chr5.18159_chr5_137321522_137326651_-_2.R 

fitVsDatCorrelation=0.85155825107804
cont.fitVsDatCorrelation=0.259855595449302

fstatistic=7338.56075481886,59,853
cont.fstatistic=2152.85651334573,59,853

residuals=-0.715826402236827,-0.110256736105135,-0.00676624179754501,0.083711934651054,1.51249954039835
cont.residuals=-0.706179924145136,-0.264179706660065,-0.0526826427252238,0.221959246131932,1.97094058135597

predictedValues:
Include	Exclude	Both
chr5.18159_chr5_137321522_137326651_-_2.R.tl.Lung	71.998332974136	107.408403950595	66.1993010629011
chr5.18159_chr5_137321522_137326651_-_2.R.tl.cerebhem	83.6147926219261	116.599570048044	70.4262706605605
chr5.18159_chr5_137321522_137326651_-_2.R.tl.cortex	66.3090658286194	87.5633042861105	75.641932643615
chr5.18159_chr5_137321522_137326651_-_2.R.tl.heart	65.5171096662462	85.467488246091	68.3444753755983
chr5.18159_chr5_137321522_137326651_-_2.R.tl.kidney	71.0666168772752	112.465648132315	62.8932523406013
chr5.18159_chr5_137321522_137326651_-_2.R.tl.liver	68.5471703111746	102.803029226467	59.7675779590476
chr5.18159_chr5_137321522_137326651_-_2.R.tl.stomach	77.9164548564638	96.09260283806	61.6945155595466
chr5.18159_chr5_137321522_137326651_-_2.R.tl.testicle	69.1662730782843	88.6925447272448	67.3062813427122


diffExp=-35.410070976459,-32.9847774261184,-21.2542384574911,-19.9503785798448,-41.39903125504,-34.2558589152922,-18.1761479815961,-19.5262716489604
diffExpScore=0.995534852656613
diffExp1.5=0,0,0,0,-1,0,0,0
diffExp1.5Score=0.5
diffExp1.4=-1,0,0,0,-1,-1,0,0
diffExp1.4Score=0.75
diffExp1.3=-1,-1,-1,-1,-1,-1,0,0
diffExp1.3Score=0.857142857142857
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	75.7454782122487	73.3496898043583	77.8088643146626
cerebhem	77.2251245084429	63.1278630730718	67.6729086987526
cortex	81.5466222768026	78.6307597821807	70.6955275479668
heart	84.1982842315035	64.7085538343023	76.935690878013
kidney	80.8012399240016	69.2743536123417	81.839668294503
liver	80.5313882868181	70.530647620702	74.6603623012972
stomach	80.4058500091777	64.6823395132519	71.2943067756466
testicle	83.417115147715	87.7020434958666	83.4345719947467
cont.diffExp=2.39578840789039,14.0972614353711,2.91586249462183,19.4897303972012,11.5268863116600,10.0007406661161,15.7235104959258,-4.28492834815162
cont.diffExpScore=1.10388900139098

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

tran.correlation=0.669449757342652
cont.tran.correlation=0.290365998931457

tran.covariance=0.00671358888772627
cont.tran.covariance=0.00108469806411301

tran.mean=85.7017754793158
cont.tran.mean=75.9923345832991

weightedLogRatios:
wLogRatio
Lung	-1.79063596587916
cerebhem	-1.52711604395154
cortex	-1.20482304286512
heart	-1.14709314726669
kidney	-2.06248328110791
liver	-1.79551491439660
stomach	-0.935250838770964
testicle	-1.08437840996935

cont.weightedLogRatios:
wLogRatio
Lung	0.138567496729554
cerebhem	0.855823458522122
cortex	0.159592404019125
heart	1.13251278226018
kidney	0.664159394467525
liver	0.573141903181594
stomach	0.930949942645699
testicle	-0.222852905813785

varWeightedLogRatios=0.166665571482525
cont.varWeightedLogRatios=0.215286268497300

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.69506129416144	0.0930473415666266	50.4588440154364	2.64380309645804e-258	***
df.mm.trans1	-0.581637765370372	0.0803534081623624	-7.23849527570894	1.01239294442271e-12	***
df.mm.trans2	-0.0402353680039055	0.0709918729205203	-0.566760198719527	0.57102621228374	   
df.mm.exp2	0.169788191054026	0.0913182475277757	1.85930189913448	0.0633285015744351	.  
df.mm.exp3	-0.419933646112199	0.0913182475277756	-4.59857320394230	4.89794870640484e-06	***
df.mm.exp4	-0.354724846224634	0.0913182475277756	-3.88449029441504	0.000110479762236653	***
df.mm.exp5	0.0842151573611064	0.0913182475277756	0.922216091975388	0.356676635605783	   
df.mm.exp6	0.00926211762879936	0.0913182475277756	0.101426800004919	0.919235498692432	   
df.mm.exp7	0.0381429735913098	0.0913182475277756	0.417692790038575	0.676276860800225	   
df.mm.exp8	-0.248175858632535	0.0913182475277756	-2.71770281790668	0.00670698707822962	** 
df.mm.trans1:exp2	-0.0202107069889979	0.084407355151369	-0.239442486413106	0.810820009738098	   
df.mm.trans2:exp2	-0.087681032641905	0.0623389631712244	-1.40652054800903	0.159933808733237	   
df.mm.trans1:exp3	0.337617307841528	0.084407355151369	3.9998564963453	6.88791882512894e-05	***
df.mm.trans2:exp3	0.215657227359682	0.0623389631712244	3.45942916579064	0.000568156172122312	***
df.mm.trans1:exp4	0.260393205422359	0.084407355151369	3.08495870952706	0.00210146488067792	** 
df.mm.trans2:exp4	0.126222467332710	0.0623389631712244	2.02477649469431	0.0432014076543589	*  
df.mm.trans1:exp5	-0.0972404199499825	0.084407355151369	-1.15203728129616	0.249628526993775	   
df.mm.trans2:exp5	-0.0382057603682977	0.0623389631712244	-0.612871283459739	0.540124812145117	   
df.mm.trans1:exp6	-0.0583829572786209	0.084407355151369	-0.691680922520577	0.489325943956611	   
df.mm.trans2:exp6	-0.0530857259462606	0.0623389631712244	-0.851565750306944	0.394694156672846	   
df.mm.trans1:exp7	0.0408512218749491	0.084407355151369	0.483977039698614	0.62852638997269	   
df.mm.trans2:exp7	-0.149469062254974	0.0623389631712244	-2.39768283993483	0.0167132171262946	*  
df.mm.trans1:exp8	0.208046253573528	0.084407355151369	2.46478820714659	0.0139054806304944	*  
df.mm.trans2:exp8	0.0567132659020774	0.0623389631712244	0.909756322804165	0.363208019016067	   
df.mm.trans1:probe2	0.072468026329108	0.0577897655446933	1.25399412242057	0.210187685228016	   
df.mm.trans1:probe3	-0.146072513591437	0.0577897655446933	-2.52765368079695	0.0116623099409825	*  
df.mm.trans1:probe4	0.00152134769186673	0.0577897655446933	0.0263255557022489	0.979003828839263	   
df.mm.trans1:probe5	0.0119414033762826	0.0577897655446933	0.206635262554359	0.836344031462618	   
df.mm.trans1:probe6	0.674803860332629	0.0577897655446933	11.6768748578976	2.49276045715816e-29	***
df.mm.trans1:probe7	-0.230994988156313	0.0577897655446933	-3.99716084637281	6.96533210606381e-05	***
df.mm.trans1:probe8	0.0935460565291057	0.0577897655446933	1.61873050785713	0.105874918048398	   
df.mm.trans1:probe9	0.545501894502128	0.0577897655446933	9.43942044686526	3.47196375010225e-20	***
df.mm.trans1:probe10	0.703519831055422	0.0577897655446933	12.1737789455355	1.49883962311416e-31	***
df.mm.trans1:probe11	0.50675919620558	0.0577897655446933	8.76901284213836	9.6543478304019e-18	***
df.mm.trans1:probe12	0.401173816701939	0.0577897655446933	6.94195266100674	7.65833029932434e-12	***
df.mm.trans1:probe13	0.765838214149663	0.0577897655446933	13.2521426057246	1.38323150197896e-36	***
df.mm.trans1:probe14	0.469414440925582	0.0577897655446933	8.12279538601948	1.59116937051992e-15	***
df.mm.trans1:probe15	0.658473127622832	0.0577897655446933	11.3942861926578	4.26955466524972e-28	***
df.mm.trans1:probe16	0.892038382714709	0.0577897655446933	15.4359232003602	1.37097385603981e-47	***
df.mm.trans1:probe17	-0.078308814617331	0.0577897655446933	-1.35506371896887	0.175755991292739	   
df.mm.trans1:probe18	-0.208745239433598	0.0577897655446933	-3.61214892405403	0.000321418880823085	***
df.mm.trans1:probe19	0.0409089616369743	0.0577897655446933	0.707892846620674	0.479205176811651	   
df.mm.trans1:probe20	0.134058240782197	0.0577897655446933	2.31975747813892	0.0205892507000402	*  
df.mm.trans1:probe21	-0.100321786033765	0.0577897655446933	-1.73597842261841	0.0829287389324656	.  
df.mm.trans1:probe22	0.0154985195146624	0.0577897655446933	0.268187963190060	0.788619480626124	   
df.mm.trans2:probe2	0.0819942934930492	0.0577897655446933	1.41883762150993	0.156311635565636	   
df.mm.trans2:probe3	0.00314356132540823	0.0577897655446933	0.0543965059518553	0.956631999923875	   
df.mm.trans2:probe4	-0.098842696011735	0.0577897655446933	-1.71038409794710	0.0875584924839185	.  
df.mm.trans2:probe5	0.207039970805160	0.0577897655446933	3.58264078169758	0.000359404166514142	***
df.mm.trans2:probe6	0.155664901274014	0.0577897655446933	2.69364133608790	0.00720640723634796	** 
df.mm.trans3:probe2	0.0350752018234795	0.0577897655446933	0.606944871516275	0.544049011012903	   
df.mm.trans3:probe3	0.187336840094306	0.0577897655446933	3.2416957973194	0.00123430582764843	** 
df.mm.trans3:probe4	0.230645287096011	0.0577897655446933	3.99110958354097	7.14212523661667e-05	***
df.mm.trans3:probe5	0.302483211491372	0.0577897655446933	5.23420035780278	2.08752237835224e-07	***
df.mm.trans3:probe6	0.0521081486978128	0.0577897655446933	0.901684722314949	0.367478893146057	   
df.mm.trans3:probe7	0.0905681227453844	0.0577897655446933	1.56720003778768	0.117438814156743	   
df.mm.trans3:probe8	0.182512148446318	0.0577897655446933	3.15820884071882	0.00164328389003417	** 
df.mm.trans3:probe9	0.0637881803489758	0.0577897655446933	1.10379718186680	0.269992409743912	   
df.mm.trans3:probe10	0.0503003006347577	0.0577897655446933	0.87040153495443	0.384325883587646	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.35295089725518	0.171386205308359	25.3984904410675	2.00586121304255e-106	***
df.mm.trans1	0.0255312806422294	0.148004934656622	0.172502901348952	0.863083100595114	   
df.mm.trans2	-0.107582532920174	0.130761690798753	-0.822737395509417	0.410887278470624	   
df.mm.exp2	0.0088394976258766	0.168201344129625	0.0525530736488315	0.958100311552355	   
df.mm.exp3	0.239193903806261	0.168201344129625	1.42206892010284	0.155371784318899	   
df.mm.exp4	-0.00826360808080641	0.168201344129624	-0.0491292630482076	0.96082778387903	   
df.mm.exp5	-0.0430566603183262	0.168201344129625	-0.255982855197308	0.798025793736492	   
df.mm.exp6	0.063383369515404	0.168201344129624	0.376830338921416	0.706393413743888	   
df.mm.exp7	0.0213970013795408	0.168201344129624	0.127210644422979	0.898803661912145	   
df.mm.exp8	0.205374287473459	0.168201344129624	1.22100265331522	0.222422399155781	   
df.mm.trans1:exp2	0.0105066044189494	0.155472000123179	0.0675787563717268	0.946136803383475	   
df.mm.trans2:exp2	-0.158915531046481	0.114823681804207	-1.38399612823301	0.166721643214636	   
df.mm.trans1:exp3	-0.165397743683055	0.155472000123179	-1.06384264402601	0.287701051511477	   
df.mm.trans2:exp3	-0.169669210698247	0.114823681804207	-1.47764997631378	0.139870606690354	   
df.mm.trans1:exp4	0.114059402783337	0.155472000123179	0.73363308308228	0.463373975790428	   
df.mm.trans2:exp4	-0.117081267111699	0.114823681804207	-1.01966132135827	0.308178217015919	   
df.mm.trans1:exp5	0.10767022228164	0.155472000123179	0.692537705801261	0.488788201670808	   
df.mm.trans2:exp5	-0.0141068553260836	0.114823681804207	-0.122856671240851	0.902249536656552	   
df.mm.trans1:exp6	-0.00211509352224821	0.155472000123179	-0.0136043372476873	0.989148825323974	   
df.mm.trans2:exp6	-0.102574311736156	0.114823681804207	-0.89332017685221	0.371937693632853	   
df.mm.trans1:exp7	0.0383111844265116	0.155472000123179	0.246418547366458	0.805417536316624	   
df.mm.trans2:exp7	-0.147147072343261	0.114823681804207	-1.28150456448671	0.20036473870089	   
df.mm.trans1:exp8	-0.108899530604581	0.155472000123179	-0.700444649314993	0.483840662978253	   
df.mm.trans2:exp8	-0.0266673629883026	0.114823681804207	-0.232246193200588	0.816402509230617	   
df.mm.trans1:probe2	0.0119573696297320	0.106444401909889	0.112334415104841	0.910584684468407	   
df.mm.trans1:probe3	-0.097666806715946	0.106444401909889	-0.917538216792522	0.359120025513035	   
df.mm.trans1:probe4	-0.0620714686246193	0.106444401909889	-0.583135115712014	0.559956478609076	   
df.mm.trans1:probe5	-0.137245918111470	0.106444401909889	-1.28936717806593	0.197619974492619	   
df.mm.trans1:probe6	-0.143935234667751	0.106444401909889	-1.35221046936409	0.176666380943325	   
df.mm.trans1:probe7	-0.0935205952296993	0.106444401909889	-0.878586318788935	0.379873030045996	   
df.mm.trans1:probe8	-0.109570913651935	0.106444401909889	-1.0293722514848	0.303596571271294	   
df.mm.trans1:probe9	-0.0549847738020314	0.106444401909889	-0.516558624178086	0.605598195128435	   
df.mm.trans1:probe10	-0.00353132715997208	0.106444401909889	-0.0331753206050379	0.973542539651596	   
df.mm.trans1:probe11	-0.119331759613220	0.106444401909889	-1.1210712585359	0.262573040381547	   
df.mm.trans1:probe12	-0.0517908417376569	0.106444401909889	-0.486552987366125	0.626700130236886	   
df.mm.trans1:probe13	-0.116659401284597	0.106444401909889	-1.09596558570882	0.273403161846922	   
df.mm.trans1:probe14	0.0129300579849222	0.106444401909889	0.121472409567092	0.903345475760899	   
df.mm.trans1:probe15	-0.0737285849128848	0.106444401909889	-0.69264877804753	0.488718512841458	   
df.mm.trans1:probe16	-0.191925002373373	0.106444401909889	-1.80305397869441	0.0717325416772206	.  
df.mm.trans1:probe17	-0.0325582220867723	0.106444401909889	-0.305870684625901	0.759777739362635	   
df.mm.trans1:probe18	-0.0993349675981542	0.106444401909889	-0.933209880612103	0.350975688380545	   
df.mm.trans1:probe19	-0.217199870160661	0.106444401909889	-2.04050063942802	0.0416079500687728	*  
df.mm.trans1:probe20	-0.0933852126956519	0.106444401909889	-0.877314457313665	0.380562881544327	   
df.mm.trans1:probe21	-0.00629751474014114	0.106444401909889	-0.0591624794460523	0.952836551388854	   
df.mm.trans1:probe22	0.0445412641173476	0.106444401909889	0.418446281045895	0.675726183998183	   
df.mm.trans2:probe2	0.00150235763487164	0.106444401909889	0.0141140126480627	0.988742321450601	   
df.mm.trans2:probe3	0.147127930149816	0.106444401909889	1.38220448900984	0.167270737166782	   
df.mm.trans2:probe4	0.246402218255237	0.106444401909889	2.31484431152922	0.0208580406745762	*  
df.mm.trans2:probe5	0.172086509876242	0.106444401909889	1.61667975758765	0.106317162749553	   
df.mm.trans2:probe6	0.230799564333581	0.106444401909889	2.16826399690766	0.0304144203648852	*  
df.mm.trans3:probe2	0.0536348335693919	0.106444401909889	0.503876508365341	0.614478267546292	   
df.mm.trans3:probe3	0.117771124722052	0.106444401909889	1.10640975578737	0.268861133900731	   
df.mm.trans3:probe4	0.165201445251368	0.106444401909889	1.55199749622549	0.121033745046314	   
df.mm.trans3:probe5	0.171859982338019	0.106444401909889	1.61455162746377	0.106777644361158	   
df.mm.trans3:probe6	0.0133966394617028	0.106444401909889	0.125855744607817	0.899875771590109	   
df.mm.trans3:probe7	0.163953756176177	0.106444401909889	1.54027598665990	0.123863958537222	   
df.mm.trans3:probe8	0.110998167765021	0.106444401909889	1.04278069840617	0.29734531536991	   
df.mm.trans3:probe9	0.0288490508143071	0.106444401909889	0.271024594029185	0.786437686684906	   
df.mm.trans3:probe10	0.00789216913418685	0.106444401909889	0.0741435809923382	0.940913521174488