chr15.8806_chr15_94287094_94300478_+_2.R 

fitVsDatCorrelation=0.895872499887992
cont.fitVsDatCorrelation=0.288773791133559

fstatistic=11317.9297309148,53,715
cont.fstatistic=2426.98503309674,53,715

residuals=-0.761022890338255,-0.0807023260357123,-0.00427055600676823,0.071407847858491,0.680674501988595
cont.residuals=-0.525198875191153,-0.189662911607709,-0.0727926163648506,0.0976134569188407,1.17958409592481

predictedValues:
Include	Exclude	Both
chr15.8806_chr15_94287094_94300478_+_2.R.tl.Lung	56.5382741615817	58.2220390231223	79.4672871725789
chr15.8806_chr15_94287094_94300478_+_2.R.tl.cerebhem	61.2664379200703	60.9509258162891	60.9989628840313
chr15.8806_chr15_94287094_94300478_+_2.R.tl.cortex	52.9209901162747	61.5844468605448	84.7458848123119
chr15.8806_chr15_94287094_94300478_+_2.R.tl.heart	53.2635151661408	53.7990474486245	75.5004191124039
chr15.8806_chr15_94287094_94300478_+_2.R.tl.kidney	56.271476236997	51.0376070785215	67.2554398183831
chr15.8806_chr15_94287094_94300478_+_2.R.tl.liver	54.6887784339281	50.2593985572089	64.9431428345114
chr15.8806_chr15_94287094_94300478_+_2.R.tl.stomach	55.4375278721693	53.8285967595842	68.5714068188851
chr15.8806_chr15_94287094_94300478_+_2.R.tl.testicle	58.7197101170026	59.9327153589525	78.7404675067455


diffExp=-1.68376486154059,0.315512103781202,-8.6634567442701,-0.5355322824837,5.23386915847547,4.4293798767192,1.60893111258510,-1.21300524194994
diffExpScore=15.7045100032187
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	56.932500385457	58.4626801666113	54.8475273022657
cerebhem	67.0068772622032	58.6321222773527	64.1622749004297
cortex	62.2184852028931	77.1600932627854	63.4900770982362
heart	60.2849212075031	60.0129558075665	56.6494768824779
kidney	62.5791622168307	62.1481213787082	57.929036737537
liver	60.6628681322789	57.940441622691	57.4502870236173
stomach	59.4807661106284	64.8219022613218	59.5451678024425
testicle	58.0853387365583	57.4564272552416	61.3370483990913
cont.diffExp=-1.53017978115429,8.3747549848506,-14.9416080598923,0.271965399936583,0.431040838122485,2.72242650958795,-5.34113615069346,0.628911481316628
cont.diffExpScore=3.29763106927101

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=0.385474087940051
cont.tran.correlation=0.171991576110727

tran.covariance=0.00147758576846484
cont.tran.covariance=0.000927343392383104

tran.mean=56.1700929329383
cont.tran.mean=61.4928539554144

weightedLogRatios:
wLogRatio
Lung	-0.118839832297191
cerebhem	0.0212341993165746
cortex	-0.613199703131333
heart	-0.0398191871830097
kidney	0.388681812866630
liver	0.334417155822912
stomach	0.117823227880663
testicle	-0.0834853852124827

cont.weightedLogRatios:
wLogRatio
Lung	-0.107551074270930
cerebhem	0.55248014378905
cortex	-0.912203330162043
heart	0.0185239432765832
kidney	0.0285661433902157
liver	0.187446960115827
stomach	-0.355024704621196
testicle	0.0441604086760919

varWeightedLogRatios=0.096561135425
cont.varWeightedLogRatios=0.182323834242703

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.33753484859117	0.0746255362698246	44.7237636795479	2.34520249040052e-209	***
df.mm.trans1	0.53978985769826	0.0662689204569491	8.14544516458404	1.68378966292395e-15	***
df.mm.trans2	0.693423052322645	0.0602802007954168	11.5033301676621	3.24232911392573e-28	***
df.mm.exp2	0.39060803792027	0.0812666684846996	4.80649748788227	1.87291738872819e-06	***
df.mm.exp3	-0.0742841200684558	0.0812666684846996	-0.914078569400707	0.360983699480456	   
df.mm.exp4	-0.0874672006339612	0.0812666684846996	-1.07629858913718	0.282156764382333	   
df.mm.exp5	0.0304162848078053	0.0812666684846996	0.374277491312836	0.708308845189125	   
df.mm.exp6	0.0215076117046033	0.0812666684846996	0.264654773053144	0.79135169325482	   
df.mm.exp7	0.0493496562936661	0.0812666684846996	0.607255806271391	0.543873956006172	   
df.mm.exp8	0.0760044138805636	0.0812666684846996	0.935247073588026	0.349976737826483	   
df.mm.trans1:exp2	-0.310293677893032	0.0771665143723553	-4.02109231467625	6.4085898703341e-05	***
df.mm.trans2:exp2	-0.344802952771955	0.0649800202404593	-5.30629186473024	1.49393203711403e-07	***
df.mm.trans1:exp3	0.00816634122344557	0.0771665143723553	0.105827524929273	0.91574888020928	   
df.mm.trans2:exp3	0.130429512267404	0.0649800202404593	2.00722486365421	0.0451016226729789	*  
df.mm.trans1:exp4	0.0278009513602214	0.0771665143723553	0.360272218932581	0.718749970982573	   
df.mm.trans2:exp4	0.00845900179861005	0.0649800202404593	0.130178503597066	0.89646181611102	   
df.mm.trans1:exp5	-0.0351463444183386	0.0771665143723553	-0.455461085733966	0.648915836256922	   
df.mm.trans2:exp5	-0.162117490558579	0.0649800202404593	-2.49488211851368	0.0128244241529550	*  
df.mm.trans1:exp6	-0.0547668983793811	0.0771665143723553	-0.709723625912552	0.478106921307365	   
df.mm.trans2:exp6	-0.168574006720554	0.0649800202404593	-2.59424367823747	0.00967409372481982	** 
df.mm.trans1:exp7	-0.0690107210534796	0.0771665143723553	-0.894309165248528	0.371457431646468	   
df.mm.trans2:exp7	-0.127808752490573	0.0649800202404593	-1.96689308525321	0.0495818471591653	*  
df.mm.trans1:exp8	-0.0381467938829507	0.0771665143723553	-0.494343876916341	0.621215186014276	   
df.mm.trans2:exp8	-0.0470458520244717	0.0649800202404593	-0.724004884122503	0.469299551775173	   
df.mm.trans1:probe2	-0.0253052126739736	0.0422658406057856	-0.598715471200392	0.549552265022899	   
df.mm.trans1:probe3	0.782079783376134	0.0422658406057856	18.5038265456639	9.29667451717826e-63	***
df.mm.trans1:probe4	0.0297410357831154	0.0422658406057856	0.703666018629812	0.481869868128942	   
df.mm.trans1:probe5	0.127925861003048	0.0422658406057856	3.02669624381105	0.00256121010910651	** 
df.mm.trans1:probe6	0.173008157943039	0.0422658406057856	4.09333294838945	4.73712469064691e-05	***
df.mm.trans1:probe7	0.0462869142892948	0.0422658406057856	1.09513767207457	0.273825085205887	   
df.mm.trans1:probe8	0.89822826128534	0.0422658406057856	21.2518726331066	4.6127128091629e-78	***
df.mm.trans1:probe9	0.2223182517576	0.0422658406057856	5.259998347866	1.90540477055346e-07	***
df.mm.trans1:probe10	1.17046056272755	0.0422658406057856	27.6928258364588	2.91435387203173e-115	***
df.mm.trans1:probe11	0.0627098560258843	0.0422658406057856	1.48370067002288	0.138329013813150	   
df.mm.trans1:probe12	0.00390824784770183	0.0422658406057856	0.0924682389297339	0.926351926607328	   
df.mm.trans1:probe13	0.113194792840266	0.0422658406057856	2.67816258278253	0.00757272811261245	** 
df.mm.trans1:probe14	0.0611949623415592	0.0422658406057856	1.44785863629984	0.148094920705890	   
df.mm.trans1:probe15	0.00996999095455942	0.0422658406057856	0.235887676943415	0.813587382238173	   
df.mm.trans1:probe16	0.0644521889401498	0.0422658406057856	1.52492386325157	0.127720269977449	   
df.mm.trans1:probe17	0.0652741446422692	0.0422658406057856	1.54437114479947	0.122940907964696	   
df.mm.trans1:probe18	0.0737065026439098	0.0422658406057856	1.74387878219132	0.0816099935375376	.  
df.mm.trans1:probe19	0.0983233804251368	0.0422658406057856	2.32630840924711	0.0202807298053061	*  
df.mm.trans1:probe20	-0.0860254055125799	0.0422658406057856	-2.03534117101658	0.0421848361146067	*  
df.mm.trans1:probe21	0.0823517877317831	0.0422658406057856	1.9484242251297	0.0517550797932495	.  
df.mm.trans1:probe22	0.123617089622872	0.0422658406057856	2.92475171086388	0.00355641027644871	** 
df.mm.trans2:probe2	0.038247397818342	0.0422658406057856	0.904924574317031	0.365810159066451	   
df.mm.trans2:probe3	0.0339118063717780	0.0422658406057856	0.802345484810634	0.422619735053804	   
df.mm.trans2:probe4	0.0152180851536192	0.0422658406057856	0.360056370238997	0.718911307553337	   
df.mm.trans2:probe5	0.117591773664419	0.0422658406057856	2.78219413074496	0.00554161506085223	** 
df.mm.trans2:probe6	0.128091532158184	0.0422658406057856	3.03061598497228	0.00252861824939202	** 
df.mm.trans3:probe2	-0.220582918290103	0.0422658406057856	-5.2189407599268	2.36060937315458e-07	***
df.mm.trans3:probe3	-0.39755411472652	0.0422658406057856	-9.4060382812332	6.85514889424632e-20	***
df.mm.trans3:probe4	-0.163472181942195	0.0422658406057856	-3.86771396473344	0.00011988205914947	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24731773038353	0.160802354825349	26.4132806699046	7.99853871530917e-108	***
df.mm.trans1	-0.0502434960569927	0.142795603138869	-0.351856044251803	0.725049897477248	   
df.mm.trans2	-0.125109693602582	0.129891170258396	-0.963188593602616	0.335778522103255	   
df.mm.exp2	0.00896468582217351	0.175112599712529	0.0511938366336303	0.959185361318453	   
df.mm.exp3	0.219953052036876	0.175112599712529	1.25606639612431	0.209502162257011	   
df.mm.exp4	0.0510618628521114	0.175112599712529	0.291594453716844	0.770681292961663	   
df.mm.exp5	0.101036321589452	0.175112599712529	0.576979165150406	0.56413514140473	   
df.mm.exp6	0.00812953475864235	0.175112599712529	0.0464246134886243	0.962984782160247	   
df.mm.exp7	0.0648635359381051	0.175112599712529	0.370410444734344	0.711186395312861	   
df.mm.exp8	-0.109141740996225	0.175112599712529	-0.623266065236858	0.533308450468234	   
df.mm.trans1:exp2	0.153964211658291	0.166277628878579	0.925946639344496	0.354786132085954	   
df.mm.trans2:exp2	-0.0060705824892667	0.140018293918643	-0.0433556381767798	0.965430144643074	   
df.mm.trans1:exp3	-0.131167269034065	0.166277628878579	-0.788844957188123	0.430464109771037	   
df.mm.trans2:exp3	0.057540739899488	0.140018293918643	0.41095158560439	0.681231168828243	   
df.mm.trans1:exp4	0.00615378436895963	0.166277628878579	0.0370090938297737	0.970488084954065	   
df.mm.trans2:exp4	-0.0248899986073246	0.140018293918643	-0.177762475964653	0.858959866179169	   
df.mm.trans1:exp5	-0.00647033318048847	0.166277628878579	-0.0389128304518541	0.96897074932687	   
df.mm.trans2:exp5	-0.0399043360965132	0.140018293918643	-0.284993731745506	0.775731473127231	   
df.mm.trans1:exp6	0.0553358861382443	0.166277628878579	0.332792129112282	0.739388750927286	   
df.mm.trans2:exp6	-0.0171025251711277	0.140018293918643	-0.122144933297537	0.902818558004017	   
df.mm.trans1:exp7	-0.0210768966380779	0.166277628878579	-0.126757260012824	0.89916816155126	   
df.mm.trans2:exp7	0.0383914033777516	0.140018293918643	0.274188481399857	0.784018974725976	   
df.mm.trans1:exp8	0.129188665336315	0.166277628878579	0.77694555910857	0.437447851896721	   
df.mm.trans2:exp8	0.091780009874699	0.140018293918643	0.655485846213976	0.51236584006143	   
df.mm.trans1:probe2	-0.140388168469509	0.0910740081452701	-1.54147348215507	0.123644029489702	   
df.mm.trans1:probe3	-0.172524140824178	0.0910740081452701	-1.89432906641145	0.0585846379028408	.  
df.mm.trans1:probe4	-0.252110032719622	0.0910740081452701	-2.76818861773918	0.00578278714238444	** 
df.mm.trans1:probe5	-0.232250157692473	0.0910740081452701	-2.55012557833203	0.0109758542241779	*  
df.mm.trans1:probe6	-0.264161591394434	0.0910740081452701	-2.90051570996058	0.00383984577922972	** 
df.mm.trans1:probe7	-0.192997868002923	0.0910740081452701	-2.11913225225661	0.0344234004463966	*  
df.mm.trans1:probe8	-0.142194801013551	0.0910740081452701	-1.56131045409508	0.118892998504593	   
df.mm.trans1:probe9	-0.183907739416451	0.0910740081452701	-2.01932190272227	0.0438264269252485	*  
df.mm.trans1:probe10	-0.238947666633654	0.0910740081452701	-2.62366477000237	0.00888445822763106	** 
df.mm.trans1:probe11	-0.300639149992154	0.0910740081452701	-3.30104226348105	0.00101110075157335	** 
df.mm.trans1:probe12	-0.173864808294091	0.0910740081452701	-1.90904970402492	0.0566557249094141	.  
df.mm.trans1:probe13	-0.176978723635839	0.0910740081452701	-1.94324074716844	0.0523791829921494	.  
df.mm.trans1:probe14	-0.187406637563525	0.0910740081452701	-2.05774008830924	0.039977110284279	*  
df.mm.trans1:probe15	-0.0976837164546	0.0910740081452701	-1.07257513360768	0.283823659663575	   
df.mm.trans1:probe16	-0.253913950233614	0.0910740081452701	-2.78799577842891	0.00544440442985397	** 
df.mm.trans1:probe17	-0.264585370825428	0.0910740081452701	-2.90516884250218	0.00378388279304422	** 
df.mm.trans1:probe18	-0.171991257775417	0.0910740081452701	-1.88847796729312	0.0593663670214996	.  
df.mm.trans1:probe19	-0.100112328685220	0.0910740081452701	-1.09924149297935	0.272032730675615	   
df.mm.trans1:probe20	-0.291252333072099	0.0910740081452701	-3.19797425196801	0.00144497252073212	** 
df.mm.trans1:probe21	-0.103627706984352	0.0910740081452701	-1.13784063197326	0.255568170341482	   
df.mm.trans1:probe22	-0.093866521776497	0.0910740081452701	-1.03066202628057	0.303047845570709	   
df.mm.trans2:probe2	-0.101798929492889	0.0910740081452701	-1.11776050671353	0.264044719362501	   
df.mm.trans2:probe3	-0.0955446228370278	0.0910740081452701	-1.04908771210142	0.294492221961236	   
df.mm.trans2:probe4	-0.178495380369349	0.0910740081452701	-1.95989376117756	0.0503962585352702	.  
df.mm.trans2:probe5	-0.168766382345800	0.0910740081452701	-1.85306857338051	0.0642843436026897	.  
df.mm.trans2:probe6	0.00641099517427296	0.0910740081452701	0.0703932472593818	0.943900349191314	   
df.mm.trans3:probe2	-0.0789442534685643	0.0910740081452701	-0.866814309332275	0.386334553249454	   
df.mm.trans3:probe3	-0.0725399068997756	0.0910740081452701	-0.796494064300638	0.426009304694918	   
df.mm.trans3:probe4	-0.118145584063441	0.0910740081452701	-1.29724810041291	0.194964250366489