chr3.14700_chr3_97012897_97013458_-_0.R 

fitVsDatCorrelation=0.940464858882177
cont.fitVsDatCorrelation=0.293355697679483

fstatistic=11095.5791073881,70,1106
cont.fstatistic=1388.72118054576,70,1106

residuals=-0.982045064540024,-0.0865724818278518,-0.00333582404880665,0.0945230132583375,0.799651232367965
cont.residuals=-0.865463043119162,-0.361453607687031,-0.127167784482929,0.323404012225831,1.55245237757095

predictedValues:
Include	Exclude	Both
chr3.14700_chr3_97012897_97013458_-_0.R.tl.Lung	92.7267568423634	65.4606808323033	79.2076876102161
chr3.14700_chr3_97012897_97013458_-_0.R.tl.cerebhem	89.0736278686966	70.6519850605784	74.1917188708223
chr3.14700_chr3_97012897_97013458_-_0.R.tl.cortex	90.1096166896577	63.1408663797449	75.0374023248974
chr3.14700_chr3_97012897_97013458_-_0.R.tl.heart	93.9264385136226	69.2594217594964	76.8273862078101
chr3.14700_chr3_97012897_97013458_-_0.R.tl.kidney	103.331090182916	70.3927314404154	83.9507400932565
chr3.14700_chr3_97012897_97013458_-_0.R.tl.liver	114.164628680193	79.1577869954336	85.0384948272356
chr3.14700_chr3_97012897_97013458_-_0.R.tl.stomach	103.794844076032	74.6165941719992	81.316723749976
chr3.14700_chr3_97012897_97013458_-_0.R.tl.testicle	101.475740100652	71.5924484511383	83.0662683963571


diffExp=27.2660760100601,18.4216428081182,26.9687503099128,24.6670167541262,32.9383587425004,35.0068416847595,29.1782499040327,29.8832916495140
diffExpScore=0.995562069015401
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=1,0,1,0,1,1,0,1
diffExp1.4Score=0.833333333333333
diffExp1.3=1,0,1,1,1,1,1,1
diffExp1.3Score=0.875
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	80.6609120943531	80.5954301220721	74.904505680668
cerebhem	82.0926525735507	74.393012191044	70.9037342305531
cortex	76.1413898730672	96.9763966662423	83.162338180056
heart	71.9700266913446	78.5668989349311	82.5922617669653
kidney	67.1416459553088	68.0319869698471	80.8105231559792
liver	95.5318470545587	88.9316254141394	88.9320153184068
stomach	83.7811286515023	84.3615740937446	80.914378210902
testicle	76.9834866847765	84.6844127140648	76.4950691000684
cont.diffExp=0.0654819722810203,7.69964038250664,-20.8350067931751,-6.59687224358656,-0.89034101453835,6.60022164041935,-0.580445442242294,-7.70092602928835
cont.diffExpScore=2.19332096611202

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

tran.correlation=0.848683301329305
cont.tran.correlation=0.455031650960652

tran.covariance=0.00504843153798359
cont.tran.covariance=0.00575520908140456

tran.mean=84.5547036278277
cont.tran.mean=80.6777766677842

weightedLogRatios:
wLogRatio
Lung	1.51663591554456
cerebhem	1.01335386131050
cortex	1.53758276733756
heart	1.33748195459514
kidney	1.70659492849954
liver	1.66786590693438
stomach	1.47777754484733
testicle	1.55069120855827

cont.weightedLogRatios:
wLogRatio
Lung	0.00356520454872993
cerebhem	0.42926379317535
cortex	-1.07720024213821
heart	-0.378875981454221
kidney	-0.055505045013301
liver	0.323857448154802
stomach	-0.0305971887839459
testicle	-0.418665548683139

varWeightedLogRatios=0.0477486995679389
cont.varWeightedLogRatios=0.227302791920237

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.96705709618528	0.0769157802486977	64.5778678981726	0	***
df.mm.trans1	-0.306465727116525	0.0645555047952434	-4.7473213645927	2.33152471731954e-06	***
df.mm.trans2	-0.765446088114758	0.0572750380588105	-13.3643924833152	7.12240383433986e-38	***
df.mm.exp2	0.101543594699355	0.0719799159621476	1.41072121774571	0.158608029640800	   
df.mm.exp3	-0.0106249697185455	0.0719799159621476	-0.147610198991242	0.882677309917713	   
df.mm.exp4	0.0997765493018165	0.0719799159621476	1.38617207269715	0.165973753342208	   
df.mm.exp5	0.122764732689386	0.0719799159621476	1.70554148401542	0.0883742664431127	.  
df.mm.exp6	0.326947267993275	0.0719799159621477	4.54220130189104	6.17784440745706e-06	***
df.mm.exp7	0.217394142798084	0.0719799159621476	3.02020556556924	0.00258401797672293	** 
df.mm.exp8	0.132137272463139	0.0719799159621476	1.83575196909963	0.0666626930113982	.  
df.mm.trans1:exp2	-0.141737357550432	0.0629656587264746	-2.25102635972006	0.0245796022230084	*  
df.mm.trans2:exp2	-0.0252270586138299	0.0440145881925593	-0.573152212704208	0.566658146076435	   
df.mm.trans1:exp3	-0.0180052078480265	0.0629656587264746	-0.28595282273218	0.774967803680956	   
df.mm.trans2:exp3	-0.0254564954355299	0.0440145881925593	-0.578364957639961	0.563135492907671	   
df.mm.trans1:exp4	-0.0869217124025582	0.0629656587264746	-1.38046221004611	0.167723302394705	   
df.mm.trans2:exp4	-0.0433670289570106	0.0440145881925593	-0.98528762253288	0.324698300594876	   
df.mm.trans1:exp5	-0.0144835020209519	0.0629656587264746	-0.230022242503153	0.818117020994273	   
df.mm.trans2:exp5	-0.0501243911975469	0.0440145881925593	-1.13881313573259	0.255027703786230	   
df.mm.trans1:exp6	-0.118962820094607	0.0629656587264746	-1.88932860388845	0.059109195971041	.  
df.mm.trans2:exp6	-0.13695377350263	0.0440145881925593	-3.11155412617906	0.00190874625873428	** 
df.mm.trans1:exp7	-0.104634915014267	0.0629656587264746	-1.66177750111065	0.0968407792146793	.  
df.mm.trans2:exp7	-0.0864808880978682	0.0440145881925593	-1.96482329266659	0.0496847179195657	*  
df.mm.trans1:exp8	-0.0419745863360813	0.0629656587264746	-0.666626653084352	0.505149674346833	   
df.mm.trans2:exp8	-0.0425973423751121	0.0440145881925593	-0.967800543509645	0.333355572466887	   
df.mm.trans1:probe2	-0.398981569780146	0.0493241142456501	-8.08897586671477	1.57098911329951e-15	***
df.mm.trans1:probe3	-0.495189321510791	0.0493241142456501	-10.0394974969969	9.30726158393338e-23	***
df.mm.trans1:probe4	-0.489056027698723	0.0493241142456501	-9.9151507366775	2.93763477908311e-22	***
df.mm.trans1:probe5	-0.383649771633457	0.0493241142456501	-7.77813808723977	1.67910579903033e-14	***
df.mm.trans1:probe6	0.487649320015964	0.0493241142456501	9.8866310621882	3.81742244350707e-22	***
df.mm.trans1:probe7	0.397197838433475	0.0493241142456501	8.05281239223681	2.07808447399817e-15	***
df.mm.trans1:probe8	0.00497160351034659	0.0493241142456501	0.100794582657610	0.919731795584876	   
df.mm.trans1:probe9	0.516487215491434	0.0493241142456501	10.4712922551262	1.57165661293548e-24	***
df.mm.trans1:probe10	0.455448497294196	0.0493241142456501	9.23378968400558	1.29426512972701e-19	***
df.mm.trans1:probe11	-0.898072168208725	0.0493241142456501	-18.2075680819332	5.42085098649374e-65	***
df.mm.trans1:probe12	-0.830934126553566	0.0493241142456501	-16.8464074674559	7.36425294208844e-57	***
df.mm.trans1:probe13	-0.782468811460777	0.0493241142456501	-15.8638188121094	3.21561279734778e-51	***
df.mm.trans1:probe14	-0.820368466652086	0.0493241142456501	-16.6321986557404	1.30013779724400e-55	***
df.mm.trans1:probe15	-0.642398557968716	0.0493241142456501	-13.0240262353088	3.52587233851437e-36	***
df.mm.trans1:probe16	-0.834270419762103	0.0493241142456501	-16.9140476726488	2.96120944455333e-57	***
df.mm.trans2:probe2	-0.207645615068778	0.0493241142456501	-4.20981944114873	2.76319234368987e-05	***
df.mm.trans2:probe3	-0.235320539853288	0.0493241142456501	-4.77090249773803	2.0793531365663e-06	***
df.mm.trans2:probe4	-0.303238164423102	0.0493241142456501	-6.1478684221855	1.09491650235048e-09	***
df.mm.trans2:probe5	0.318212168398358	0.0493241142456501	6.45145226153598	1.65319161873923e-10	***
df.mm.trans2:probe6	-0.237332013404146	0.0493241142456501	-4.81168323108967	1.70389349023368e-06	***
df.mm.trans3:probe2	0.114957754255268	0.0493241142456501	2.33066028682727	0.0199503522410997	*  
df.mm.trans3:probe3	0.335228083957251	0.0493241142456501	6.79643393670907	1.74968965756647e-11	***
df.mm.trans3:probe4	0.816450312999828	0.0493241142456501	16.5527617776092	3.74949271811184e-55	***
df.mm.trans3:probe5	0.0353109627428892	0.0493241142456501	0.71589654032162	0.474206349830483	   
df.mm.trans3:probe6	0.149685545105308	0.0493241142456501	3.03473356581378	0.00246373358027236	** 
df.mm.trans3:probe7	0.130533839504184	0.0493241142456501	2.64645075741418	0.00824963105063896	** 
df.mm.trans3:probe8	0.0864013017080557	0.0493241142456501	1.75170508440860	0.080101683320155	.  
df.mm.trans3:probe9	0.21423705357148	0.0493241142456501	4.34345465393479	1.53138056597505e-05	***
df.mm.trans3:probe10	0.083836038175999	0.0493241142456501	1.69969678033078	0.0894691551065777	.  
df.mm.trans3:probe11	0.816721960387199	0.0493241142456501	16.5582691727551	3.48436734825601e-55	***
df.mm.trans3:probe12	0.433072188753743	0.0493241142456501	8.78013108551535	6.09717202391567e-18	***
df.mm.trans3:probe13	1.30437128040316	0.0493241142456501	26.4449002349433	8.04829008183624e-120	***
df.mm.trans3:probe14	1.21391979882067	0.0493241142456501	24.6110815649919	5.19016400129056e-107	***
df.mm.trans3:probe15	0.821693563897546	0.0493241142456501	16.6590637554127	9.08092643374512e-56	***
df.mm.trans3:probe16	1.33320917587863	0.0493241142456501	27.0295614278813	5.97627731381378e-124	***
df.mm.trans3:probe17	1.27217045768140	0.0493241142456501	25.7920588567607	3.10783934561916e-115	***
df.mm.trans3:probe18	0.106897111482621	0.0493241142456501	2.16723834005896	0.0304295582061856	*  
df.mm.trans3:probe19	0.38335923258106	0.0493241142456501	7.77224768136346	1.75484750557152e-14	***
df.mm.trans3:probe20	0.772066627783501	0.0493241142456501	15.6529243270008	4.90488051525276e-50	***
df.mm.trans3:probe21	-0.0920717002474142	0.0493241142456501	-1.86666707868016	0.0622125421830127	.  
df.mm.trans3:probe22	0.263346111399485	0.0493241142456501	5.33909458744532	1.13312258975385e-07	***
df.mm.trans3:probe23	0.439740765855145	0.0493241142456501	8.915330210799	1.96755204139664e-18	***
df.mm.trans3:probe24	0.505083737973459	0.0493241142456501	10.2400974796624	1.42195953331001e-23	***
df.mm.trans3:probe25	0.135736339009634	0.0493241142456501	2.75192653908843	0.00602142194142657	** 
df.mm.trans3:probe26	1.09628021971430	0.0493241142456501	22.2260498030329	8.97284367801174e-91	***
df.mm.trans3:probe27	0.104820368022474	0.0493241142456501	2.12513432071857	0.0337966094139877	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.47688165609081	0.216339233313372	20.6938038354141	1.13414253355914e-80	***
df.mm.trans1	-0.0576572848851758	0.181573772877343	-0.317541922335472	0.750892372166436	   
df.mm.trans2	-0.0896343358583186	0.161096172743396	-0.556402640310356	0.578048187593971	   
df.mm.exp2	-0.00759456930845047	0.202456242176333	-0.0375121518942144	0.970083420598505	   
df.mm.exp3	0.0227830390082004	0.202456242176333	0.112533151674114	0.910421106169131	   
df.mm.exp4	-0.237197781226541	0.202456242176333	-1.17160023655852	0.241609921106857	   
df.mm.exp5	-0.428806698688008	0.202456242176333	-2.11802162323319	0.0343958221396663	*  
df.mm.exp6	0.0959732823267682	0.202456242176333	0.474044570298694	0.635561691614922	   
df.mm.exp7	0.0064462629767222	0.202456242176333	0.0318402777184203	0.974605170702705	   
df.mm.exp8	-0.0181857892337450	0.202456242176333	-0.0898257768604918	0.92844192753574	   
df.mm.trans1:exp2	0.0251889908684119	0.177102049669288	0.142228680669979	0.886925282199132	   
df.mm.trans2:exp2	-0.0724853650947103	0.123798812589479	-0.585509372655085	0.558324711388983	   
df.mm.trans1:exp3	-0.0804451313136706	0.177102049669288	-0.454230379963924	0.649752145105086	   
df.mm.trans2:exp3	0.162242626879256	0.123798812589479	1.31053459629906	0.190287124262763	   
df.mm.trans1:exp4	0.123193420343217	0.177102049669288	0.695606971083973	0.486821129350985	   
df.mm.trans2:exp4	0.211706309149007	0.123798812589479	1.71008351954903	0.0875308965070128	.  
df.mm.trans1:exp5	0.245357107939994	0.177102049669288	1.38539959530768	0.166209639526207	   
df.mm.trans2:exp5	0.259342740209852	0.123798812589479	2.09487259841369	0.0364093501575829	*  
df.mm.trans1:exp6	0.073232289309288	0.177102049669288	0.413503341412695	0.67931803705232	   
df.mm.trans2:exp6	0.00245258870563677	0.123798812589479	0.0198110842449647	0.984197648969035	   
df.mm.trans1:exp7	0.0315074267910069	0.177102049669288	0.1779054892354	0.858829777785116	   
df.mm.trans2:exp7	0.0392238020349726	0.123798812589479	0.316835042392854	0.751428566130083	   
df.mm.trans1:exp8	-0.0284773678219957	0.177102049669288	-0.160796376299274	0.872283143912328	   
df.mm.trans2:exp8	0.0676753949385329	0.123798812589479	0.546656252374138	0.584725180032651	   
df.mm.trans1:probe2	-0.168600251195094	0.138732793521207	-1.21528765417184	0.224515757817974	   
df.mm.trans1:probe3	0.20538696805562	0.138732793521207	1.48045002801896	0.139037983779939	   
df.mm.trans1:probe4	-0.150141231478648	0.138732793521207	-1.08223317405987	0.279384826626786	   
df.mm.trans1:probe5	-0.122740198393405	0.138732793521207	-0.884723757650294	0.376497930839479	   
df.mm.trans1:probe6	-0.284480220291948	0.138732793521207	-2.05056218556186	0.0405448773329477	*  
df.mm.trans1:probe7	-0.0986582479487438	0.138732793521207	-0.711138624435345	0.477148282317397	   
df.mm.trans1:probe8	-0.0644790071904871	0.138732793521207	-0.464771201919399	0.642186795015356	   
df.mm.trans1:probe9	0.080095620361298	0.138732793521207	0.577337328315633	0.563829103484015	   
df.mm.trans1:probe10	-0.138313838897952	0.138732793521207	-0.996980132724058	0.318992222629554	   
df.mm.trans1:probe11	0.0529558672118226	0.138732793521207	0.38171124409549	0.702748881502442	   
df.mm.trans1:probe12	0.0414196536898155	0.138732793521207	0.298557050849582	0.76533412229763	   
df.mm.trans1:probe13	-0.177234863304152	0.138732793521207	-1.27752681111449	0.201684415881479	   
df.mm.trans1:probe14	-0.133817554954375	0.138732793521207	-0.964570463535856	0.3349708508077	   
df.mm.trans1:probe15	-0.100805958900804	0.138732793521207	-0.726619542086818	0.467612806453022	   
df.mm.trans1:probe16	0.0164834015764821	0.138732793521207	0.118814024846710	0.905444272907574	   
df.mm.trans2:probe2	0.0651972569455248	0.138732793521207	0.469948418760549	0.638484515155927	   
df.mm.trans2:probe3	0.0412836629929412	0.138732793521207	0.297576816159407	0.766082055944412	   
df.mm.trans2:probe4	0.0812030836923815	0.138732793521207	0.585320035957963	0.558451945139465	   
df.mm.trans2:probe5	-0.103740930255965	0.138732793521207	-0.747775112306862	0.454754776523908	   
df.mm.trans2:probe6	-0.0115203020076996	0.138732793521207	-0.0830395014423077	0.933835156589654	   
df.mm.trans3:probe2	0.00030456965418183	0.138732793521207	0.00219536885585219	0.998248746385928	   
df.mm.trans3:probe3	0.155661501076697	0.138732793521207	1.12202383535874	0.262095835415862	   
df.mm.trans3:probe4	-0.103627152233583	0.138732793521207	-0.746954988819871	0.455249489777051	   
df.mm.trans3:probe5	-0.165557228309930	0.138732793521207	-1.19335323760076	0.232986978082517	   
df.mm.trans3:probe6	-0.049565413244808	0.138732793521207	-0.357272509165119	0.720955967444952	   
df.mm.trans3:probe7	-0.0099368932502526	0.138732793521207	-0.071626131054109	0.942912393480327	   
df.mm.trans3:probe8	0.137133633875672	0.138732793521207	0.98847309561823	0.323137199861168	   
df.mm.trans3:probe9	0.157298726134240	0.138732793521207	1.13382511907824	0.257113611002951	   
df.mm.trans3:probe10	-0.0541377409086965	0.138732793521207	-0.390230309176474	0.696441392938572	   
df.mm.trans3:probe11	0.00953779616200204	0.138732793521207	0.0687493988978466	0.94520152355039	   
df.mm.trans3:probe12	-0.111690939909827	0.138732793521207	-0.805079585546974	0.420946790235101	   
df.mm.trans3:probe13	-0.0781648334076061	0.138732793521207	-0.563420020772938	0.573263114262719	   
df.mm.trans3:probe14	0.00861990986416281	0.138732793521207	0.0621331816752119	0.950467999122034	   
df.mm.trans3:probe15	-0.177225111963343	0.138732793521207	-1.27745652246418	0.201709206484254	   
df.mm.trans3:probe16	-0.194991694266292	0.138732793521207	-1.40551984370217	0.160147589956407	   
df.mm.trans3:probe17	0.0176748879779986	0.138732793521207	0.127402379274492	0.89864509225069	   
df.mm.trans3:probe18	0.24081790762704	0.138732793521207	1.73583982211263	0.0828706608757238	.  
df.mm.trans3:probe19	-0.0212764244755155	0.138732793521207	-0.153362618422754	0.878140298149308	   
df.mm.trans3:probe20	0.183731494331084	0.138732793521207	1.32435518429172	0.185658713717050	   
df.mm.trans3:probe21	0.0583477655008405	0.138732793521207	0.420576592021996	0.674145992454976	   
df.mm.trans3:probe22	0.0169506275239709	0.138732793521207	0.122181836707410	0.902777206930087	   
df.mm.trans3:probe23	-0.291022723739442	0.138732793521207	-2.09772121178369	0.0361562685764939	*  
df.mm.trans3:probe24	-0.0734886053037462	0.138732793521207	-0.529713295887123	0.596417040637109	   
df.mm.trans3:probe25	0.0195117077173248	0.138732793521207	0.140642361637029	0.888178090669106	   
df.mm.trans3:probe26	0.00308481327389277	0.138732793521207	0.0222356459175691	0.982263994100255	   
df.mm.trans3:probe27	-0.0391423281541738	0.138732793521207	-0.282141858177104	0.777887524272656