chr10.2447_chr10_76757362_76765575_-_2.R 

fitVsDatCorrelation=0.874358385924845
cont.fitVsDatCorrelation=0.243368762342033

fstatistic=13119.3548345916,55,761
cont.fstatistic=3273.71228418994,55,761

residuals=-0.501124935063818,-0.0838344274026787,-0.0032136889160063,0.0769242988328988,0.670095401181582
cont.residuals=-0.53359605224516,-0.191615636231756,-0.0584486403451777,0.140223481416422,0.924197274093239

predictedValues:
Include	Exclude	Both
chr10.2447_chr10_76757362_76765575_-_2.R.tl.Lung	62.2747192275382	47.1010446797823	62.5369404896741
chr10.2447_chr10_76757362_76765575_-_2.R.tl.cerebhem	65.0927124703494	52.6201534066236	67.836995767414
chr10.2447_chr10_76757362_76765575_-_2.R.tl.cortex	71.1165594131257	48.7881960673561	77.895300853515
chr10.2447_chr10_76757362_76765575_-_2.R.tl.heart	60.2994640809976	46.7151344093453	61.3852149727147
chr10.2447_chr10_76757362_76765575_-_2.R.tl.kidney	62.8858515612154	47.7753055676849	59.5608263464228
chr10.2447_chr10_76757362_76765575_-_2.R.tl.liver	60.8259830497553	49.9504676588635	57.821613127114
chr10.2447_chr10_76757362_76765575_-_2.R.tl.stomach	58.8467350126638	47.0449267629316	62.2731369801797
chr10.2447_chr10_76757362_76765575_-_2.R.tl.testicle	61.0310055381235	47.7112073225251	61.7200189614318


diffExp=15.1736745477559,12.4725590637258,22.3283633457697,13.5843296716524,15.1105459935304,10.8755153908917,11.8018082497322,13.3197982155984
diffExpScore=0.991354461463076
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=1,0,1,0,1,0,0,0
diffExp1.3Score=0.75
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	57.9092910762901	53.9985230976949	55.6114675486055
cerebhem	57.5478095503348	60.6686862545569	56.6384409286959
cortex	58.5028652708309	64.9462402586339	60.4480589953908
heart	63.4077953177655	56.6444408890042	60.2167129015262
kidney	59.3662133478845	55.1232917215166	58.936697715281
liver	54.9975729719493	64.8530321985892	62.4419006005119
stomach	56.572492641144	59.8694011277244	67.4283753664788
testicle	61.280235662315	56.8796438517894	58.2888808040353
cont.diffExp=3.91076797859516,-3.12087670422208,-6.44337498780306,6.76335442876136,4.24292162636797,-9.85545922663988,-3.29690848658034,4.40059181052568
cont.diffExpScore=9.55544722244564

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=0.397897893630662
cont.tran.correlation=-0.535500681666537

tran.covariance=0.000985443547621284
cont.tran.covariance=-0.00169462555442369

tran.mean=55.6299666393051
cont.tran.mean=58.9104709523765

weightedLogRatios:
wLogRatio
Lung	1.11478656183184
cerebhem	0.865627833601653
cortex	1.5359304097374
heart	1.01379529261179
kidney	1.10032517001842
liver	0.789816908842069
stomach	0.887055849710462
testicle	0.981975709075908

cont.weightedLogRatios:
wLogRatio
Lung	0.281356895489688
cerebhem	-0.215419733121230
cortex	-0.430612274055098
heart	0.461683039203318
kidney	0.300070831475071
liver	-0.674125154374205
stomach	-0.230186989070258
testicle	0.303906649870868

varWeightedLogRatios=0.0536434387238067
cont.varWeightedLogRatios=0.172687190374746

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.15949690759811	0.0665451020160217	62.5064322028788	5.758349190692e-302	***
df.mm.trans1	0.0872203371463803	0.0582699567641714	1.49683202099113	0.134851588958434	   
df.mm.trans2	-0.283644283298057	0.052254728701559	-5.42810747172808	7.66338032686846e-08	***
df.mm.exp2	0.073710780504576	0.0689114954968048	1.06964418596885	0.285118648701445	   
df.mm.exp3	-0.0516503190728729	0.0689114954968049	-0.74951673447963	0.453777445357714	   
df.mm.exp4	-0.0218709054422809	0.0689114954968048	-0.317376734964269	0.751044814562328	   
df.mm.exp5	0.0727387037624943	0.0689114954968049	1.05553802363594	0.291514311931756	   
df.mm.exp6	0.113592979361704	0.0689114954968048	1.64838940938338	0.0996855386362968	.  
df.mm.exp7	-0.05358406200987	0.0689114954968048	-0.777577987875106	0.437059500948229	   
df.mm.exp8	0.00584670909993712	0.0689114954968049	0.084843741349485	0.932407933239888	   
df.mm.trans1:exp2	-0.0294537337237981	0.0646447129022429	-0.455624789738624	0.648789788888999	   
df.mm.trans2:exp2	0.0370932296563125	0.0515686412318518	0.71929817754053	0.47217804003703	   
df.mm.trans1:exp3	0.184414979354772	0.064644712902243	2.85274651360349	0.00445189219218595	** 
df.mm.trans2:exp3	0.0868435379934613	0.0515686412318518	1.6840377391953	0.0925844533553095	.  
df.mm.trans1:exp4	-0.0103614309574848	0.064644712902243	-0.160282728351716	0.872700898817806	   
df.mm.trans2:exp4	0.0136439140890996	0.0515686412318518	0.264577731023720	0.79140641727246	   
df.mm.trans1:exp5	-0.0629730533394137	0.064644712902243	-0.974140815423572	0.330296165495708	   
df.mm.trans2:exp5	-0.0585249984962837	0.0515686412318518	-1.13489510482070	0.256776601354191	   
df.mm.trans1:exp6	-0.137131481434518	0.064644712902243	-2.12131008520204	0.0342183890680644	*  
df.mm.trans2:exp6	-0.0548562925853977	0.0515686412318518	-1.06375291795579	0.287778064712948	   
df.mm.trans1:exp7	-0.00303513818947048	0.064644712902243	-0.0469510661151868	0.96256454625761	   
df.mm.trans2:exp7	0.0523919149081511	0.0515686412318518	1.01596461835397	0.30996912727943	   
df.mm.trans1:exp8	-0.0260202390985106	0.064644712902243	-0.402511480526783	0.6874206785595	   
df.mm.trans2:exp8	0.00702443473329985	0.0515686412318518	0.136215237894636	0.891687154344704	   
df.mm.trans1:probe2	0.475872103987953	0.0395866402948019	12.0210278125179	1.33823909738142e-30	***
df.mm.trans1:probe3	-0.0631034530970482	0.0395866402948019	-1.59405932473977	0.111337963678967	   
df.mm.trans1:probe4	-0.339176246785130	0.0395866402948019	-8.56794727360755	5.82401459059219e-17	***
df.mm.trans1:probe5	0.222485243023448	0.0395866402948019	5.62021028727368	2.67702680629665e-08	***
df.mm.trans1:probe6	-0.100713090352945	0.0395866402948019	-2.54411815710893	0.0111519836658876	*  
df.mm.trans1:probe7	-0.444419255355144	0.0395866402948019	-11.2264959098714	3.60587558528077e-27	***
df.mm.trans1:probe8	0.0711799062656118	0.0395866402948019	1.79807899168848	0.0725607283599381	.  
df.mm.trans1:probe9	-0.0765278579301335	0.0395866402948019	-1.93317385259851	0.0535854274845165	.  
df.mm.trans1:probe10	-0.091762421596607	0.0395866402948019	-2.31801488869103	0.0207127904002934	*  
df.mm.trans1:probe11	-0.20532664823939	0.0395866402948019	-5.1867662097698	2.74592908606926e-07	***
df.mm.trans1:probe12	-0.259996441059687	0.0395866402948019	-6.56778244184129	9.45941850072838e-11	***
df.mm.trans1:probe13	0.103498562772898	0.0395866402948019	2.61448210815930	0.00911306256688416	** 
df.mm.trans1:probe14	-0.213766971222088	0.0395866402948019	-5.39997760936934	8.91556679199183e-08	***
df.mm.trans1:probe15	-0.0252389330385785	0.0395866402948019	-0.637561885793391	0.523950684652602	   
df.mm.trans1:probe16	-0.156431472322170	0.0395866402948019	-3.9516228494569	8.48453726146776e-05	***
df.mm.trans1:probe17	-0.328258246746415	0.0395866402948019	-8.29214715625965	5.02717547318264e-16	***
df.mm.trans1:probe18	-0.311866877292445	0.0395866402948019	-7.87808399424582	1.14819278189651e-14	***
df.mm.trans1:probe19	-0.388271257170351	0.0395866402948019	-9.80813866190446	1.82325282004123e-21	***
df.mm.trans1:probe20	-0.379581730216034	0.0395866402948019	-9.58863210894604	1.23661949656318e-20	***
df.mm.trans1:probe21	-0.342915113135297	0.0395866402948019	-8.66239495399475	2.74808316086245e-17	***
df.mm.trans1:probe22	-0.370207181998831	0.0395866402948019	-9.35182120134208	9.39721067724418e-20	***
df.mm.trans2:probe2	-0.0727957068195861	0.0395866402948019	-1.83889580619816	0.0663199826401727	.  
df.mm.trans2:probe3	-0.0677086765581321	0.0395866402948019	-1.71039209323917	0.0876009722571278	.  
df.mm.trans2:probe4	-0.0990329637281216	0.0395866402948019	-2.50167639866942	0.0125695990200702	*  
df.mm.trans2:probe5	-0.00520174114229413	0.0395866402948019	-0.131401429966189	0.895492487822286	   
df.mm.trans2:probe6	-0.0379502335817006	0.0395866402948019	-0.958662652326266	0.3380331855022	   
df.mm.trans3:probe2	0.0914340055794508	0.0395866402948019	2.30971875608896	0.0211705366405669	*  
df.mm.trans3:probe3	0.156743786400434	0.0395866402948019	3.95951223021612	8.21457940592754e-05	***
df.mm.trans3:probe4	-0.142021059403199	0.0395866402948019	-3.58760072452644	0.000355082256406141	***
df.mm.trans3:probe5	0.292485515111454	0.0395866402948019	7.38849048399443	3.91320085947128e-13	***
df.mm.trans3:probe6	0.637464563496213	0.0395866402948019	16.1030226043183	2.00272431875138e-50	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.06707844218689	0.133004132414257	30.5785870586299	1.43021515964103e-134	***
df.mm.trans1	0.00937944834698837	0.116464545254870	0.080534795602065	0.9358330973857	   
df.mm.trans2	-0.0648613772167956	0.104441869422935	-0.621028497241283	0.534766833773648	   
df.mm.exp2	0.0919107328706397	0.137733858604872	0.667306745063402	0.504778510760214	   
df.mm.exp3	0.111406014849178	0.137733858604872	0.808849878872398	0.418854299973376	   
df.mm.exp4	0.0589856189004204	0.137733858604872	0.428257942512430	0.668584513680936	   
df.mm.exp5	-0.0126114426708353	0.137733858604872	-0.0915638521898583	0.927068668977743	   
df.mm.exp6	0.0157310846142094	0.137733858604872	0.114213634712278	0.909098569408978	   
df.mm.exp7	-0.112822620108203	0.137733858604872	-0.81913496979611	0.41296585956943	   
df.mm.exp8	0.0615384391473736	0.137733858604872	0.446792384753511	0.655152090237961	   
df.mm.trans1:exp2	-0.0981724994510434	0.129205812212316	-0.759814885801904	0.447600555780335	   
df.mm.trans2:exp2	0.0245602587466577	0.103070581891559	0.238285826041980	0.81172356062732	   
df.mm.trans1:exp3	-0.101208122166494	0.129205812212316	-0.783309360728948	0.433689172143347	   
df.mm.trans2:exp3	0.0731971437412657	0.103070581891559	0.710165232386837	0.47781923614741	   
df.mm.trans1:exp4	0.0317233501791009	0.129205812212316	0.245525720831906	0.806115593853052	   
df.mm.trans2:exp4	-0.0111484632098741	0.103070581891559	-0.108163386732438	0.913894598815894	   
df.mm.trans1:exp5	0.0374588690105771	0.129205812212316	0.289916284485895	0.771959258288948	   
df.mm.trans2:exp5	0.0332270906312642	0.103070581891559	0.322372203799359	0.7472592809976	   
df.mm.trans1:exp6	-0.0673198674823945	0.129205812212316	-0.521028166842616	0.602498723507384	   
df.mm.trans2:exp6	0.167435886017682	0.103070581891559	1.62447793487614	0.104687924004838	   
df.mm.trans1:exp7	0.0894676520993724	0.129205812212316	0.692442937105301	0.488870443084958	   
df.mm.trans2:exp7	0.216031465970370	0.103070581891559	2.09595659601163	0.0364157949413089	*  
df.mm.trans1:exp8	-0.00495890740227852	0.129205812212316	-0.0383799096756563	0.969394844710218	   
df.mm.trans2:exp8	-0.00955761121566734	0.103070581891559	-0.0927287984628139	0.926143423303791	   
df.mm.trans1:probe2	0.00887512797291245	0.0791220779305097	0.112170056766042	0.9107181505585	   
df.mm.trans1:probe3	-0.0449294680597944	0.0791220779305097	-0.567849950796976	0.570304351272625	   
df.mm.trans1:probe4	0.0123883578632251	0.0791220779305096	0.156572706218679	0.875623141783623	   
df.mm.trans1:probe5	-0.00369766485887444	0.0791220779305096	-0.0467336672088159	0.962737758127798	   
df.mm.trans1:probe6	0.00176388683763752	0.0791220779305096	0.0222932319748564	0.982219891571644	   
df.mm.trans1:probe7	-0.0388230813484557	0.0791220779305097	-0.490673176993061	0.623799072220893	   
df.mm.trans1:probe8	-0.104336666856648	0.0791220779305096	-1.31867955930434	0.187672965036972	   
df.mm.trans1:probe9	-0.0201217599694696	0.0791220779305097	-0.254312835251141	0.79932258540691	   
df.mm.trans1:probe10	-0.0405330030915477	0.0791220779305097	-0.512284360468219	0.608600650409987	   
df.mm.trans1:probe11	0.0621651200666356	0.0791220779305096	0.785686140867448	0.43229593692844	   
df.mm.trans1:probe12	-0.0240647595753743	0.0791220779305097	-0.304147214087446	0.76109888343347	   
df.mm.trans1:probe13	-0.0666106583819384	0.0791220779305096	-0.841871954379667	0.400124109510315	   
df.mm.trans1:probe14	-0.119480882219348	0.0791220779305096	-1.51008271451470	0.13143740175698	   
df.mm.trans1:probe15	-0.0664402527947602	0.0791220779305096	-0.839718249729394	0.401330099913319	   
df.mm.trans1:probe16	0.0310583932733349	0.0791220779305097	0.392537634067352	0.694770929489555	   
df.mm.trans1:probe17	0.0038540550380183	0.0791220779305097	0.0487102353581157	0.961162999724704	   
df.mm.trans1:probe18	-0.0419010584510483	0.0791220779305097	-0.529574798172624	0.596561224193459	   
df.mm.trans1:probe19	-0.0462867480127266	0.0791220779305096	-0.585004201398486	0.55871830053051	   
df.mm.trans1:probe20	-0.0269027073353502	0.0791220779305097	-0.340015177040446	0.73393892458322	   
df.mm.trans1:probe21	-0.0337679344892282	0.0791220779305097	-0.426782705566523	0.669658312610291	   
df.mm.trans1:probe22	0.0655502710834172	0.0791220779305097	0.828470040195201	0.407664106544651	   
df.mm.trans2:probe2	-0.0336285035326593	0.0791220779305096	-0.425020479899354	0.670941892776396	   
df.mm.trans2:probe3	0.00622517928351616	0.0791220779305097	0.0786781571760986	0.937309302670067	   
df.mm.trans2:probe4	-0.0424467898532362	0.0791220779305096	-0.536472132222258	0.591789076046405	   
df.mm.trans2:probe5	-0.0367093821643051	0.0791220779305096	-0.463958772626595	0.642809966384109	   
df.mm.trans2:probe6	-0.0525649296036016	0.0791220779305096	-0.664352238698378	0.506666137611876	   
df.mm.trans3:probe2	-0.0564635765982582	0.0791220779305096	-0.713626058302568	0.475677234124733	   
df.mm.trans3:probe3	0.0254765676999921	0.0791220779305096	0.321990629750237	0.747548221262178	   
df.mm.trans3:probe4	0.101405415681352	0.0791220779305096	1.28163236271946	0.200361991732733	   
df.mm.trans3:probe5	-0.0379606593869981	0.0791220779305096	-0.479773286797874	0.631526467238424	   
df.mm.trans3:probe6	0.00829975788512281	0.0791220779305096	0.104898128337987	0.916484285190797