chr6.20024_chr6_74130790_74138673_+_2.R 

fitVsDatCorrelation=0.927839565003056
cont.fitVsDatCorrelation=0.246949240888329

fstatistic=8256.71459732079,66,1014
cont.fstatistic=1210.13163236793,66,1014

residuals=-0.964779543421933,-0.105260425508746,0.00485312213153573,0.115268898303354,0.741385059098862
cont.residuals=-0.91695012743382,-0.360770659628485,-0.131236270493140,0.269976966692093,1.85410783893572

predictedValues:
Include	Exclude	Both
chr6.20024_chr6_74130790_74138673_+_2.R.tl.Lung	62.9890456995093	161.90601018202	68.0495372998767
chr6.20024_chr6_74130790_74138673_+_2.R.tl.cerebhem	62.139733920526	165.211111318727	70.0266394515924
chr6.20024_chr6_74130790_74138673_+_2.R.tl.cortex	60.0666580779552	246.436285065653	86.5211983526666
chr6.20024_chr6_74130790_74138673_+_2.R.tl.heart	63.9422620685062	494.717835037334	134.724578164428
chr6.20024_chr6_74130790_74138673_+_2.R.tl.kidney	66.4589609143018	338.526202526733	115.208903028686
chr6.20024_chr6_74130790_74138673_+_2.R.tl.liver	65.5973570831744	256.769813884263	91.4435449857882
chr6.20024_chr6_74130790_74138673_+_2.R.tl.stomach	66.9135995659566	220.286614276871	76.6785032907752
chr6.20024_chr6_74130790_74138673_+_2.R.tl.testicle	63.666930004568	262.250403176577	83.4139910666647


diffExp=-98.9169644825105,-103.071377398201,-186.369626987698,-430.775572968828,-272.067241612432,-191.172456801089,-153.373014710914,-198.583473172009
diffExpScore=0.999388502524722
diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.888888888888889
diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.4Score=0.888888888888889
diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.3Score=0.888888888888889
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	89.9395228165136	89.0704337818219	92.3863670850762
cerebhem	85.6567280241666	76.734988996661	79.7001807752133
cortex	82.6460063137812	92.2734404102194	94.2716617501434
heart	83.9218369393345	113.254298557314	92.1578303970037
kidney	89.3553019139628	101.851424110063	87.1893122271389
liver	85.3738945473769	76.2206153060883	88.0412075471252
stomach	91.4564139825119	109.763319013932	83.4572298126025
testicle	81.203935717164	96.3351923667589	89.1110076283388
cont.diffExp=0.869089034691768,8.92173902750561,-9.62743409643825,-29.3324616179791,-12.4961221961005,9.15327924128857,-18.3069050314200,-15.1312566495949
cont.diffExpScore=1.55098095261591

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

tran.correlation=0.223908549029660
cont.tran.correlation=0.179685295349694

tran.covariance=0.00367246922083134
cont.tran.covariance=0.00105225430754710

tran.mean=166.117426425167
cont.tran.mean=90.3160845498544

weightedLogRatios:
wLogRatio
Lung	-4.35680357072001
cerebhem	-4.51595629125186
cortex	-6.77771890438667
heart	-10.6003298767121
kidney	-8.1573300299084
liver	-6.6401665046939
stomach	-5.71833695720966
testicle	-6.8820824349251

cont.weightedLogRatios:
wLogRatio
Lung	0.0436396094331464
cerebhem	0.48344480815275
cortex	-0.492511297802043
heart	-1.37278268654768
kidney	-0.596626224116613
liver	0.49790100665092
stomach	-0.84062839198733
testicle	-0.765907385216597

varWeightedLogRatios=4.0861628926634
cont.varWeightedLogRatios=0.443146046938888

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.62589742661729	0.0898369726241977	51.4921339343006	3.29825605752226e-285	***
df.mm.trans1	-0.580205047517068	0.0767986446575542	-7.55488654915992	9.34332179011068e-14	***
df.mm.trans2	0.61558302898434	0.0670786447012487	9.17703438592106	2.41883193412955e-19	***
df.mm.exp2	-0.0220068792297496	0.084529356729278	-0.260345991987506	0.794649755609854	   
df.mm.exp3	0.132428056955208	0.084529356729278	1.56665165901279	0.117508135106102	   
df.mm.exp4	0.448994671450688	0.084529356729278	5.31170103291668	1.33481034031717e-07	***
df.mm.exp5	0.264698210030726	0.084529356729278	3.13143528204615	0.00178935916927203	** 
df.mm.exp6	0.206252750702053	0.084529356729278	2.44001325317805	0.0148571456687472	*  
df.mm.exp7	0.248969433386819	0.084529356729278	2.94536055898536	0.0032994736507851	** 
df.mm.exp8	0.289408119703630	0.084529356729278	3.42375869049278	0.000642320265433799	***
df.mm.trans1:exp2	0.00843166776248024	0.0771136096620464	0.109340851756679	0.91295377974986	   
df.mm.trans2:exp2	0.0422150150544983	0.052440123168209	0.805013651838455	0.42100051525488	   
df.mm.trans1:exp3	-0.179933976922879	0.0771136096620464	-2.33336213557434	0.0198238727388653	*  
df.mm.trans2:exp3	0.287659441881866	0.052440123168209	5.48548371938711	5.20707694028415e-08	***
df.mm.trans1:exp4	-0.433974983944979	0.0771136096620464	-5.62773530958922	2.36206286503192e-08	***
df.mm.trans2:exp4	0.667976915562519	0.052440123168209	12.7378975335334	1.39157847599948e-34	***
df.mm.trans1:exp5	-0.211074415467181	0.0771136096620464	-2.73718759103904	0.00630508518878403	** 
df.mm.trans2:exp5	0.472887304286821	0.052440123168209	9.0176619679166	9.38896411197832e-19	***
df.mm.trans1:exp6	-0.165678177417323	0.0771136096620464	-2.14849464502329	0.0319107615023645	*  
df.mm.trans2:exp6	0.254911284226003	0.052440123168209	4.86099705388447	1.35276379821657e-06	***
df.mm.trans1:exp7	-0.188528038396753	0.0771136096620464	-2.44480888941634	0.0146622335072513	*  
df.mm.trans2:exp7	0.0589440744368859	0.052440123168209	1.12402623937046	0.261267918865016	   
df.mm.trans1:exp8	-0.278703677623731	0.0771136096620464	-3.61419571519426	0.000316082869379006	***
df.mm.trans2:exp8	0.192875682147655	0.052440123168209	3.67801733662943	0.000247401062163224	***
df.mm.trans1:probe2	0.386242489952283	0.0574145819751085	6.72725423864855	2.88507504556989e-11	***
df.mm.trans1:probe3	1.08574743303368	0.0574145819751085	18.9106564165946	1.49402218157382e-68	***
df.mm.trans1:probe4	0.161398487210087	0.0574145819751085	2.81110619737786	0.00503226505589396	** 
df.mm.trans1:probe5	0.183333370746391	0.0574145819751085	3.19314997060979	0.00145063576755118	** 
df.mm.trans1:probe6	-0.0051112934898681	0.0574145819751085	-0.0890243090524294	0.929080170396686	   
df.mm.trans1:probe7	-0.1738053058861	0.0574145819751085	-3.02719796795615	0.00253068847792494	** 
df.mm.trans1:probe8	0.0930017490652933	0.0574145819751085	1.61982802740971	0.105580159248943	   
df.mm.trans1:probe9	0.0327664404159463	0.0574145819751085	0.570698928543132	0.568330189245981	   
df.mm.trans1:probe10	-0.189306731252617	0.0574145819751085	-3.29718905442330	0.00101047988586093	** 
df.mm.trans1:probe11	0.229732556252992	0.0574145819751085	4.00129284843684	6.75794110458153e-05	***
df.mm.trans1:probe12	0.124510587666971	0.0574145819751085	2.16862308117041	0.0303432132122962	*  
df.mm.trans1:probe13	0.0625228981898183	0.0574145819751085	1.08897245332073	0.276424772902187	   
df.mm.trans1:probe14	0.583282162656764	0.0574145819751085	10.1591293116031	3.70873810343136e-23	***
df.mm.trans1:probe15	0.185055732441023	0.0574145819751085	3.22314865100389	0.00130832769520405	** 
df.mm.trans1:probe16	0.681940179780073	0.0574145819751085	11.8774735671806	1.48037990808561e-30	***
df.mm.trans1:probe17	0.186831105519464	0.0574145819751085	3.25407064011130	0.00117523415786327	** 
df.mm.trans1:probe18	0.069590312788831	0.0574145819751085	1.21206687212320	0.225769129052411	   
df.mm.trans1:probe19	0.0465385092964508	0.0574145819751085	0.810569505088919	0.41780313013313	   
df.mm.trans1:probe20	-0.0339217857874530	0.0574145819751085	-0.59082178464975	0.554771499194771	   
df.mm.trans1:probe21	0.0251092599553788	0.0574145819751085	0.437332452690584	0.661963388079837	   
df.mm.trans1:probe22	0.0580115625473429	0.0574145819751085	1.01039771695095	0.312545819425685	   
df.mm.trans2:probe2	-1.28616138785762	0.0574145819751085	-22.4013019621952	1.29163784923187e-90	***
df.mm.trans2:probe3	-1.04338317289086	0.0574145819751085	-18.172790552463	4.20860541157841e-64	***
df.mm.trans2:probe4	-0.701282214646496	0.0574145819751085	-12.2143572333337	4.15116685051883e-32	***
df.mm.trans2:probe5	-0.38977953317543	0.0574145819751085	-6.78885955042597	1.92091296895197e-11	***
df.mm.trans2:probe6	-0.132076565892877	0.0574145819751085	-2.30040107145843	0.0216277791411949	*  
df.mm.trans3:probe2	-0.339678465235233	0.0574145819751085	-5.91624032693467	4.50010109245386e-09	***
df.mm.trans3:probe3	0.0954938347311266	0.0574145819751085	1.66323312730078	0.096574793021959	.  
df.mm.trans3:probe4	-0.368461360703601	0.0574145819751085	-6.41755714364242	2.12219699643485e-10	***
df.mm.trans3:probe5	-0.42311588584744	0.0574145819751085	-7.36948474223634	3.54763882310476e-13	***
df.mm.trans3:probe6	-0.925156882504498	0.0574145819751085	-16.1136221962844	3.49573517564048e-52	***
df.mm.trans3:probe7	-0.177147496612697	0.0574145819751085	-3.08540949909724	0.00208782554775355	** 
df.mm.trans3:probe8	-0.899827858696124	0.0574145819751085	-15.6724620774255	9.78999316822385e-50	***
df.mm.trans3:probe9	-0.00309464096944516	0.0574145819751085	-0.053899912931297	0.957025523127273	   
df.mm.trans3:probe10	-0.315837083151249	0.0574145819751085	-5.50099072894368	4.78132188499635e-08	***
df.mm.trans3:probe11	-0.0553124334557862	0.0574145819751085	-0.963386504838899	0.335583281672428	   
df.mm.trans3:probe12	-0.516535529340614	0.0574145819751085	-8.99659131132493	1.12163572477004e-18	***
df.mm.trans3:probe13	-0.976590324334273	0.0574145819751085	-17.0094476131110	2.84642009356909e-57	***
df.mm.trans3:probe14	-0.427053559464393	0.0574145819751085	-7.43806790493637	2.17292095238827e-13	***
df.mm.trans3:probe15	-0.96451546526947	0.0574145819751085	-16.7991376422043	4.60256484459879e-56	***
df.mm.trans3:probe16	-0.909126121609493	0.0574145819751085	-15.8344115786410	1.25052563872798e-50	***
df.mm.trans3:probe17	-0.291711860748399	0.0574145819751085	-5.08079743356605	4.47261263103792e-07	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.51639033292047	0.233403092251476	19.3501735103593	3.0475181672582e-71	***
df.mm.trans1	0.0385899848504136	0.199528552890787	0.193405827343097	0.84667988517802	   
df.mm.trans2	0.00680682070792699	0.174275274867093	0.0390578681520833	0.96885193991708	   
df.mm.exp2	-0.0501517934560938	0.219613514016917	-0.228363876788705	0.819409413052205	   
df.mm.exp3	-0.0694432808592519	0.219613514016917	-0.316206774296698	0.751910643725317	   
df.mm.exp4	0.173433420133864	0.219613514016917	0.789721073906703	0.429875308401065	   
df.mm.exp5	0.185468448443396	0.219613514016917	0.844522019847603	0.398576967986265	   
df.mm.exp6	-0.159718132586573	0.219613514016917	-0.727269145077612	0.467228970288071	   
df.mm.exp7	0.327269130493193	0.219613514016917	1.49020488087078	0.136481352493361	   
df.mm.exp8	0.0123290454332026	0.219613514016917	0.0561397393434216	0.955241546063316	   
df.mm.trans1:exp2	0.00136209191810865	0.200346855242838	0.00679866882091897	0.994576826184851	   
df.mm.trans2:exp2	-0.098917869865405	0.136243314394718	-0.726038340338847	0.467982811045483	   
df.mm.trans1:exp3	-0.0151276922563030	0.200346855242838	-0.075507510402232	0.93982581609585	   
df.mm.trans2:exp3	0.104772180536022	0.136243314394718	0.769007866562032	0.442067718715457	   
df.mm.trans1:exp4	-0.242685042865844	0.200346855242838	-1.21132444315978	0.226053305014443	   
df.mm.trans2:exp4	0.0667748523103844	0.136243314394718	0.490114708432057	0.624158755703867	   
df.mm.trans1:exp5	-0.191985345638619	0.200346855242838	-0.958264832287564	0.338157652270818	   
df.mm.trans2:exp5	-0.0513807709971177	0.136243314394718	-0.377125081149007	0.706159563451296	   
df.mm.trans1:exp6	0.107621026440436	0.200346855242838	0.537173524934992	0.591265607807383	   
df.mm.trans2:exp6	0.0039226532093745	0.136243314394718	0.0287915280599382	0.977036523141353	   
df.mm.trans1:exp7	-0.310544097372984	0.200346855242838	-1.5500323027111	0.121445797909054	   
df.mm.trans2:exp7	-0.118370175697788	0.136243314394718	-0.868814563295573	0.385154154728303	   
df.mm.trans1:exp8	-0.114502805769672	0.200346855242838	-0.571522850363112	0.567771932307322	   
df.mm.trans2:exp8	0.0660772041952098	0.136243314394718	0.484994104031951	0.627785284096844	   
df.mm.trans1:probe2	0.00714819371307497	0.149167325900146	0.0479206399252611	0.961788926452238	   
df.mm.trans1:probe3	-0.071873360343121	0.149167325900146	-0.481830453883941	0.630030367743462	   
df.mm.trans1:probe4	-0.268083668221778	0.149167325900146	-1.79720100634663	0.0726011817417293	.  
df.mm.trans1:probe5	-0.177164977669127	0.149167325900146	-1.18769292537779	0.235232541992271	   
df.mm.trans1:probe6	-0.0180682170530334	0.149167325900146	-0.121127176772804	0.903614301380257	   
df.mm.trans1:probe7	-0.101756918592589	0.149167325900146	-0.682166271859736	0.495289610945419	   
df.mm.trans1:probe8	-0.237353419325732	0.149167325900146	-1.59118907504328	0.111878717924235	   
df.mm.trans1:probe9	-0.261766650758340	0.149167325900146	-1.75485247307825	0.0795865378047971	.  
df.mm.trans1:probe10	-0.212008332961607	0.149167325900146	-1.42127863245016	0.155543232624842	   
df.mm.trans1:probe11	0.00906304411723343	0.149167325900146	0.0607575691428585	0.951564255346364	   
df.mm.trans1:probe12	-0.025261309736905	0.149167325900146	-0.169348814054729	0.865556059415842	   
df.mm.trans1:probe13	-0.268508215771262	0.149167325900146	-1.80004712259174	0.0721503332495207	.  
df.mm.trans1:probe14	-0.189302586972805	0.149167325900146	-1.26906201361769	0.204710165032091	   
df.mm.trans1:probe15	0.0744543543346658	0.149167325900146	0.499133130431703	0.617793867708815	   
df.mm.trans1:probe16	-0.139873764619097	0.149167325900146	-0.93769707122544	0.348623394914213	   
df.mm.trans1:probe17	-0.218194264050675	0.149167325900146	-1.46274837826574	0.143846114949945	   
df.mm.trans1:probe18	0.0388897507217954	0.149167325900146	0.260712260457284	0.79436734597096	   
df.mm.trans1:probe19	0.0309198223784839	0.149167325900146	0.207282809367930	0.835830617616196	   
df.mm.trans1:probe20	0.0414195407310176	0.149167325900146	0.277671671601489	0.781321010443956	   
df.mm.trans1:probe21	-0.138466144214910	0.149167325900146	-0.928260551560739	0.353493335774317	   
df.mm.trans1:probe22	-0.052083714414336	0.149167325900146	-0.349163022800324	0.727039418094045	   
df.mm.trans2:probe2	-0.189203385360026	0.149167325900146	-1.26839697781189	0.204947342999042	   
df.mm.trans2:probe3	-0.105239159683966	0.149167325900146	-0.705510801704753	0.480654450679963	   
df.mm.trans2:probe4	-0.127082271886924	0.149167325900146	-0.851944426301468	0.394446098564495	   
df.mm.trans2:probe5	-0.264493309588202	0.149167325900146	-1.77313166936609	0.0765070252026091	.  
df.mm.trans2:probe6	-0.0906851131795429	0.149167325900146	-0.607942206058239	0.543361939504908	   
df.mm.trans3:probe2	-0.0113593066048889	0.149167325900146	-0.0761514395752657	0.939313637727339	   
df.mm.trans3:probe3	0.112578128535756	0.149167325900146	0.754710375455256	0.450598021476179	   
df.mm.trans3:probe4	-0.163414522842924	0.149167325900146	-1.0955115127043	0.273552733968689	   
df.mm.trans3:probe5	-0.0594649944753325	0.149167325900146	-0.398646245861771	0.690237810123693	   
df.mm.trans3:probe6	0.0495803983557363	0.149167325900146	0.332381089870351	0.739670213075306	   
df.mm.trans3:probe7	-0.147227159696959	0.149167325900146	-0.986993356678625	0.323881344116514	   
df.mm.trans3:probe8	-0.136041227877956	0.149167325900146	-0.912004201034103	0.361983272902968	   
df.mm.trans3:probe9	0.00425758495000005	0.149167325900146	0.0285423427973102	0.977235213463432	   
df.mm.trans3:probe10	-0.0964016276142838	0.149167325900146	-0.646265038489837	0.518253961563214	   
df.mm.trans3:probe11	-0.0431128390542120	0.149167325900146	-0.289023342035857	0.772622592506277	   
df.mm.trans3:probe12	0.0317677568723457	0.149167325900146	0.212967261299645	0.83139530557515	   
df.mm.trans3:probe13	0.0458005127096669	0.149167325900146	0.307041186354217	0.758875066001754	   
df.mm.trans3:probe14	0.00901873612391554	0.149167325900146	0.0604605336288778	0.951800761745476	   
df.mm.trans3:probe15	0.0144752383961177	0.149167325900146	0.0970402754676153	0.922713586511236	   
df.mm.trans3:probe16	-0.29481995906384	0.149167325900146	-1.97643791818857	0.0483758551955843	*  
df.mm.trans3:probe17	0.0756321588262058	0.149167325900146	0.50702899156907	0.612244718583868