0.117027861475805	0.0723745161823667	-1.61697608010148	0.106339175370058	   
df.mm.trans1:probe4	-0.526193882331289	0.0723745161823667	-7.2704303957681	9.7144196460715e-13	***
df.mm.trans1:probe5	0.472557604825931	0.0723745161823667	6.5293369787122	1.27869138025788e-10	***
df.mm.trans1:probe6	0.264202353642348	0.0723745161823667	3.65048870208155	0.000281467786257106	***
df.mm.trans1:probe7	0.0431379406406372	0.0723745161823667	0.596037706586387	0.551344940946018	   
df.mm.trans1:probe8	-0.366437524254219	0.0723745161823667	-5.06307390478277	5.29519869880333e-07	***
df.mm.trans1:probe9	-0.107056573948872	0.0723745161823667	-1.47920261987127	0.139541227731388	   
df.mm.trans1:probe10	-0.281783867248349	0.0723745161823667	-3.89341279378394	0.000108414669815656	***
df.mm.trans1:probe11	1.35063998021847	0.0723745161823667	18.6618170519465	2.90556954892988e-63	***
df.mm.trans1:probe12	1.17907219537779	0.0723745161823667	16.2912618635931	9.46831552401797e-51	***
df.mm.trans1:probe13	0.970819635509107	0.0723745161823667	13.413832474719	1.23582373822494e-36	***
df.mm.trans1:probe14	0.562920431633854	0.0723745161823667	7.77788179219641	2.68288970112051e-14	***
df.mm.trans1:probe15	0.489197490364392	0.0723745161823667	6.75925057836283	2.94858087931494e-11	***
df.mm.trans1:probe16	0.242307340382199	0.0723745161823667	3.34796490758766	0.00085815460053686	***
df.mm.trans1:probe17	-0.247316883423889	0.0723745161823667	-3.41718185446254	0.00066975721150889	***
df.mm.trans1:probe18	-0.133484630403465	0.0723745161823667	-1.84435955422646	0.0655580008951223	.  
df.mm.trans1:probe19	0.122260535310318	0.0723745161823667	1.68927602917925	0.0916170013857936	.  
df.mm.trans1:probe20	-0.219640221065008	0.0723745161823667	-3.03477290972926	0.00249740039574308	** 
df.mm.trans1:probe21	-0.165683366552810	0.0723745161823667	-2.28925007436770	0.0223651431671616	*  
df.mm.trans1:probe22	-0.160676318551786	0.0723745161823667	-2.22006760151488	0.0267374412554288	*  
df.mm.trans2:probe2	-0.129555905668377	0.0723745161823667	-1.79007629345565	0.0738787402585951	.  
df.mm.trans2:probe3	-0.572062783758984	0.0723745161823667	-7.904201836977	1.06494929206616e-14	***
df.mm.trans2:probe4	-1.12926622743120	0.0723745161823667	-15.6030919030355	2.98413267401213e-47	***
df.mm.trans2:probe5	-1.47998565505669	0.0723745161823667	-20.4489885822170	4.63305998310658e-73	***
df.mm.trans2:probe6	-1.09482672629104	0.0723745161823667	-15.1272406924606	7.11619119252738e-45	***
df.mm.trans3:probe2	0.418430432039675	0.0723745161823667	5.7814608526754	1.12076958944963e-08	***
df.mm.trans3:probe3	0.159825873969780	0.0723745161823667	2.20831699333307	0.0275492939924917	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.14446836452847	0.33608909020723	15.3068591466519	9.09984417828985e-46	***
df.mm.trans1	-0.0561423632107574	0.301857152345445	-0.185989839149175	0.852507234979694	   
df.mm.trans2	-0.202514684564323	0.2775986475423	-0.729523311288697	0.465928467636451	   
df.mm.exp2	-0.132735345364590	0.380241399629359	-0.349081781978434	0.727134105088126	   
df.mm.exp3	-0.284833757136591	0.380241399629359	-0.749086652358825	0.454059528770763	   
df.mm.exp4	-0.185790340629951	0.380241399629359	-0.488611552584885	0.625271535808239	   
df.mm.exp5	-0.0773031712795612	0.380241399629359	-0.203300249144129	0.838960125513232	   
df.mm.exp6	-0.266181678900111	0.380241399629359	-0.700033397624697	0.484141714749753	   
df.mm.exp7	0.232080263123644	0.380241399629359	0.610349802388337	0.541830501119635	   
df.mm.exp8	-0.216730911959464	0.380241399629359	-0.569982416882334	0.568874619406934	   
df.mm.trans1:exp2	-0.0499254665425795	0.364053423496359	-0.137137747704984	0.890961805536886	   
df.mm.trans2:exp2	0.291283771214103	0.316867833024466	0.919259517237309	0.358280158207885	   
df.mm.trans1:exp3	0.131447582143352	0.364053423496360	0.361066738175217	0.718159758362334	   
df.mm.trans2:exp3	0.143726978532872	0.316867833024466	0.453586522686808	0.650268661851346	   
df.mm.trans1:exp4	-0.0091622268944694	0.364053423496359	-0.0251672592623237	0.979928807526602	   
df.mm.trans2:exp4	0.208963203104415	0.316867833024466	0.659464866186908	0.509816699490049	   
df.mm.trans1:exp5	-0.00853638046413414	0.36405342349636	-0.0234481532467157	0.981299554450001	   
df.mm.trans2:exp5	0.244340980894796	0.316867833024466	0.771113238483659	0.440903023367943	   
df.mm.trans1:exp6	0.117760789865765	0.364053423496360	0.323471178308924	0.746436160233057	   
df.mm.trans2:exp6	0.086386029413989	0.316867833024466	0.272624799398047	0.785222976937099	   
df.mm.trans1:exp7	-0.440122486907669	0.364053423496359	-1.20895027625546	0.227094854089271	   
df.mm.trans2:exp7	-0.173894415515923	0.316867833024466	-0.548791632953466	0.583325470265285	   
df.mm.trans1:exp8	0.0629556035356881	0.364053423496360	0.172929574267052	0.862757351840364	   
df.mm.trans2:exp8	0.0412046109617569	0.316867833024466	0.130037216363882	0.896574771887908	   
df.mm.trans1:probe2	0.0179341034750661	0.18202671174818	0.0985245698437742	0.921544294609475	   
df.mm.trans1:probe3	-0.0259689616818212	0.182026711748180	-0.142665663915015	0.886595763842867	   
df.mm.trans1:probe4	0.0154893447384949	0.182026711748180	0.0850938007380107	0.932211431125527	   
df.mm.trans1:probe5	0.196720686046124	0.182026711748180	1.08072427478815	0.280196274386857	   
df.mm.trans1:probe6	-0.129880036370913	0.182026711748180	-0.713521851400535	0.475763459971066	   
df.mm.trans1:probe7	0.0716992105165255	0.182026711748180	0.393893895175758	0.693780720082543	   
df.mm.trans1:probe8	-0.048101469931069	0.182026711748180	-0.264255006691621	0.791662108005485	   
df.mm.trans1:probe9	0.134698123004214	0.182026711748180	0.739990970064652	0.459556444924108	   
df.mm.trans1:probe10	0.0840160287900385	0.182026711748180	0.461558789823486	0.644542803886658	   
df.mm.trans1:probe11	-0.104824890993163	0.182026711748180	-0.575876419380584	0.564885942994087	   
df.mm.trans1:probe12	-0.0768146993875819	0.182026711748180	-0.421996852274348	0.673158383274802	   
df.mm.trans1:probe13	0.0777807502875026	0.182026711748180	0.427304045326635	0.669290811120518	   
df.mm.trans1:probe14	-0.285941072835045	0.182026711748180	-1.57087424196633	0.116668961690559	   
df.mm.trans1:probe15	-0.0756004485112391	0.18202671174818	-0.415326123211117	0.678031924149881	   
df.mm.trans1:probe16	0.156725072450773	0.182026711748180	0.861000404531782	0.38953604259986	   
df.mm.trans1:probe17	0.00885313703599517	0.182026711748180	0.0486364718176243	0.961223037660408	   
df.mm.trans1:probe18	-0.0454535944045073	0.182026711748180	-0.249708375039972	0.802886987121422	   
df.mm.trans1:probe19	0.258669584856121	0.182026711748180	1.42105289038002	0.155751839145025	   
df.mm.trans1:probe20	0.201087924530932	0.182026711748180	1.10471656934133	0.269666379510602	   
df.mm.trans1:probe21	-0.140910825197241	0.182026711748180	-0.774121687108103	0.439123224391263	   
df.mm.trans1:probe22	0.0908405585237682	0.18202671174818	0.499050703335449	0.617902271412303	   
df.mm.trans2:probe2	0.235637757696055	0.182026711748180	1.29452296002601	0.195916638389446	   
df.mm.trans2:probe3	0.103019814546068	0.182026711748180	0.565959872354275	0.571604534564134	   
df.mm.trans2:probe4	0.260001844609074	0.182026711748180	1.42837192471381	0.153636010665427	   
df.mm.trans2:probe5	0.281514520846397	0.182026711748180	1.54655609686479	0.122427502085712	   
df.mm.trans2:probe6	-0.0483575723691774	0.18202671174818	-0.265661956449977	0.790578689930196	   
df.mm.trans3:probe2	0.197886129800468	0.182026711748180	1.08712687220450	0.277359254843108	   
df.mm.trans3:probe3	0.417910277813162	0.182026711748180	2.29587335726478	0.0219812254917112	*