chr14.7610_chr14_26068742_26073952_+_2.R 

fitVsDatCorrelation=0.878541340909632
cont.fitVsDatCorrelation=0.265442933368498

fstatistic=14049.9049777132,53,715
cont.fstatistic=3438.51370936642,53,715

residuals=-0.738499448288739,-0.0720949013919539,-0.00578225533738125,0.066495150505846,0.62609179208939
cont.residuals=-0.624208170226803,-0.187364756613942,-0.0289413054391369,0.135866873348083,1.02228427752624

predictedValues:
Include	Exclude	Both
chr14.7610_chr14_26068742_26073952_+_2.R.tl.Lung	65.2417115490848	61.8742449275909	65.959613171975
chr14.7610_chr14_26068742_26073952_+_2.R.tl.cerebhem	60.931529980164	59.0299119442202	66.1806937823715
chr14.7610_chr14_26068742_26073952_+_2.R.tl.cortex	67.0740589567963	70.9813811387795	64.6316196586295
chr14.7610_chr14_26068742_26073952_+_2.R.tl.heart	69.4571570026102	72.4974556961691	61.1367619610295
chr14.7610_chr14_26068742_26073952_+_2.R.tl.kidney	64.1850820460026	62.5741718434919	68.0186287884052
chr14.7610_chr14_26068742_26073952_+_2.R.tl.liver	67.3852677903322	67.5777309536626	67.1600571156291
chr14.7610_chr14_26068742_26073952_+_2.R.tl.stomach	72.0730629250075	81.3169106723321	58.1331015081018
chr14.7610_chr14_26068742_26073952_+_2.R.tl.testicle	66.2460407001626	66.5076993542581	62.08536389011


diffExp=3.36746662149390,1.90161803594384,-3.90732218198315,-3.04029869355890,1.61091020251074,-0.192463163330373,-9.24384774732458,-0.261658654095442
diffExpScore=2.18525627538846
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	62.7143086749362	57.4735639070639	59.8604151589698
cerebhem	58.8286769807567	60.9822388094194	62.1464693619764
cortex	62.2290782854556	66.6352693550698	59.3542488567805
heart	64.2177198708376	64.5595509713247	54.9337536730085
kidney	62.8194291027431	59.156889669621	57.4687339217375
liver	62.8281004062178	61.1492195790893	63.9310507606995
stomach	62.8705938859646	58.1559848170927	63.4161891389062
testicle	62.8565065406134	60.4320033766303	73.226596361553
cont.diffExp=5.24074476787225,-2.15356182866270,-4.40619106961419,-0.341831100487127,3.66253943312214,1.67888082712840,4.71460906887184,2.42450316398314
cont.diffExpScore=2.08320645159704

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=0.95226414819916
cont.tran.correlation=0.0628106852055917

tran.covariance=0.00495311688106225
cont.tran.covariance=6.97651118375279e-05

tran.mean=67.1845885925415
cont.tran.mean=61.7443208895523

weightedLogRatios:
wLogRatio
Lung	0.220014099207523
cerebhem	0.129803067505036
cortex	-0.239736176410136
heart	-0.182595440901931
kidney	0.105461739275428
liver	-0.0120125813000491
stomach	-0.523484284504111
testicle	-0.0165381434044169

cont.weightedLogRatios:
wLogRatio
Lung	0.357344595432889
cerebhem	-0.147142344910479
cortex	-0.28493632721412
heart	-0.0221111564070236
kidney	0.246906966948578
liver	0.111777368703508
stomach	0.319757974549899
testicle	0.162109484067351

varWeightedLogRatios=0.0582805498101854
cont.varWeightedLogRatios=0.051981155686945

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.87866261065295	0.0674962005551296	72.2805516536913	0	***
df.mm.trans1	-0.0928812139892509	0.059937932366227	-1.54962325730119	0.121674457389242	   
df.mm.trans2	-0.733143698286021	0.0545213438424044	-13.4469117343328	6.53654133400135e-37	***
df.mm.exp2	-0.118754110361683	0.0735028735292116	-1.61563901735744	0.106613516460497	   
df.mm.exp3	0.185350815627128	0.0735028735292116	2.52168121772090	0.0118957300024386	*  
df.mm.exp4	0.296987833277606	0.0735028735292116	4.04049282725765	5.91170492249693e-05	***
df.mm.exp5	-0.0358185976123945	0.0735028735292116	-0.487308807024523	0.626188874208552	   
df.mm.exp6	0.102465841011074	0.0735028735292116	1.39403857415659	0.163739019077611	   
df.mm.exp7	0.499138734032568	0.0735028735292116	6.79073769591062	2.34760566218200e-11	***
df.mm.exp8	0.148022749174314	0.0735028735292116	2.01383622254559	0.0444008627082667	*  
df.mm.trans1:exp2	0.0504058726974922	0.069794426821732	0.722204837733509	0.470404679682275	   
df.mm.trans2:exp2	0.0716943902768769	0.0587721669746967	1.21986977794682	0.222916457033785	   
df.mm.trans1:exp3	-0.157652461196546	0.069794426821732	-2.25881160395829	0.0241955635108253	*  
df.mm.trans2:exp3	-0.0480372280819982	0.0587721669746967	-0.817346552879013	0.414002676555143	   
df.mm.trans1:exp4	-0.23437672886007	0.069794426821732	-3.35810091912800	0.000826380451954444	***
df.mm.trans2:exp4	-0.138540383502668	0.0587721669746967	-2.35724477476412	0.0186796938105121	*  
df.mm.trans1:exp5	0.0194904023556052	0.069794426821732	0.279254422496904	0.780130336381612	   
df.mm.trans2:exp5	0.0470671825961259	0.0587721669746967	0.800841367928288	0.423489514185955	   
df.mm.trans1:exp6	-0.0701384378297335	0.069794426821732	-1.00492891801920	0.315271043781465	   
df.mm.trans2:exp6	-0.0142913536204169	0.0587721669746967	-0.243165334138007	0.80794706411206	   
df.mm.trans1:exp7	-0.399557378759598	0.069794426821732	-5.72477484169534	1.52450486422014e-08	***
df.mm.trans2:exp7	-0.225888753382728	0.0587721669746967	-3.84346477270406	0.000132106831122017	***
df.mm.trans1:exp8	-0.132746061176918	0.069794426821732	-1.90195789580702	0.0575782819485753	.  
df.mm.trans2:exp8	-0.0758090460751305	0.0587721669746967	-1.28988005679234	0.197509343988484	   
df.mm.trans1:probe2	-0.803104217734673	0.0382279819584062	-21.0082818028032	1.10427691269893e-76	***
df.mm.trans1:probe3	-0.634411948974202	0.0382279819584062	-16.5954862504767	1.45047408697323e-52	***
df.mm.trans1:probe4	-0.646413891402454	0.0382279819584062	-16.9094432477702	3.27645299304741e-54	***
df.mm.trans1:probe5	-0.859645186831926	0.0382279819584062	-22.4873284644546	4.16302938584319e-85	***
df.mm.trans1:probe6	-0.338709825482582	0.0382279819584062	-8.86025911205865	6.26863881898993e-18	***
df.mm.trans1:probe7	-0.955359129309577	0.0382279819584062	-24.9910950138318	1.46444334281822e-99	***
df.mm.trans1:probe8	-0.644337445294668	0.0382279819584062	-16.8551258079942	6.32612979740491e-54	***
df.mm.trans1:probe9	-1.05790833108770	0.0382279819584062	-27.6736640777627	3.76600277707563e-115	***
df.mm.trans1:probe10	-0.95009997900495	0.0382279819584062	-24.8535216961937	9.19981286830085e-99	***
df.mm.trans1:probe11	-0.510099769779261	0.0382279819584062	-13.3436227508497	1.98758958353801e-36	***
df.mm.trans1:probe12	-0.290226996171587	0.0382279819584062	-7.59200411068958	9.8608382957744e-14	***
df.mm.trans1:probe13	-0.690451615851754	0.0382279819584062	-18.0614194231596	2.33919386524210e-60	***
df.mm.trans1:probe14	-0.628622590122231	0.0382279819584062	-16.4440432876159	8.9275872315333e-52	***
df.mm.trans1:probe15	-0.458914556314561	0.0382279819584062	-12.0046764910029	2.24346755320199e-30	***
df.mm.trans1:probe16	-0.792765647386839	0.0382279819584062	-20.7378367042603	3.71437363204888e-75	***
df.mm.trans1:probe17	-0.939507746409555	0.0382279819584062	-24.5764410852705	3.71748168228656e-97	***
df.mm.trans1:probe18	-0.924171509573476	0.0382279819584062	-24.1752627847062	7.82643634421359e-95	***
df.mm.trans1:probe19	-0.959127797060901	0.0382279819584062	-25.0896790237182	3.9226546643476e-100	***
df.mm.trans1:probe20	-0.847526253976807	0.0382279819584062	-22.1703111322736	2.71784486174626e-83	***
df.mm.trans1:probe21	-0.934135643703382	0.0382279819584062	-24.4359130628388	2.4236062061996e-96	***
df.mm.trans1:probe22	-0.934201918050477	0.0382279819584062	-24.4376467234638	2.36820727678987e-96	***
df.mm.trans2:probe2	-0.0207665953895957	0.0382279819584062	-0.543230228898578	0.587140606085355	   
df.mm.trans2:probe3	-0.00931537457872412	0.0382279819584062	-0.243679475125307	0.807548969749896	   
df.mm.trans2:probe4	-0.218883407577396	0.0382279819584062	-5.72573796376569	1.5162578723652e-08	***
df.mm.trans2:probe5	0.00369986409516632	0.0382279819584062	0.0967841854480296	0.92292490485846	   
df.mm.trans2:probe6	0.0411165660206790	0.0382279819584062	1.07556203373267	0.282485972336171	   
df.mm.trans3:probe2	0.197913630358832	0.0382279819584062	5.17719273212411	2.93075348550912e-07	***
df.mm.trans3:probe3	0.272208738332879	0.0382279819584062	7.12066722823754	2.62203788436762e-12	***
df.mm.trans3:probe4	0.075497370154467	0.0382279819584062	1.97492429070966	0.0486610277515210	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.1907788067976	0.136235020044457	30.7613916409309	5.05890387963775e-133	***
df.mm.trans1	0.0317181076239873	0.120979334394781	0.262177898255618	0.793259807487897	   
df.mm.trans2	-0.136134170406940	0.11004643683838	-1.23706113817091	0.216470523119836	   
df.mm.exp2	-0.0421811897001882	0.148358950077469	-0.28431847002262	0.776248652839492	   
df.mm.exp3	0.148633409813995	0.148358950077469	1.0018499708739	0.316754985756397	   
df.mm.exp4	0.225839995011788	0.148358950077469	1.52225393138641	0.128387587128431	   
df.mm.exp5	0.0713171496050697	0.148358950077469	0.480706755931002	0.630871980388443	   
df.mm.exp6	-0.00198491519467405	0.148358950077469	-0.0133791402112079	0.989329041255105	   
df.mm.exp7	-0.0434111116197434	0.148358950077469	-0.292608646779148	0.769906195525903	   
df.mm.exp8	-0.149084692994827	0.148358950077469	-1.00489180408043	0.315288904070035	   
df.mm.trans1:exp2	-0.0217790006646329	0.140873783395907	-0.154599387761354	0.877180781400633	   
df.mm.trans2:exp2	0.101438760473335	0.118626341631099	0.855111597294191	0.392775808506665	   
df.mm.trans1:exp3	-0.156400652895542	0.140873783395907	-1.11021830411127	0.267278197634796	   
df.mm.trans2:exp3	-0.00072448648846872	0.118626341631099	-0.00610729858568604	0.995128814591761	   
df.mm.trans1:exp4	-0.202150442085512	0.140873783395907	-1.43497560165183	0.151731311781699	   
df.mm.trans2:exp4	-0.109577010233311	0.118626341631099	-0.923715666576576	0.355945990764769	   
df.mm.trans1:exp5	-0.0696423734972489	0.140873783395907	-0.494360070542922	0.62120375723336	   
df.mm.trans2:exp5	-0.0424491719767705	0.118626341631099	-0.357839341524817	0.720569155976075	   
df.mm.trans1:exp6	0.00379771715182534	0.140873783395907	0.0269582960028294	0.978500519154856	   
df.mm.trans2:exp6	0.0639769308998436	0.118626341631099	0.539314708859499	0.589837616548652	   
df.mm.trans1:exp7	0.0459000300887632	0.140873783395907	0.325823790504492	0.744653010171074	   
df.mm.trans2:exp7	0.0552148216727111	0.118626341631099	0.465451609764859	0.641749817664464	   
df.mm.trans1:exp8	0.151349517448121	0.140873783395907	1.07436255206388	0.283022646317882	   
df.mm.trans2:exp8	0.199278430895691	0.118626341631099	1.67988347407190	0.0934168244007604	.  
df.mm.trans1:probe2	-0.067451116105988	0.077159748927035	-0.874174903935627	0.382316531219234	   
df.mm.trans1:probe3	-0.168621109138817	0.077159748927035	-2.18535067160821	0.0291869419959206	*  
df.mm.trans1:probe4	-0.150664082954822	0.077159748927035	-1.95262536555549	0.0512538380293772	.  
df.mm.trans1:probe5	-0.073619409486083	0.077159748927035	-0.954116757892772	0.340346993635576	   
df.mm.trans1:probe6	-0.193634892786695	0.077159748927035	-2.50953243730489	0.0123090619676879	*  
df.mm.trans1:probe7	-0.166975410404495	0.077159748927035	-2.16402221010844	0.0307930768667274	*  
df.mm.trans1:probe8	-0.139648785682287	0.077159748927035	-1.80986573471543	0.0707363626571001	.  
df.mm.trans1:probe9	-0.0464641806042767	0.077159748927035	-0.602181594035705	0.547244177056047	   
df.mm.trans1:probe10	-0.178725187110347	0.077159748927035	-2.31630078629928	0.0208237244701972	*  
df.mm.trans1:probe11	-0.104978990157219	0.077159748927035	-1.36054084697050	0.174087567917299	   
df.mm.trans1:probe12	-0.0805959082810872	0.077159748927035	-1.04453305514643	0.296591843327057	   
df.mm.trans1:probe13	-0.13159889419877	0.077159748927035	-1.70553813392025	0.0885284317738309	.  
df.mm.trans1:probe14	-0.131894900880305	0.077159748927035	-1.70937441754806	0.0878155288167218	.  
df.mm.trans1:probe15	-0.0619962677761157	0.077159748927035	-0.803479387092635	0.421964732122885	   
df.mm.trans1:probe16	-0.153789481675241	0.077159748927035	-1.99313092400896	0.0466267203783923	*  
df.mm.trans1:probe17	-0.044924815247594	0.077159748927035	-0.58223122641413	0.560594484263261	   
df.mm.trans1:probe18	-0.00181537137027725	0.077159748927035	-0.0235274400904794	0.98123611487837	   
df.mm.trans1:probe19	-0.00096533351313847	0.077159748927035	-0.0125108431087732	0.990021541782564	   
df.mm.trans1:probe20	-0.091339383104882	0.077159748927035	-1.18376983304152	0.236897587917508	   
df.mm.trans1:probe21	-0.0114361480927499	0.077159748927035	-0.14821391012514	0.882215742470568	   
df.mm.trans1:probe22	-0.180449722881623	0.077159748927035	-2.33865098566174	0.019628124159683	*  
df.mm.trans2:probe2	-0.00626125941673755	0.077159748927035	-0.0811467054235546	0.935347991103116	   
df.mm.trans2:probe3	0.0515227602461686	0.077159748927035	0.667741419102987	0.504514133494747	   
df.mm.trans2:probe4	-0.0403870421864211	0.077159748927035	-0.523421119794111	0.600843409867782	   
df.mm.trans2:probe5	-0.111882401792828	0.077159748927035	-1.45000992549403	0.147494248954177	   
df.mm.trans2:probe6	0.0738124186842479	0.077159748927035	0.956618181249494	0.339083338327991	   
df.mm.trans3:probe2	0.00843597308994593	0.077159748927035	0.109331266719430	0.912970424531717	   
df.mm.trans3:probe3	-0.000215589436993946	0.077159748927035	-0.00279406607709176	0.997771440076744	   
df.mm.trans3:probe4	0.0143903918864303	0.077159748927035	0.186501279313886	0.85210457795221