chr14.7292_chr14_43771294_43772161_-_2.R 

fitVsDatCorrelation=0.958417353492238
cont.fitVsDatCorrelation=0.223856593317263

fstatistic=6095.86105907867,51,669
cont.fstatistic=510.619625261786,51,669

residuals=-1.25178481800629,-0.118320829786928,0.0120010426758241,0.130388500487506,0.824281235287242
cont.residuals=-1.51659415382789,-0.633677344817277,-0.137915245001107,0.52641184190396,2.37851668601035

predictedValues:
Include	Exclude	Both
chr14.7292_chr14_43771294_43772161_-_2.R.tl.Lung	73.845521202997	62.7874680674716	131.037089329073
chr14.7292_chr14_43771294_43772161_-_2.R.tl.cerebhem	98.5231393905952	237.100124762512	572.108450892174
chr14.7292_chr14_43771294_43772161_-_2.R.tl.cortex	126.039311867598	214.771327949872	474.641797127903
chr14.7292_chr14_43771294_43772161_-_2.R.tl.heart	256.435116678846	204.400149376943	555.149738060681
chr14.7292_chr14_43771294_43772161_-_2.R.tl.kidney	76.7006140040744	50.1255329821027	120.200332051195
chr14.7292_chr14_43771294_43772161_-_2.R.tl.liver	237.267766808707	55.8025929198598	425.893372985407
chr14.7292_chr14_43771294_43772161_-_2.R.tl.stomach	84.7445868526877	58.1286059876991	135.488524322392
chr14.7292_chr14_43771294_43772161_-_2.R.tl.testicle	79.4626739324166	51.2691909218328	134.240814054331


diffExp=11.0580531355253,-138.576985371917,-88.732016082274,52.0349673019032,26.5750810219717,181.465173888847,26.6159808649886,28.1934830105838
diffExpScore=5.55285541888661
diffExp1.5=0,-1,-1,0,1,1,0,1
diffExp1.5Score=2.5
diffExp1.4=0,-1,-1,0,1,1,1,1
diffExp1.4Score=2
diffExp1.3=0,-1,-1,0,1,1,1,1
diffExp1.3Score=2
diffExp1.2=0,-1,-1,1,1,1,1,1
diffExp1.2Score=1.75

cont.predictedValues:
Include	Exclude	Both
Lung	161.616338602512	174.672066794043	156.087614584098
cerebhem	143.766889869641	224.804270608522	152.020165312542
cortex	125.837784077549	164.928605314832	174.623144660852
heart	197.13909830715	154.014692065203	145.965037808078
kidney	169.404405122278	177.570271979013	145.715823279741
liver	174.997841742986	179.857580803368	160.27769102041
stomach	191.064772943682	191.988942133957	143.65738769693
testicle	181.124600278171	143.154555260622	164.322776337972
cont.diffExp=-13.0557281915316,-81.0373807388804,-39.0908212372838,43.1244062419476,-8.16586685673474,-4.85973906038211,-0.92416919027474,37.9700450175488
cont.diffExpScore=3.40439582578747

cont.diffExp1.5=0,-1,0,0,0,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=0,-1,0,0,0,0,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,-1,-1,0,0,0,0,0
cont.diffExp1.3Score=0.666666666666667
cont.diffExp1.2=0,-1,-1,1,0,0,0,1
cont.diffExp1.2Score=4

tran.correlation=0.29042462051681
cont.tran.correlation=-0.331155047266469

tran.covariance=0.140187462688021
cont.tran.covariance=-0.00631918240588087

tran.mean=122.962732731638
cont.tran.mean=172.246419743971

weightedLogRatios:
wLogRatio
Lung	0.684708196743752
cerebhem	-4.41676278771626
cortex	-2.71984170910201
heart	1.23229146620540
kidney	1.75563357049938
liver	6.86849650601677
stomach	1.60261536886164
testicle	1.82123106771461

cont.weightedLogRatios:
wLogRatio
Lung	-0.398063542298492
cerebhem	-2.32088692542730
cortex	-1.34454809378065
heart	1.27392384997585
kidney	-0.242724210954241
liver	-0.141846973734989
stomach	-0.0253569750520081
testicle	1.19548836820999

varWeightedLogRatios=11.3154456648205
cont.varWeightedLogRatios=1.42607485879187

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.39485724036879	0.116348106628706	29.1784485260476	2.27162722483884e-121	***
df.mm.trans1	0.825873354718343	0.0975608533031925	8.46521249821128	1.61414445185961e-16	***
df.mm.trans2	0.708017024819917	0.0896522372151152	7.89737151925246	1.1706565676746e-14	***
df.mm.exp2	0.143194932025986	0.116348106628706	1.23074570076980	0.218850523040452	   
df.mm.exp3	0.477356867544145	0.116348106628706	4.10283313906863	4.58465377552768e-05	***
df.mm.exp4	0.98146693702789	0.116348106628706	8.43560729492558	2.02977821829312e-16	***
df.mm.exp5	-0.100970004985019	0.116348106628706	-0.867826799341377	0.385800338935364	   
df.mm.exp6	-0.129429811885703	0.116348106628706	-1.11243591009817	0.266350348444955	   
df.mm.exp7	0.0271623747340470	0.116348106628706	0.233457814837749	0.815477338562413	   
df.mm.exp8	-0.153508353449118	0.116348106628706	-1.31938849627351	0.187490628839970	   
df.mm.trans1:exp2	0.145121146313341	0.100760416022680	1.44025949913383	0.150261796820760	   
df.mm.trans2:exp2	1.18553208675226	0.0822705351753734	14.4101662183806	3.38010199510578e-41	***
df.mm.trans1:exp3	0.0572616297740759	0.100760416022680	0.56829489232346	0.570025440687174	   
df.mm.trans2:exp3	0.752461503143431	0.0822705351753734	9.14618461566384	7.00208407675752e-19	***
df.mm.trans1:exp4	0.263433379245411	0.100760416022680	2.61445307238624	0.00913825527859381	** 
df.mm.trans2:exp4	0.198857151613302	0.0822705351753734	2.41711265387303	0.0159106025443722	*  
df.mm.trans1:exp5	0.138904358673534	0.100760416022680	1.37856078960878	0.168491008968792	   
df.mm.trans2:exp5	-0.124254976880425	0.0822705351753734	-1.51032172837522	0.131433505481632	   
df.mm.trans1:exp6	1.29664377309444	0.100760416022680	12.8685829641928	5.10670073359363e-34	***
df.mm.trans2:exp6	0.0114946477961549	0.0822705351753734	0.139717673789919	0.88892511308434	   
df.mm.trans1:exp7	0.110504137621027	0.10076041602268	1.09670187939829	0.273166339826733	   
df.mm.trans2:exp7	-0.104259974747837	0.0822705351753734	-1.26728207766716	0.205495397273145	   
df.mm.trans1:exp8	0.226820394649973	0.100760416022680	2.25108632539706	0.0247038778561580	*  
df.mm.trans2:exp8	-0.0491571421075742	0.0822705351753734	-0.597506045181153	0.550371755496731	   
df.mm.trans1:probe2	-0.226309673952744	0.0712483734448146	-3.17634863802235	0.00155997380775276	** 
df.mm.trans1:probe3	-0.00327075486715819	0.0712483734448146	-0.0459063794584946	0.963398568888667	   
df.mm.trans1:probe4	0.202618094720477	0.0712483734448146	2.84382765421886	0.00459361636179596	** 
df.mm.trans1:probe5	0.125801716636926	0.0712483734448146	1.76567843663640	0.0779059088212745	.  
df.mm.trans1:probe6	0.0909358859941042	0.0712483734448146	1.27632227372234	0.202284513498928	   
df.mm.trans1:probe7	0.284353409496367	0.0712483734448146	3.99101615585109	7.30635128011195e-05	***
df.mm.trans1:probe8	0.203565736939907	0.0712483734448146	2.85712819953116	0.00440770473744972	** 
df.mm.trans1:probe9	0.157117945731531	0.0712483734448146	2.20521449311719	0.0277784688571043	*  
df.mm.trans1:probe10	-0.0301109937539833	0.0712483734448146	-0.422620086580724	0.672708267486026	   
df.mm.trans1:probe11	0.593979128242964	0.0712483734448146	8.3367394864534	4.34285785833469e-16	***
df.mm.trans1:probe12	0.551193860821902	0.0712483734448146	7.73623079618553	3.78108264225756e-14	***
df.mm.trans2:probe2	0.0100825131159637	0.0712483734448146	0.141512186573257	0.88750793522903	   
df.mm.trans2:probe3	-0.0663423344998411	0.0712483734448146	-0.931141741098504	0.352116136499603	   
df.mm.trans2:probe4	0.405908280628026	0.0712483734448146	5.69708838254985	1.82678346715243e-08	***
df.mm.trans2:probe5	0.00848975672934457	0.0712483734448146	0.119157200633083	0.905186585015257	   
df.mm.trans2:probe6	0.305724019540652	0.0712483734448146	4.29096138984072	2.04170372376066e-05	***
df.mm.trans3:probe2	0.351490197874456	0.0712483734448146	4.93330838137242	1.02133340345037e-06	***
df.mm.trans3:probe3	-0.0193479527180585	0.0712483734448146	-0.271556412905965	0.786046892949346	   
df.mm.trans3:probe4	-0.256256173505945	0.0712483734448146	-3.59665998135982	0.00034607717744536	***
df.mm.trans3:probe5	0.284561293144896	0.0712483734448146	3.99393388770206	7.21905256320307e-05	***
df.mm.trans3:probe6	-0.309362571113296	0.0712483734448146	-4.34202994617011	1.63040561744121e-05	***
df.mm.trans3:probe7	-0.551960709749076	0.0712483734448146	-7.74699383385358	3.49839671237678e-14	***
df.mm.trans3:probe8	0.301048302105576	0.0712483734448146	4.22533578733208	2.71692910514182e-05	***
df.mm.trans3:probe9	0.570217274729757	0.0712483734448146	8.0032321744358	5.36236598021599e-15	***
df.mm.trans3:probe10	-0.380068210161792	0.0712483734448146	-5.3344124474108	1.31321089760112e-07	***
df.mm.trans3:probe11	-1.10230375831838	0.0712483734448146	-15.4712831328307	2.21062734970025e-46	***
df.mm.trans3:probe12	0.472775762167406	0.0712483734448146	6.6356007766773	6.67787889740865e-11	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.41299008440495	0.397362505085982	13.6222970590385	1.79617334290205e-37	***
df.mm.trans1	-0.254534506497222	0.333198589905698	-0.763912315983271	0.445188825773269	   
df.mm.trans2	-0.247561175264286	0.306188373825857	-0.808525719546376	0.419075427025994	   
df.mm.exp2	0.161692027570152	0.397362505085982	0.406913147316617	0.684201930882934	   
df.mm.exp3	-0.419841934649759	0.397362505085982	-1.05657159212572	0.291088533186662	   
df.mm.exp4	0.139872360694627	0.397362505085982	0.35200190985398	0.724947679560791	   
df.mm.exp5	0.132278829516240	0.397362505085982	0.332892076688557	0.739320041760013	   
df.mm.exp6	0.0823130045694285	0.397362505085982	0.207148393509391	0.8359570039498	   
df.mm.exp7	0.344900984097742	0.397362505085982	0.867975663740875	0.385718896722826	   
df.mm.exp8	-0.136440672159292	0.397362505085982	-0.343365743906232	0.731431202651464	   
df.mm.trans1:exp2	-0.278724106239099	0.344126023915883	-0.809947771654808	0.418258189254893	   
df.mm.trans2:exp2	0.090627775702996	0.280977721935572	0.322544346500813	0.747141121309002	   
df.mm.trans1:exp3	0.169610338008155	0.344126023915883	0.492872744926764	0.62226423352658	   
df.mm.trans2:exp3	0.362444307914389	0.280977721935572	1.28993966289433	0.197517322057925	   
df.mm.trans1:exp4	0.0588119554718368	0.344126023915883	0.170902376991438	0.864352202500172	   
df.mm.trans2:exp4	-0.26573467174559	0.280977721935572	-0.945749968769848	0.344617581586081	   
df.mm.trans1:exp5	-0.0852152895624166	0.344126023915883	-0.247628146783942	0.804498110944933	   
df.mm.trans2:exp5	-0.115822712409389	0.280977721935572	-0.412213152030419	0.680315248775126	   
df.mm.trans1:exp6	-0.00276460980895755	0.344126023915883	-0.0080337132818334	0.993592488142726	   
df.mm.trans2:exp6	-0.0530579965510696	0.280977721935572	-0.188833464039672	0.850280612573265	   
df.mm.trans1:exp7	-0.177513734371297	0.344126023915883	-0.515839320581833	0.606137068960471	   
df.mm.trans2:exp7	-0.250373518715621	0.280977721935572	-0.891079609411281	0.373206816651601	   
df.mm.trans1:exp8	0.250400619724130	0.344126023915883	0.7276422075691	0.46708720940484	   
df.mm.trans2:exp8	-0.0625447871475921	0.280977721935572	-0.222596961484134	0.823917142559469	   
df.mm.trans1:probe2	-0.342432327353991	0.243333845093685	-1.40725318018195	0.159816746532258	   
df.mm.trans1:probe3	-0.271973075779208	0.243333845093685	-1.11769522104291	0.264098394543394	   
df.mm.trans1:probe4	-0.0721639779504805	0.243333845093685	-0.296563669236792	0.766891695421438	   
df.mm.trans1:probe5	-0.302205879611066	0.243333845093685	-1.24193935905100	0.214694143574733	   
df.mm.trans1:probe6	0.0182325517156117	0.243333845093685	0.0749281371384736	0.94029428832711	   
df.mm.trans1:probe7	-0.195139265268543	0.243333845093685	-0.80194049945421	0.422872135648076	   
df.mm.trans1:probe8	-0.277521179595697	0.243333845093685	-1.14049559973398	0.254488006757857	   
df.mm.trans1:probe9	-0.280651841258081	0.243333845093685	-1.15336130553490	0.249174013213131	   
df.mm.trans1:probe10	0.0530632945743702	0.243333845093685	0.218067875243333	0.827442725371936	   
df.mm.trans1:probe11	0.0537205435925869	0.243333845093685	0.22076889292529	0.825339744169164	   
df.mm.trans1:probe12	-0.140456804296408	0.243333845093685	-0.577218529721303	0.56398603066027	   
df.mm.trans2:probe2	0.00806750089045757	0.243333845093685	0.0331540435213668	0.973561634803109	   
df.mm.trans2:probe3	-0.121447078095330	0.243333845093685	-0.499096531551424	0.617875456321304	   
df.mm.trans2:probe4	0.202064614430621	0.243333845093685	0.83040077862093	0.406608462076945	   
df.mm.trans2:probe5	-0.0527972365976518	0.243333845093685	-0.216974488597443	0.828294377227879	   
df.mm.trans2:probe6	-0.0812225503333998	0.243333845093685	-0.333790600736731	0.738642174324612	   
df.mm.trans3:probe2	0.140324725260376	0.243333845093685	0.576675740303819	0.564352500070734	   
df.mm.trans3:probe3	0.213689177143938	0.243333845093685	0.878172853684478	0.380165196675005	   
df.mm.trans3:probe4	0.118523926866	0.243333845093685	0.487083606558584	0.626358633539767	   
df.mm.trans3:probe5	0.156244552156143	0.243333845093685	0.642099548856379	0.521028505384229	   
df.mm.trans3:probe6	0.341833137487655	0.243333845093685	1.40479076125250	0.160547640211286	   
df.mm.trans3:probe7	-0.199105222356406	0.243333845093685	-0.818238918962339	0.413512117331674	   
df.mm.trans3:probe8	0.126456972720668	0.243333845093685	0.519685096300437	0.603454975815766	   
df.mm.trans3:probe9	0.219488631582874	0.243333845093685	0.90200617796661	0.367378212307803	   
df.mm.trans3:probe10	0.320257326482177	0.243333845093685	1.31612323127050	0.188583452308084	   
df.mm.trans3:probe11	0.289400523141562	0.243333845093685	1.18931471711278	0.234737785116057	   
df.mm.trans3:probe12	-0.0528368036940148	0.243333845093685	-0.217137092761068	0.828167710079241