chr7.21641_chr7_22342351_22347720_-_2.R 

fitVsDatCorrelation=0.822441964673902
cont.fitVsDatCorrelation=0.246503124354514

fstatistic=8847.59333136769,52,692
cont.fstatistic=3039.48347418261,52,692

residuals=-0.512794380175243,-0.091909931848401,-0.0053792455767168,0.070893795543107,1.45698938061655
cont.residuals=-0.578082037155259,-0.176249405870824,-0.036899192963215,0.141268734641012,1.89000427523938

predictedValues:
Include	Exclude	Both
chr7.21641_chr7_22342351_22347720_-_2.R.tl.Lung	61.9709744567524	60.8068589950931	54.8299754440438
chr7.21641_chr7_22342351_22347720_-_2.R.tl.cerebhem	70.4011625582586	69.0230981195275	85.8320518320509
chr7.21641_chr7_22342351_22347720_-_2.R.tl.cortex	60.9230286843519	57.3224272779592	56.2657966517737
chr7.21641_chr7_22342351_22347720_-_2.R.tl.heart	61.1828960083888	57.7044976630035	56.3773178476516
chr7.21641_chr7_22342351_22347720_-_2.R.tl.kidney	60.4331500460578	62.4554674327406	54.7810001232239
chr7.21641_chr7_22342351_22347720_-_2.R.tl.liver	62.6765577490502	63.2411091528577	54.7865937328153
chr7.21641_chr7_22342351_22347720_-_2.R.tl.stomach	62.173084247617	61.265570830756	55.4852600013989
chr7.21641_chr7_22342351_22347720_-_2.R.tl.testicle	65.3007026206739	61.2543608881203	60.4892689324684


diffExp=1.1641154616593,1.37806443873112,3.60060140639271,3.47839834538532,-2.0223173866828,-0.564551403807478,0.907513416860944,4.04634173255367
diffExpScore=1.32134926343072
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	61.6216419817592	61.6366901962182	57.8343480506032
cerebhem	60.41313149301	62.7237926079681	66.2562382567658
cortex	59.4061292344491	58.1581195491719	65.5431474791065
heart	61.5520905472876	69.9794429694003	62.8275582291463
kidney	58.5672073945491	55.0390164283742	57.9040523430941
liver	61.562107472488	58.8685632729568	60.7134897515974
stomach	58.8947564804771	57.2178890204007	59.7459884253654
testicle	60.5212973776971	66.2358979339217	59.6641422050348
cont.diffExp=-0.0150482144589503,-2.31066111495803,1.24800968527722,-8.42735242211274,3.52819096617493,2.69354419953124,1.67686746007649,-5.71460055622462
cont.diffExpScore=3.07825029641565

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

tran.correlation=0.814787813180792
cont.tran.correlation=0.669505605579544

tran.covariance=0.00233490666142112
cont.tran.covariance=0.00112626870876158

tran.mean=62.3834341707005
cont.tran.mean=60.7748608725081

weightedLogRatios:
wLogRatio
Lung	0.0780763345800564
cerebhem	0.0839042570368058
cortex	0.248499036941779
heart	0.239082151382248
kidney	-0.135547889670379
liver	-0.0371457565900204
stomach	0.0606188570283493
testicle	0.265275473905796

cont.weightedLogRatios:
wLogRatio
Lung	-0.00100627236982755
cerebhem	-0.154640545769866
cortex	0.0864941468467884
heart	-0.536886774117112
kidney	0.250960384885570
liver	0.183327298378454
stomach	0.117312820612822
testicle	-0.374272484177913

varWeightedLogRatios=0.0207561712181067
cont.varWeightedLogRatios=0.078157339175616

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.50203889443398	0.0882770578370176	50.9989685286738	1.34141183308775e-236	***
df.mm.trans1	-0.0912604775256293	0.0792857074881124	-1.15103314855723	0.250116156388924	   
df.mm.trans2	-0.460049872984018	0.0729139760218325	-6.30948822275535	4.99598946350587e-10	***
df.mm.exp2	-0.193873195610675	0.0998740899516035	-1.94117609186347	0.0526425777935022	.  
df.mm.exp3	-0.101915315286498	0.0998740899516035	-1.02043798682805	0.307877395378820	   
df.mm.exp4	-0.0929957937190541	0.0998740899516035	-0.931130323831913	0.352110877395881	   
df.mm.exp5	0.00251648217910305	0.0998740899516035	0.0251965467752695	0.979905455328455	   
df.mm.exp6	0.0513648500169276	0.0998740899516035	0.514296050575456	0.607209222137836	   
df.mm.exp7	-0.00110886317545808	0.0998740899516035	-0.0111026110575366	0.991144780025743	   
df.mm.exp8	-0.0385598100836357	0.0998740899516035	-0.386084219664188	0.699552966764774	   
df.mm.trans1:exp2	0.321416850746470	0.09562216108216	3.36132175961077	0.000818345822528206	***
df.mm.trans2:exp2	0.320611804516759	0.083228408293003	3.85219195095088	0.000127937705913158	***
df.mm.trans1:exp3	0.0848604363383375	0.09562216108216	0.887455746429157	0.375141915842124	   
df.mm.trans2:exp3	0.0429046684127290	0.083228408293003	0.515505093665668	0.606364756214549	   
df.mm.trans1:exp4	0.0801973456857716	0.09562216108216	0.838689951975303	0.401932928251522	   
df.mm.trans2:exp4	0.0406283182655097	0.083228408293003	0.488154454696273	0.625595079509852	   
df.mm.trans1:exp5	-0.027644807478253	0.0956221610821601	-0.289104608862585	0.772587914687523	   
df.mm.trans2:exp5	0.0242347044947445	0.083228408293003	0.291183082697281	0.770998555173385	   
df.mm.trans1:exp6	-0.0400434733924131	0.09562216108216	-0.418767709694483	0.675515847692125	   
df.mm.trans2:exp6	-0.0121128940715411	0.083228408293003	-0.145537975794251	0.884328515841047	   
df.mm.trans1:exp7	0.00436491862484675	0.09562216108216	0.0456475630277415	0.9636043281963	   
df.mm.trans2:exp7	0.00862430290888726	0.083228408293003	0.103622105549894	0.917499267399531	   
df.mm.trans1:exp8	0.090896484692462	0.09562216108216	0.950579694746308	0.342149653784019	   
df.mm.trans2:exp8	0.0458922601188218	0.083228408293003	0.55140139118436	0.581536542993271	   
df.mm.trans1:probe2	-0.565695026811878	0.04781108054108	-11.8318812377776	1.51678266702372e-29	***
df.mm.trans1:probe3	-0.593317185628737	0.04781108054108	-12.4096167439460	4.52587415401008e-32	***
df.mm.trans1:probe4	-0.669541349456528	0.04781108054108	-14.0038949523688	2.06490422167755e-39	***
df.mm.trans1:probe5	-0.392030758653846	0.04781108054108	-8.19957955806933	1.17170680433903e-15	***
df.mm.trans1:probe6	-0.448396648642426	0.04781108054108	-9.37850898929498	9.35857912667094e-20	***
df.mm.trans1:probe7	-0.450721247097089	0.0478110805410801	-9.42712948538827	6.21174773239887e-20	***
df.mm.trans1:probe8	-0.596989346196707	0.04781108054108	-12.4864223824384	2.06202263491884e-32	***
df.mm.trans1:probe9	-0.537981110168213	0.04781108054108	-11.2522265566864	4.31766036410871e-27	***
df.mm.trans1:probe10	-0.531828139991043	0.04781108054108	-11.1235331637001	1.47543714248844e-26	***
df.mm.trans1:probe11	-0.570243837037976	0.0478110805410801	-11.9270225768692	5.89353689451674e-30	***
df.mm.trans1:probe12	-0.478528112936082	0.04781108054108	-10.0087282596536	4.08513084976149e-22	***
df.mm.trans1:probe13	-0.21218372633171	0.04781108054108	-4.43796132466403	1.05650750104601e-05	***
df.mm.trans1:probe14	-0.392869796939837	0.04781108054108	-8.21712859223663	1.02562747684188e-15	***
df.mm.trans1:probe15	-0.407014249413577	0.0478110805410801	-8.51296906088252	1.05054339568046e-16	***
df.mm.trans1:probe16	-0.319588757475851	0.04781108054108	-6.68440775358038	4.77587205509411e-11	***
df.mm.trans1:probe17	0.0613290612260827	0.0478110805410801	1.28273740170728	0.200013570665821	   
df.mm.trans1:probe18	-0.204442620088829	0.0478110805410801	-4.27605102781913	2.16970444940653e-05	***
df.mm.trans1:probe19	0.0107998887468129	0.04781108054108	0.225886732209147	0.821356215830958	   
df.mm.trans1:probe20	-0.0828953756222966	0.04781108054108	-1.73381096357091	0.0833970109715645	.  
df.mm.trans1:probe21	0.157612713073367	0.04781108054108	3.29657291342628	0.00102871032513502	** 
df.mm.trans1:probe22	0.121718240324668	0.0478110805410801	2.54581655438817	0.0111179690083218	*  
df.mm.trans2:probe2	0.210226467923755	0.04781108054108	4.39702398575003	1.27009773149537e-05	***
df.mm.trans2:probe3	0.0696955129045998	0.0478110805410801	1.45772720707946	0.145369405981894	   
df.mm.trans2:probe4	0.0972600309289006	0.0478110805410801	2.03425711839608	0.0423065171740490	*  
df.mm.trans2:probe5	0.111025953952932	0.0478110805410801	2.32218039618528	0.0205125154578595	*  
df.mm.trans2:probe6	0.103214196497348	0.0478110805410801	2.15879238304737	0.0312093749689055	*  
df.mm.trans3:probe2	0.247730746231695	0.04781108054108	5.18145048026767	2.89164162002813e-07	***
df.mm.trans3:probe3	-0.0872052533257529	0.0478110805410801	-1.82395487277943	0.0685900444698673	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.10412887944005	0.150396678438288	27.2886936204784	7.15702603465697e-112	***
df.mm.trans1	-0.0323768562661524	0.135078211100524	-0.239689702746048	0.810641796718754	   
df.mm.trans2	-0.0242954987793484	0.124222760410284	-0.195580090951973	0.84499625796855	   
df.mm.exp2	-0.138269886471234	0.170154417906634	-0.812614142919905	0.416718787347796	   
df.mm.exp3	-0.219833355664640	0.170154417906634	-1.29196384301503	0.196800966191350	   
df.mm.exp4	0.043003944710688	0.170154417906634	0.252734811354031	0.800548199916792	   
df.mm.exp5	-0.165257705168747	0.170154417906634	-0.971221947698277	0.331777113244752	   
df.mm.exp6	-0.0954997462144858	0.170154417906634	-0.561253403757568	0.574806501736327	   
df.mm.exp7	-0.152170988934266	0.170154417906634	-0.894311125190794	0.371466382842694	   
df.mm.exp8	0.0227991029335692	0.170154417906634	0.133990661036374	0.89344891740441	   
df.mm.trans1:exp2	0.118463236896851	0.162910452208311	0.727167810849691	0.467369090130558	   
df.mm.trans2:exp2	0.155753416265539	0.141795348255528	1.09843812354731	0.272395253891869	   
df.mm.trans1:exp3	0.183217622765141	0.162910452208311	1.12465234907619	0.261126328935451	   
df.mm.trans2:exp3	0.161741542697232	0.141795348255528	1.14066889137829	0.254402348913640	   
df.mm.trans1:exp4	-0.0441332673419916	0.162910452208311	-0.270905069280386	0.786544830744749	   
df.mm.trans2:exp4	0.0839402690462142	0.141795348255528	0.591981825066265	0.554056113633969	   
df.mm.trans1:exp5	0.114419504631200	0.162910452208312	0.702346001009767	0.48269958670911	   
df.mm.trans2:exp5	0.0520427152134255	0.141795348255528	0.367026957186493	0.713711116457488	   
df.mm.trans1:exp6	0.0945331493351045	0.162910452208311	0.580276759739309	0.561916894899841	   
df.mm.trans2:exp6	0.0495496505804049	0.141795348255528	0.349444824460051	0.726861699512143	   
df.mm.trans1:exp7	0.10690991181842	0.162910452208311	0.656249555318377	0.511881715868303	   
df.mm.trans2:exp7	0.0777802702406384	0.141795348255528	0.548538941492434	0.5834988206801	   
df.mm.trans1:exp8	-0.0408169167803482	0.162910452208311	-0.250548176787062	0.80223782185614	   
df.mm.trans2:exp8	0.0491661646030778	0.141795348255528	0.346740321230256	0.728891827616087	   
df.mm.trans1:probe2	0.0587646356358747	0.0814552261041558	0.721434810833783	0.470885708916797	   
df.mm.trans1:probe3	0.0192308520980227	0.0814552261041557	0.236091077488785	0.813431856759156	   
df.mm.trans1:probe4	0.0117460986593529	0.0814552261041557	0.144203131231055	0.885382053196863	   
df.mm.trans1:probe5	0.0917705421946412	0.0814552261041557	1.12663786700801	0.260286155219268	   
df.mm.trans1:probe6	0.0307314378308116	0.0814552261041557	0.377280124316587	0.70608111539068	   
df.mm.trans1:probe7	0.0535043700498899	0.0814552261041558	0.656856197065545	0.511491768927878	   
df.mm.trans1:probe8	0.0338691329671784	0.0814552261041558	0.415800613258017	0.677684819068213	   
df.mm.trans1:probe9	0.122774856804337	0.0814552261041557	1.50726801307194	0.132198334320690	   
df.mm.trans1:probe10	0.0844801417507211	0.0814552261041557	1.03713593088180	0.300034778853525	   
df.mm.trans1:probe11	0.0765342248547937	0.0814552261041558	0.93958642698911	0.347757585299553	   
df.mm.trans1:probe12	0.00764170815153798	0.0814552261041557	0.0938148295330569	0.925283407067257	   
df.mm.trans1:probe13	0.110292344302079	0.0814552261041557	1.35402416244047	0.176170679864256	   
df.mm.trans1:probe14	0.0372102199409705	0.0814552261041557	0.456818079338338	0.647945167512293	   
df.mm.trans1:probe15	-0.00264407720241503	0.0814552261041558	-0.0324604979800078	0.974114177531546	   
df.mm.trans1:probe16	0.0289358825999275	0.0814552261041557	0.355236661708207	0.72252054824355	   
df.mm.trans1:probe17	0.0797694556083151	0.0814552261041558	0.97930432979604	0.32777186900544	   
df.mm.trans1:probe18	0.089699675384196	0.0814552261041558	1.10121449137589	0.271186201654185	   
df.mm.trans1:probe19	-0.0208540468337252	0.0814552261041558	-0.256018524914035	0.798012618576847	   
df.mm.trans1:probe20	0.0588871216288285	0.0814552261041558	0.722938532556896	0.469961913608485	   
df.mm.trans1:probe21	0.0313997367555456	0.0814552261041558	0.385484618450327	0.699996866103229	   
df.mm.trans1:probe22	0.227783600220273	0.0814552261041558	2.79642708165844	0.00531052333663535	** 
df.mm.trans2:probe2	0.140537788515892	0.0814552261041558	1.72533789711894	0.084913046566238	.  
df.mm.trans2:probe3	-0.0252832315168782	0.0814552261041558	-0.310394221784479	0.756354648360747	   
df.mm.trans2:probe4	0.05542223754689	0.0814552261041558	0.680401248607698	0.496478004995914	   
df.mm.trans2:probe5	0.0756989065495742	0.0814552261041558	0.929331488844914	0.353041377826654	   
df.mm.trans2:probe6	0.126439692628654	0.0814552261041558	1.55226004120322	0.121057215082834	   
df.mm.trans3:probe2	-0.0623229845882688	0.0814552261041557	-0.765119533381163	0.44446122305122	   
df.mm.trans3:probe3	0.0927019797299689	0.0814552261041558	1.13807283048275	0.25548393731411