chr7.21860_chr7_11229159_11239885_+_2.R 

fitVsDatCorrelation=0.948203785337702
cont.fitVsDatCorrelation=0.240474013223319

fstatistic=7137.8631121983,70,1106
cont.fstatistic=750.379593414931,70,1106

residuals=-0.999750445595687,-0.122303768207685,0.00336800732242349,0.116921259946694,0.971592730047673
cont.residuals=-1.42962691765041,-0.50282782218886,-0.199097334646352,0.383876274522792,2.29677645025055

predictedValues:
Include	Exclude	Both
chr7.21860_chr7_11229159_11239885_+_2.R.tl.Lung	139.912887060668	82.0939151037207	99.7294852646656
chr7.21860_chr7_11229159_11239885_+_2.R.tl.cerebhem	175.518266863366	80.0073780026172	128.735617761851
chr7.21860_chr7_11229159_11239885_+_2.R.tl.cortex	214.136215894988	74.549691297039	150.550689732647
chr7.21860_chr7_11229159_11239885_+_2.R.tl.heart	143.966694976269	75.6831052959374	103.105137170639
chr7.21860_chr7_11229159_11239885_+_2.R.tl.kidney	138.939051807944	74.227432918532	96.182525937081
chr7.21860_chr7_11229159_11239885_+_2.R.tl.liver	126.490050541935	73.0373391349415	88.8284241539931
chr7.21860_chr7_11229159_11239885_+_2.R.tl.stomach	134.995203624453	86.1426471280874	88.1838978984925
chr7.21860_chr7_11229159_11239885_+_2.R.tl.testicle	155.404301474251	75.3078487217343	107.072848519931


diffExp=57.8189719569477,95.5108888607489,139.586524597949,68.2835896803314,64.7116188894119,53.4527114069939,48.8525564963653,80.0964527525163
diffExpScore=0.998358808225635
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	107.076394070525	148.529037126309	101.408161086204
cerebhem	103.070669483006	114.151741819236	107.373485702963
cortex	114.922810336220	99.5623559919703	107.692748479038
heart	106.454418468723	92.1511667965164	92.696330020097
kidney	124.023809665017	102.849765814230	114.300834595259
liver	114.474860976801	93.711396360648	127.786743772920
stomach	113.056024374030	96.1404479516253	110.124968155527
testicle	131.354167719743	125.910390101383	122.185907309643
cont.diffExp=-41.4526430557832,-11.0810723362300,15.3604543442493,14.3032516722062,21.174043850787,20.7634646161525,16.9155764224044,5.44377761836034
cont.diffExpScore=3.45286706652243

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=-1,0,0,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=-1,0,0,0,1,1,0,0
cont.diffExp1.2Score=1.5

tran.correlation=-0.178299223575820
cont.tran.correlation=0.0191319471000681

tran.covariance=-0.00151545282294053
cont.tran.covariance=0.000380062798101417

tran.mean=115.650751865405
cont.tran.mean=111.714966065999

weightedLogRatios:
wLogRatio
Lung	2.49220721703037
cerebhem	3.75130165676136
cortex	5.10589487443858
heart	2.98883367453491
kidney	2.89665169489731
liver	2.50737686872803
stomach	2.10269750467951
testicle	3.39316427445802

cont.weightedLogRatios:
wLogRatio
Lung	-1.58290273067542
cerebhem	-0.478553286251861
cortex	0.670397383128217
heart	0.66307947224584
kidney	0.884890289752574
liver	0.9286859681316
stomach	0.753130097962846
testicle	0.205569911434337

varWeightedLogRatios=0.896956269982616
cont.varWeightedLogRatios=0.765179984795379

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.08784656650367	0.103269851777949	39.5841234990186	3.72006149945632e-214	***
df.mm.trans1	1.04066715887051	0.0880168828166444	11.8234948292637	1.84719552534086e-30	***
df.mm.trans2	0.325095766950977	0.076608863226244	4.24357904895276	2.38408460731085e-05	***
df.mm.exp2	-0.0543213675574285	0.0959094914144956	-0.566381561994379	0.571249332369969	   
df.mm.exp3	-0.082644119210574	0.0959094914144957	-0.861688639901214	0.389045657874712	   
df.mm.exp4	-0.0860347916779533	0.0959094914144956	-0.897041475344014	0.369892000861148	   
df.mm.exp5	-0.0715010582008559	0.0959094914144956	-0.745505550559612	0.456124558569413	   
df.mm.exp6	-0.101994750585822	0.0959094914144956	-1.06344793493928	0.287810993873519	   
df.mm.exp7	0.135396957356698	0.0959094914144956	1.41171593509497	0.158314884377747	   
df.mm.exp8	-0.0523174690543939	0.0959094914144956	-0.545487920776178	0.585527977560581	   
df.mm.trans1:exp2	0.281044496078809	0.0871141216927224	3.22616460589635	0.00129139079098342	** 
df.mm.trans2:exp2	0.0285763249671039	0.0574123326883149	0.497738441011299	0.61876735481268	   
df.mm.trans1:exp3	0.508236460951794	0.0871141216927224	5.83414549875732	7.0938874296416e-09	***
df.mm.trans2:exp3	-0.0137538785164956	0.0574123326883149	-0.239563136916312	0.810713333261902	   
df.mm.trans1:exp4	0.114596785956807	0.0871141216927224	1.31547886530986	0.188621647395454	   
df.mm.trans2:exp4	0.00472584945839832	0.0574123326883149	0.0823141864667723	0.93441176754497	   
df.mm.trans1:exp5	0.0645164253112566	0.0871141216927225	0.740596634134995	0.459095242682516	   
df.mm.trans2:exp5	-0.0292290421151588	0.0574123326883149	-0.509107377222242	0.610778511568202	   
df.mm.trans1:exp6	0.00113841015812206	0.0871141216927225	0.0130680323235947	0.989575872333416	   
df.mm.trans2:exp6	-0.0148983420800203	0.0574123326883149	-0.25949724357834	0.795299901697805	   
df.mm.trans1:exp7	-0.171177701916834	0.0871141216927224	-1.96498223928181	0.0496662921768558	*  
df.mm.trans2:exp7	-0.0872562457146534	0.0574123326883149	-1.51981711295999	0.128842754435928	   
df.mm.trans1:exp8	0.157327592959690	0.0871141216927224	1.80599413622778	0.0711910271312176	.  
df.mm.trans2:exp8	-0.0339620669237069	0.0574123326883149	-0.591546542936743	0.554275164503176	   
df.mm.trans1:probe2	-0.0185532102180028	0.0665345094594159	-0.278850935683530	0.780411352350823	   
df.mm.trans1:probe3	-1.06920942503834	0.0665345094594159	-16.0699978661529	2.19212714432411e-52	***
df.mm.trans1:probe4	-0.351738007362028	0.0665345094594159	-5.28654994558243	1.50115354688850e-07	***
df.mm.trans1:probe5	-0.793190454290223	0.0665345094594159	-11.921489475684	6.53467213339962e-31	***
df.mm.trans1:probe6	-1.01599038956875	0.0665345094594159	-15.2701267030227	6.50015240509268e-48	***
df.mm.trans1:probe7	-0.466971273915968	0.0665345094594159	-7.01848225394684	3.90432225162963e-12	***
df.mm.trans1:probe8	-0.099071963579087	0.0665345094594159	-1.48903124685270	0.136764220490756	   
df.mm.trans1:probe9	-1.01431362920340	0.0665345094594159	-15.2449253394150	8.94260729749665e-48	***
df.mm.trans1:probe10	-1.08475870672119	0.0665345094594159	-16.3037003734560	1.01769858145648e-53	***
df.mm.trans1:probe11	-1.23439428530003	0.0665345094594159	-18.5526923596390	4.14553762500169e-67	***
df.mm.trans1:probe12	-1.07842110595580	0.0665345094594159	-16.2084475367418	3.5681360794126e-53	***
df.mm.trans1:probe13	-1.05938890162023	0.0665345094594159	-15.9223974179359	1.50251771605198e-51	***
df.mm.trans1:probe14	-1.11192961494861	0.0665345094594159	-16.7120735387229	4.46843124194288e-56	***
df.mm.trans1:probe15	-1.0835602908253	0.0665345094594158	-16.2856884288933	1.29059913385818e-53	***
df.mm.trans1:probe16	-1.23497733593879	0.0665345094594159	-18.5614554908846	3.66074968261715e-67	***
df.mm.trans1:probe17	0.686832035415903	0.0665345094594158	10.3229443035851	6.48785200211684e-24	***
df.mm.trans1:probe18	1.00815930450175	0.0665345094594159	15.1524271042638	2.87536289953672e-47	***
df.mm.trans1:probe19	0.918878065696464	0.0665345094594159	13.8105484381297	3.84133943273037e-40	***
df.mm.trans1:probe20	1.24049587057061	0.0665345094594159	18.6443979319826	1.12643730825313e-67	***
df.mm.trans1:probe21	0.707876547635481	0.0665345094594159	10.6392389962274	3.09581896594305e-25	***
df.mm.trans1:probe22	0.0919963069406255	0.0665345094594159	1.38268558208490	0.167040401145950	   
df.mm.trans2:probe2	-0.155224645767559	0.0665345094594159	-2.33299451711209	0.019827015221669	*  
df.mm.trans2:probe3	-0.0242282333795537	0.0665345094594159	-0.364145367214771	0.715819063905854	   
df.mm.trans2:probe4	0.0406616938932757	0.0665345094594159	0.611136900589582	0.541234531959594	   
df.mm.trans2:probe5	0.00384586540894478	0.0665345094594159	0.0578025665206212	0.953916334903222	   
df.mm.trans2:probe6	-0.00217243623044751	0.0665345094594159	-0.0326512699664921	0.97395857532869	   
df.mm.trans3:probe2	-0.205107122542995	0.0665345094594159	-3.08271788894911	0.00210197977569209	** 
df.mm.trans3:probe3	-1.63020636557867	0.0665345094594159	-24.5016665610655	2.96195621410476e-106	***
df.mm.trans3:probe4	-0.406781067511476	0.0665345094594159	-6.11383582469486	1.34659030481925e-09	***
df.mm.trans3:probe5	-0.545269487977839	0.0665345094594159	-8.19528831591428	6.85981908573996e-16	***
df.mm.trans3:probe6	-1.14621549731538	0.0665345094594159	-17.2273833027136	4.23329788346665e-59	***
df.mm.trans3:probe7	-0.3443775919303	0.0665345094594159	-5.17592441468829	2.69200357591896e-07	***
df.mm.trans3:probe8	-1.32090433103997	0.0665345094594159	-19.8529205636616	2.91786063475476e-75	***
df.mm.trans3:probe9	-0.415504691905998	0.0665345094594159	-6.24495010607156	6.03437711771449e-10	***
df.mm.trans3:probe10	-0.73419738755438	0.0665345094594159	-11.0348358095616	6.2174202627924e-27	***
df.mm.trans3:probe11	-1.37983441952900	0.0665345094594159	-20.7386276796804	5.80037054427201e-81	***
df.mm.trans3:probe12	-0.771857687605545	0.0665345094594158	-11.6008623776862	1.91075784448501e-29	***
df.mm.trans3:probe13	-1.4193496220119	0.0665345094594159	-21.3325330500507	7.57923205741785e-85	***
df.mm.trans3:probe14	-1.40835216115048	0.0665345094594159	-21.1672434739981	9.22950077322713e-84	***
df.mm.trans3:probe15	-0.285539384063501	0.0665345094594159	-4.2915982455341	1.92924163542683e-05	***
df.mm.trans3:probe16	-0.630027639845834	0.0665345094594159	-9.46918591516982	1.64503437040074e-20	***
df.mm.trans3:probe17	-1.37625432272483	0.0665345094594159	-20.6848195606568	1.29719011800582e-80	***
df.mm.trans3:probe18	-1.43321384367713	0.0665345094594159	-21.5409094516786	3.20738217777287e-86	***
df.mm.trans3:probe19	-0.882630464663311	0.0665345094594159	-13.2657544458442	2.22306645811916e-37	***
df.mm.trans3:probe20	-0.627544934884165	0.0665345094594159	-9.4318713699535	2.28787629691684e-20	***
df.mm.trans3:probe21	-0.910942479971373	0.0665345094594159	-13.6912782159613	1.57014578036064e-39	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.31591786078571	0.315553139453349	16.8463475597003	7.37019053367223e-57	***
df.mm.trans1	-0.594237565455208	0.268945904535715	-2.20950590967745	0.0273437742860686	*  
df.mm.trans2	-0.340056794226411	0.234087363202311	-1.45269180520657	0.146592982863508	   
df.mm.exp2	-0.358539227292345	0.293062695434995	-1.22342158479148	0.221431093242533	   
df.mm.exp3	-0.389406867678066	0.293062695434995	-1.32874935549223	0.184204746233249	   
df.mm.exp4	-0.39335108434916	0.293062695434995	-1.34220796599617	0.179804024356285	   
df.mm.exp5	-0.340260419153570	0.293062695434995	-1.16104992021765	0.245872125028396	   
df.mm.exp6	-0.624957204536352	0.293062695434995	-2.13250343449112	0.0331852448004273	*  
df.mm.exp7	-0.463091632813821	0.293062695434995	-1.5801793951511	0.114351716072910	   
df.mm.exp8	-0.147245451832163	0.293062695434995	-0.502436694010495	0.61546039276932	   
df.mm.trans1:exp2	0.320411548753282	0.266187412081959	1.20370661500187	0.22896055906587	   
df.mm.trans2:exp2	0.0952873838580112	0.175430113544584	0.543164351505678	0.587126096654109	   
df.mm.trans1:exp3	0.460125013221065	0.266187412081959	1.72857540340560	0.084164198030778	.  
df.mm.trans2:exp3	-0.0105894663931875	0.175430113544584	-0.0603628771550462	0.951877529665818	   
df.mm.trans1:exp4	0.387525439296218	0.266187412081959	1.45583683415090	0.145721519670217	   
df.mm.trans2:exp4	-0.0839990450209257	0.175430113544584	-0.47881770879421	0.632162962229348	   
df.mm.trans1:exp5	0.487191436766628	0.266187412081959	1.83025723476594	0.067480485079942	.  
df.mm.trans2:exp5	-0.0272507170464214	0.175430113544584	-0.155336598123422	0.876584308826224	   
df.mm.trans1:exp6	0.691769905649884	0.266187412081959	2.59880773564487	0.00947927805961951	** 
df.mm.trans2:exp6	0.164396537100210	0.175430113544584	0.937105573145685	0.34890883458847	   
df.mm.trans1:exp7	0.517432576595755	0.266187412081959	1.94386568676824	0.052164996032585	.  
df.mm.trans2:exp7	0.0281212793044917	0.175430113544584	0.160299042942504	0.872674784225783	   
df.mm.trans1:exp8	0.351600154353055	0.266187412081958	1.32087446060296	0.186816452758603	   
df.mm.trans2:exp8	-0.0179645592354090	0.175430113544584	-0.102402939110243	0.91845541356977	   
df.mm.trans1:probe2	-0.125139621368224	0.203303994151663	-0.615529576240744	0.53833167981672	   
df.mm.trans1:probe3	0.00412533930269726	0.203303994151663	0.0202914818270604	0.98381451088821	   
df.mm.trans1:probe4	-0.0762149037919493	0.203303994151663	-0.374881487744376	0.707820478754141	   
df.mm.trans1:probe5	0.212909099723417	0.203303994151663	1.04724504116032	0.29521538020971	   
df.mm.trans1:probe6	-0.247020316086365	0.203303994151663	-1.21502933140649	0.224614223952087	   
df.mm.trans1:probe7	-0.318044177799505	0.203303994151663	-1.56437741976799	0.118015022545571	   
df.mm.trans1:probe8	-0.0996271709990666	0.203303994151663	-0.490040401885787	0.624202499726866	   
df.mm.trans1:probe9	-0.134942930971953	0.203303994151663	-0.663749532000274	0.506988963626993	   
df.mm.trans1:probe10	-0.212603231564137	0.203303994151663	-1.04574055444054	0.295909324837671	   
df.mm.trans1:probe11	0.107841784962869	0.203303994151663	0.530445972853933	0.595909241424379	   
df.mm.trans1:probe12	-0.111596136033102	0.203303994151663	-0.548912659088501	0.583176184208205	   
df.mm.trans1:probe13	-0.161258204864801	0.203303994151663	-0.793187588555216	0.427838659996476	   
df.mm.trans1:probe14	-0.0231977464991510	0.203303994151663	-0.114103742014265	0.909176265227032	   
df.mm.trans1:probe15	-0.315931000001946	0.203303994151663	-1.55398324228822	0.120474500961964	   
df.mm.trans1:probe16	0.0924758108970815	0.203303994151663	0.454864702894599	0.649295845194954	   
df.mm.trans1:probe17	-0.0620209217484657	0.203303994151663	-0.305064944775254	0.760374088022669	   
df.mm.trans1:probe18	-0.16095632313119	0.203303994151663	-0.791702710036863	0.428703800089295	   
df.mm.trans1:probe19	-0.0199309578815667	0.203303994151663	-0.0980352499454508	0.921922066111092	   
df.mm.trans1:probe20	-0.109995120221237	0.203303994151663	-0.541037674543577	0.588590566140233	   
df.mm.trans1:probe21	-0.162461692440641	0.203303994151663	-0.799107234063713	0.424399808311982	   
df.mm.trans1:probe22	-0.146334930239842	0.203303994151663	-0.719783843157931	0.471810165301013	   
df.mm.trans2:probe2	0.305633915946562	0.203303994151663	1.50333453713930	0.133038272345865	   
df.mm.trans2:probe3	0.0162619166974292	0.203303994151663	0.0799881810747798	0.936261126431425	   
df.mm.trans2:probe4	0.175051703367146	0.203303994151663	0.861034256103002	0.389405798264623	   
df.mm.trans2:probe5	0.0691976978597962	0.203303994151663	0.340365658572233	0.733645811698099	   
df.mm.trans2:probe6	0.106678802995815	0.203303994151663	0.524725564005564	0.599879138715554	   
df.mm.trans3:probe2	0.224918056833463	0.203303994151663	1.10631400908767	0.268831203717856	   
df.mm.trans3:probe3	0.112094274844095	0.203303994151663	0.55136287563772	0.581496313288552	   
df.mm.trans3:probe4	0.372250123458632	0.203303994151663	1.83100250937981	0.0673690821890403	.  
df.mm.trans3:probe5	0.512897477535835	0.203303994151663	2.52281062984536	0.0117814604080226	*  
df.mm.trans3:probe6	0.0314782622708617	0.203303994151663	0.154833467006945	0.876980856780106	   
df.mm.trans3:probe7	0.0469422466510321	0.203303994151663	0.230896824466782	0.81743766218693	   
df.mm.trans3:probe8	0.217514668411778	0.203303994151663	1.06989864768477	0.284898365664221	   
df.mm.trans3:probe9	0.166306625062507	0.203303994151663	0.818019467627595	0.413522267178418	   
df.mm.trans3:probe10	0.588792528565727	0.203303994151663	2.89611884420968	0.00385244781742279	** 
df.mm.trans3:probe11	0.244996517001111	0.203303994151663	1.20507478479909	0.228432212081098	   
df.mm.trans3:probe12	0.0632579449949962	0.203303994151663	0.311149543613031	0.755745572966952	   
df.mm.trans3:probe13	0.253399455156220	0.203303994151663	1.24640667397408	0.212879054390123	   
df.mm.trans3:probe14	0.362517612464383	0.203303994151663	1.78313079375090	0.074839192875103	.  
df.mm.trans3:probe15	0.206437822040048	0.203303994151663	1.01541449247695	0.310130362782145	   
df.mm.trans3:probe16	0.246040441678597	0.203303994151663	1.21020958149525	0.226457060761627	   
df.mm.trans3:probe17	0.116637287594171	0.203303994151663	0.573708785608808	0.566281522845014	   
df.mm.trans3:probe18	0.460601364541805	0.203303994151663	2.26557951536457	0.0236698461841115	*  
df.mm.trans3:probe19	0.252027304129543	0.203303994151663	1.23965741637881	0.215365099013172	   
df.mm.trans3:probe20	0.298638454899049	0.203303994151663	1.46892566545578	0.142137313011464	   
df.mm.trans3:probe21	0.210383020748745	0.203303994151663	1.03481990910518	0.300979230263272