chr7.22251_chr7_99811687_99833570_+_2.R 

fitVsDatCorrelation=0.750408259138557
cont.fitVsDatCorrelation=0.254287756019104

fstatistic=11641.7662404819,53,715
cont.fstatistic=5430.57007683526,53,715

residuals=-0.499558547183754,-0.0832490038681514,-0.00824218297849716,0.0696155936509455,1.16166798942055
cont.residuals=-0.418926118837941,-0.127778401736670,-0.0208641262086484,0.0931445172669662,1.68012512465214

predictedValues:
Include	Exclude	Both
chr7.22251_chr7_99811687_99833570_+_2.R.tl.Lung	49.2188009031469	60.7559454618002	69.8920377464524
chr7.22251_chr7_99811687_99833570_+_2.R.tl.cerebhem	58.1645214202579	53.4944147933624	69.9627807919025
chr7.22251_chr7_99811687_99833570_+_2.R.tl.cortex	48.0968287246895	52.8043706449408	57.9003039871533
chr7.22251_chr7_99811687_99833570_+_2.R.tl.heart	48.3692768058006	58.4832360223807	64.6596143896139
chr7.22251_chr7_99811687_99833570_+_2.R.tl.kidney	49.0435742114858	53.2490524147962	66.3060690078311
chr7.22251_chr7_99811687_99833570_+_2.R.tl.liver	50.6314641414271	54.7174873902408	62.6540526778031
chr7.22251_chr7_99811687_99833570_+_2.R.tl.stomach	52.2259787675516	51.6622702378428	58.9352247571033
chr7.22251_chr7_99811687_99833570_+_2.R.tl.testicle	53.9234229773243	57.934127348657	64.8669895756131


diffExp=-11.5371445586533,4.67010662689548,-4.70754192025133,-10.1139592165801,-4.20547820331044,-4.08602324881370,0.563708529708791,-4.0107043713327
diffExpScore=1.27500567326109
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=-1,0,0,-1,0,0,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	55.4798709873265	53.1038366454526	56.9016768098984
cerebhem	54.611769928915	59.8016874410024	53.578254939972
cortex	52.7552897555158	53.6983129897576	54.2928834111168
heart	53.8582773195957	57.8225015556472	57.5739308185954
kidney	53.7698412027499	52.6097399376565	57.995052846637
liver	53.5115864929994	56.1851059586567	55.2453463058809
stomach	54.6460248862317	55.843146446046	54.9963084753316
testicle	53.9677130051864	53.5008817558304	52.6463621610314
cont.diffExp=2.37603434187391,-5.18991751208739,-0.943023234241892,-3.9642242360515,1.16010126509337,-2.67351946565734,-1.1971215598143,0.466831249356069
cont.diffExpScore=1.63894541596351

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=-0.209338551770137
cont.tran.correlation=0.116560859402224

tran.covariance=-0.000776471548264114
cont.tran.covariance=8.06521321260893e-05

tran.mean=53.2984232666065
cont.tran.mean=54.6978491442856

weightedLogRatios:
wLogRatio
Lung	-0.842687740980757
cerebhem	0.336586631445559
cortex	-0.366031803589978
heart	-0.754526996120041
kidney	-0.323640686487424
liver	-0.307598385400343
stomach	0.0428683189312267
testicle	-0.288648053439526

cont.weightedLogRatios:
wLogRatio
Lung	0.174827635310928
cerebhem	-0.367281363031181
cortex	-0.0704187610435787
heart	-0.285640630406670
kidney	0.0866745525239517
liver	-0.195222430196676
stomach	-0.0869351154545466
testicle	0.034612661106077

varWeightedLogRatios=0.146809717379908
cont.varWeightedLogRatios=0.034783798450924

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.89266984524023	0.0687628130920357	56.6101017424938	2.2111238827425e-266	***
df.mm.trans1	-0.0221230688832701	0.0600431018383874	-0.368453131265883	0.712644449605308	   
df.mm.trans2	0.183966462089245	0.0540900862001787	3.40111238514974	0.000708437398072457	***
df.mm.exp2	0.0387005314082180	0.0714332410458558	0.541772021563106	0.588144350616954	   
df.mm.exp3	0.0248986796830455	0.0714332410458558	0.348558728660541	0.727523224391395	   
df.mm.exp4	0.0222792820068916	0.0714332410458558	0.311889558428262	0.75521538357861	   
df.mm.exp5	-0.0827811438644525	0.0714332410458558	-1.15886025402812	0.246900041898397	   
df.mm.exp6	0.0329392976060870	0.0714332410458558	0.461120020928939	0.644852732547399	   
df.mm.exp7	0.0676799315190576	0.0714332410458558	0.947457101597997	0.343726002862861	   
df.mm.exp8	0.118343823482736	0.0714332410458558	1.65670522224753	0.0980178037335807	.  
df.mm.trans1:exp2	0.128299357176810	0.0666118407434498	1.92607433971003	0.0544912514023994	.  
df.mm.trans2:exp2	-0.16598822445757	0.0537041829162308	-3.09078763411191	0.00207374748055906	** 
df.mm.trans1:exp3	-0.0479581183066405	0.0666118407434498	-0.719963864853207	0.471782521916741	   
df.mm.trans2:exp3	-0.165169660146265	0.0537041829162308	-3.0755455381176	0.00218124976456185	** 
df.mm.trans1:exp4	-0.039690129262155	0.0666118407434498	-0.595841952709554	0.551469377538303	   
df.mm.trans2:exp4	-0.0604040776721801	0.0537041829162307	-1.12475554774570	0.261070073994014	   
df.mm.trans1:exp5	0.0792146337491248	0.0666118407434498	1.18919748899019	0.234756736394127	   
df.mm.trans2:exp5	-0.0491037918475291	0.0537041829162308	-0.914338309999474	0.360847337383173	   
df.mm.trans1:exp6	-0.00464177626854226	0.0666118407434499	-0.069683951332612	0.944464699784307	   
df.mm.trans2:exp6	-0.137620888037927	0.0537041829162308	-2.56257297969866	0.0105936355107803	*  
df.mm.trans1:exp7	-0.00837556557369317	0.0666118407434499	-0.125736888220084	0.89997554691313	   
df.mm.trans2:exp7	-0.229817144175131	0.0537041829162308	-4.27931553364485	2.13003164602146e-05	***
df.mm.trans1:exp8	-0.0270545590586105	0.0666118407434499	-0.406152401084501	0.684752150636284	   
df.mm.trans2:exp8	-0.165902138856338	0.0537041829162308	-3.08918467515122	0.00208481950098389	** 
df.mm.trans1:probe2	-0.107066629776931	0.0407912551622468	-2.62474467507986	0.00885660508873516	** 
df.mm.trans1:probe3	0.0844340067959	0.0407912551622467	2.06990460234834	0.0388198339635796	*  
df.mm.trans1:probe4	0.0628426699616309	0.0407912551622467	1.54059172025168	0.123858613209657	   
df.mm.trans1:probe5	-0.0433650069211672	0.0407912551622467	-1.06309567451856	0.288097479260663	   
df.mm.trans1:probe6	-0.0683552227633682	0.0407912551622467	-1.67573227377991	0.0942278440687558	.  
df.mm.trans1:probe7	-0.0618145568364704	0.0407912551622468	-1.51538746700987	0.130116251047267	   
df.mm.trans1:probe8	-0.0319445014500274	0.0407912551622467	-0.783121316639277	0.433815181916334	   
df.mm.trans1:probe9	0.268607856434506	0.0407912551622468	6.58493727065082	8.81479248799942e-11	***
df.mm.trans1:probe10	0.00558021158465512	0.0407912551622467	0.136799212538567	0.891228015708944	   
df.mm.trans1:probe11	-0.0723091699555192	0.0407912551622468	-1.77266351986254	0.0767102028180529	.  
df.mm.trans1:probe12	0.038791524351666	0.0407912551622467	0.95097648251747	0.341937655877469	   
df.mm.trans1:probe13	-0.00541448831304579	0.0407912551622467	-0.13273649686703	0.894439124138933	   
df.mm.trans1:probe14	0.00151914397542007	0.0407912551622468	0.0372419031818877	0.97030252300741	   
df.mm.trans1:probe15	0.0677367216739937	0.0407912551622468	1.66056968349151	0.0972383308201385	.  
df.mm.trans1:probe16	0.0767513338296694	0.0407912551622467	1.88156342638617	0.0603013383127039	.  
df.mm.trans1:probe17	0.248954919047338	0.0407912551622467	6.103144364083	1.70445533617692e-09	***
df.mm.trans1:probe18	0.0348970953212848	0.0407912551622468	0.855504327642825	0.392558594719772	   
df.mm.trans1:probe19	0.0155638492385267	0.0407912551622467	0.381548672052911	0.702909520338424	   
df.mm.trans1:probe20	0.153541808256568	0.0407912551622468	3.76408638679682	0.000180876187518967	***
df.mm.trans2:probe2	0.164783029376815	0.0407912551622467	4.03966557835478	5.93212437220816e-05	***
df.mm.trans2:probe3	0.0327050744974066	0.0407912551622467	0.801766809266411	0.422954239062256	   
df.mm.trans2:probe4	0.0400508568239381	0.0407912551622468	0.981849091542693	0.326506307799377	   
df.mm.trans2:probe5	0.080362580570925	0.0407912551622467	1.97009335092249	0.0492131795932317	*  
df.mm.trans2:probe6	0.0448421121677951	0.0407912551622468	1.09930699581163	0.272004187550022	   
df.mm.trans3:probe2	0.135184351550768	0.0407912551622467	3.31405226470903	0.000965891642378409	***
df.mm.trans3:probe3	0.536363389880061	0.0407912551622467	13.1489797935043	1.59393787728194e-35	***
df.mm.trans3:probe4	0.294818665840369	0.0407912551622468	7.22749679233284	1.26573137423792e-12	***
df.mm.trans3:probe5	0.00110004976519919	0.0407912551622467	0.0269677841690273	0.978492954094781	   
df.mm.trans3:probe6	0.187164513555944	0.0407912551622468	4.58834896870663	5.27574002103485e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.99180476091857	0.100612764418144	39.6749337323516	7.76082970642711e-183	***
df.mm.trans1	-0.000615179006164764	0.0878542076531189	-0.00700227140621107	0.994414994614142	   
df.mm.trans2	-0.0125967459427348	0.0791438403331699	-0.159162682651064	0.873585651057066	   
df.mm.exp2	0.163195371490781	0.104520096397912	1.56137792745129	0.118877086635595	   
df.mm.exp3	0.00770783604781732	0.104520096397912	0.0737450147239942	0.941233905226377	   
df.mm.exp4	0.0437195885698829	0.104520096397912	0.418288827475251	0.675861558638439	   
df.mm.exp5	-0.059688339877705	0.104520096397912	-0.571070463334335	0.568131323818078	   
df.mm.exp6	0.0498211577862023	0.104520096397912	0.476665823159321	0.633745742128405	   
df.mm.exp7	0.069212575566965	0.104520096397912	0.662193950754408	0.508060303527786	   
df.mm.exp8	0.0575423153982527	0.104520096397912	0.550538292456092	0.582122178075004	   
df.mm.trans1:exp2	-0.178966215560664	0.0974654924487941	-1.83620080362995	0.0667430003382298	.  
df.mm.trans2:exp2	-0.0444106717031404	0.0785791921687024	-0.565170886559824	0.572134823255429	   
df.mm.trans1:exp3	-0.0580640590471743	0.0974654924487941	-0.595739657065598	0.551537686339669	   
df.mm.trans2:exp3	0.00342457066498856	0.0785791921687024	0.0435811386001056	0.96525045431691	   
df.mm.trans1:exp4	-0.0733837561627337	0.097465492448794	-0.752920385656366	0.451745579901976	   
df.mm.trans2:exp4	0.0414092327736873	0.0785791921687024	0.526974528890364	0.598374730266194	   
df.mm.trans1:exp5	0.0283808073731024	0.097465492448794	0.291188262225351	0.770991789383958	   
df.mm.trans2:exp5	0.0503404335491736	0.0785791921687024	0.640633126401926	0.521966330350973	   
df.mm.trans1:exp6	-0.0859432274227996	0.0974654924487941	-0.881781082345138	0.378191533407228	   
df.mm.trans2:exp6	0.00658136661280237	0.0785791921687024	0.083754572058628	0.933275010597398	   
df.mm.trans1:exp7	-0.0843563713150866	0.0974654924487941	-0.865499872782208	0.387054790448096	   
df.mm.trans2:exp7	-0.0189149500186186	0.0785791921687024	-0.240711942902262	0.80984738568395	   
df.mm.trans1:exp8	-0.0851766250164735	0.0974654924487941	-0.873915709821331	0.382457583220439	   
df.mm.trans2:exp8	-0.0500933590625056	0.0785791921687024	-0.637488852710011	0.524010547668271	   
df.mm.trans1:probe2	0.0204769679032104	0.0596851810071581	0.343082948860532	0.731636904129538	   
df.mm.trans1:probe3	-0.0162244215077006	0.0596851810071581	-0.271833330048121	0.785828647646485	   
df.mm.trans1:probe4	0.111905742902583	0.0596851810071581	1.87493345943211	0.0612092857328209	.  
df.mm.trans1:probe5	0.0176338445187919	0.0596851810071581	0.295447617335316	0.767737738025501	   
df.mm.trans1:probe6	0.0570494745681384	0.0596851810071581	0.955839851793302	0.339476206848263	   
df.mm.trans1:probe7	0.00103795683330248	0.0596851810071581	0.0173905283654581	0.986129916787332	   
df.mm.trans1:probe8	0.080407414481619	0.0596851810071581	1.34719226991999	0.178345102415287	   
df.mm.trans1:probe9	0.046954631337748	0.0596851810071581	0.78670501698096	0.431715234451328	   
df.mm.trans1:probe10	-0.0353080403266544	0.0596851810071581	-0.591571303476819	0.554324679436371	   
df.mm.trans1:probe11	-0.0531203412604067	0.0596851810071581	-0.89000888267451	0.373760473441214	   
df.mm.trans1:probe12	0.0466588232199085	0.0596851810071581	0.781748876899823	0.434620957227635	   
df.mm.trans1:probe13	0.0599634738833054	0.0596851810071581	1.00466267960407	0.315399180069539	   
df.mm.trans1:probe14	0.0661652926007702	0.0596851810071581	1.10857153290420	0.267987811796075	   
df.mm.trans1:probe15	0.0211857381804388	0.0596851810071581	0.354958095509469	0.722725659863569	   
df.mm.trans1:probe16	-0.0189470026836028	0.0596851810071581	-0.317449027780120	0.750995589597024	   
df.mm.trans1:probe17	0.109427416309943	0.0596851810071581	1.83341014408282	0.0671571548391535	.  
df.mm.trans1:probe18	0.0619750304504785	0.0596851810071581	1.03836546031494	0.29945096026798	   
df.mm.trans1:probe19	0.0526772536016223	0.0596851810071581	0.88258513608771	0.377757088444351	   
df.mm.trans1:probe20	0.0156786366492186	0.0596851810071581	0.262688935254100	0.79286601707199	   
df.mm.trans2:probe2	-0.0322655547781492	0.0596851810071581	-0.540595743092068	0.588954610524573	   
df.mm.trans2:probe3	0.0238663537770039	0.0596851810071581	0.399870677683655	0.689371198042318	   
df.mm.trans2:probe4	-0.0265915156087988	0.0596851810071581	-0.445529613215206	0.656071927715408	   
df.mm.trans2:probe5	-0.0239964353547659	0.0596851810071581	-0.402050139579671	0.687767280920347	   
df.mm.trans2:probe6	-0.0245188815718279	0.0596851810071581	-0.410803505293672	0.68133970630329	   
df.mm.trans3:probe2	0.00787485238026593	0.0596851810071581	0.131939825721924	0.895069005895912	   
df.mm.trans3:probe3	0.0545517195149545	0.0596851810071581	0.91399102079312	0.361029669218671	   
df.mm.trans3:probe4	0.10251015762241	0.0596851810071581	1.71751439624713	0.0863182299512191	.  
df.mm.trans3:probe5	0.184088570066459	0.0596851810071581	3.08432624246178	0.00211871062615040	** 
df.mm.trans3:probe6	0.0273665452958321	0.0596851810071581	0.458514908291054	0.64672188750029