chr11.4332_chr11_99500703_99501076_-_1.R 

fitVsDatCorrelation=0.88459848206419
cont.fitVsDatCorrelation=0.232776745746460

fstatistic=9344.01958385089,43,485
cont.fstatistic=2139.92605270421,43,485

residuals=-0.604865443363649,-0.0820687440847858,-0.000856752086921867,0.0827308349650526,0.556847049350437
cont.residuals=-0.691912983907398,-0.219373089540862,-0.0548476970486624,0.175379143323282,1.22788604592702

predictedValues:
Include	Exclude	Both
chr11.4332_chr11_99500703_99501076_-_1.R.tl.Lung	48.7169588384933	58.407261770672	66.5171799581743
chr11.4332_chr11_99500703_99501076_-_1.R.tl.cerebhem	51.9844441231112	58.5514813197552	82.4927503919116
chr11.4332_chr11_99500703_99501076_-_1.R.tl.cortex	49.6057341363096	84.8564582787212	105.950369822656
chr11.4332_chr11_99500703_99501076_-_1.R.tl.heart	48.9204324398574	67.8449275423531	77.2694125560001
chr11.4332_chr11_99500703_99501076_-_1.R.tl.kidney	50.2346145715744	58.9005438523186	66.7895841562969
chr11.4332_chr11_99500703_99501076_-_1.R.tl.liver	52.9415378199492	58.7127287204544	67.5939507638023
chr11.4332_chr11_99500703_99501076_-_1.R.tl.stomach	46.9774983310525	55.0494579130183	66.6978152974535
chr11.4332_chr11_99500703_99501076_-_1.R.tl.testicle	48.440381683198	66.5492420177385	78.2617602034251


diffExp=-9.69030293217874,-6.567037196644,-35.2507241424116,-18.9244951024956,-8.66592928074419,-5.77119090050525,-8.07195958196577,-18.1088603345405
diffExpScore=0.991075452544016
diffExp1.5=0,0,-1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,-1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,-1,-1,0,0,0,-1
diffExp1.3Score=0.75
diffExp1.2=0,0,-1,-1,0,0,0,-1
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	65.2733850593497	66.9837243629277	64.815840802661
cerebhem	61.5225699487287	61.7713588168765	65.420862805195
cortex	60.514798159934	71.5406540346841	65.9322094283959
heart	63.7724716664613	59.8737531785825	63.3619380479582
kidney	67.8314773060133	66.0357705365833	63.6271817089536
liver	65.8702173868427	69.2575898427737	64.3689506769054
stomach	61.6790801443675	59.8886271781478	70.5579246609217
testicle	61.7764160882259	58.9687372247258	60.2250182964956
cont.diffExp=-1.71033930357802,-0.248788868147813,-11.0258558747501,3.89871848787877,1.79570676943001,-3.38737245593099,1.79045296621966,2.80767886350013
cont.diffExpScore=3.76633743768438

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=-0.080125550070398
cont.tran.correlation=0.270156744376947

tran.covariance=-0.000356409248673549
cont.tran.covariance=0.000839456866105129

tran.mean=56.6683564599111
cont.tran.mean=63.9100394334515

weightedLogRatios:
wLogRatio
Lung	-0.721431301607507
cerebhem	-0.477087701551282
cortex	-2.24004423204157
heart	-1.32568260844191
kidney	-0.635991557772486
liver	-0.416038013629616
stomach	-0.622987288558342
testicle	-1.28286397626156

cont.weightedLogRatios:
wLogRatio
Lung	-0.108414829358798
cerebhem	-0.0166328594567789
cortex	-0.700740631310351
heart	0.260142004432159
kidney	0.112781975910199
liver	-0.211254460284207
stomach	0.120991149936258
testicle	0.190720726305981

varWeightedLogRatios=0.382975616270332
cont.varWeightedLogRatios=0.0947970524240791

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.95471901842451	0.0760565887313537	51.9970601415392	1.82289333363213e-200	***
df.mm.trans1	-0.0693255818757889	0.0608872767001209	-1.13858897347681	0.255436717822639	   
df.mm.trans2	0.0816461992303173	0.0608872767001208	1.34094023670064	0.180567522088423	   
df.mm.exp2	-0.147866671489272	0.0815322115582437	-1.81359819221439	0.0703575132364927	.  
df.mm.exp3	-0.0739104059598279	0.0815322115582437	-0.90651786020828	0.365111963366847	   
df.mm.exp4	0.00411442649267485	0.0815322115582437	0.0504638156385057	0.959773559376467	   
df.mm.exp5	0.0350003356967585	0.0815322115582437	0.429282304844086	0.667908421969258	   
df.mm.exp6	0.072319130176475	0.0815322115582437	0.887000717806027	0.375518137730114	   
df.mm.exp7	-0.0982786223243385	0.0815322115582437	-1.20539625316225	0.228638141445141	   
df.mm.exp8	-0.0377903231988694	0.0815322115582438	-0.463501755645048	0.643212688857638	   
df.mm.trans1:exp2	0.212783993597175	0.0639591288802861	3.32687447941088	0.000944951511375413	***
df.mm.trans2:exp2	0.150332833802019	0.0639591288802862	2.35045155295034	0.0191502932542866	*  
df.mm.trans1:exp3	0.091989640355391	0.0639591288802862	1.43825661740281	0.151006199750630	   
df.mm.trans2:exp3	0.447431281319987	0.0639591288802862	6.99558122746567	8.81356801101957e-12	***
df.mm.trans1:exp4	5.35237824967867e-05	0.0639591288802861	0.000836843519194399	0.99933263964931	   
df.mm.trans2:exp4	0.145669969624502	0.0639591288802861	2.27754774298374	0.0231879639723228	*  
df.mm.trans1:exp5	-0.00432321355980352	0.0639591288802862	-0.0675933777630928	0.946137183043365	   
df.mm.trans2:exp5	-0.0265902390881140	0.0639591288802862	-0.41573798070145	0.677785626101879	   
df.mm.trans1:exp6	0.0108419143160909	0.0639591288802861	0.169513164201845	0.865463697758252	   
df.mm.trans2:exp6	-0.067102810722432	0.0639591288802861	-1.04915141743143	0.294630945777362	   
df.mm.trans1:exp7	0.0619201502388157	0.0639591288802862	0.968120600183801	0.333466660478967	   
df.mm.trans2:exp7	0.0390704107774263	0.0639591288802862	0.610865273830657	0.541574942855343	   
df.mm.trans1:exp8	0.0320969211170543	0.0639591288802862	0.501834869845255	0.616011413677852	   
df.mm.trans2:exp8	0.168292250817136	0.0639591288802862	2.63124676279023	0.00877806555044017	** 
df.mm.trans1:probe2	-0.0329527978539777	0.0437898220576411	-0.752521848812299	0.452102370295292	   
df.mm.trans1:probe3	-0.0215665611510057	0.0437898220576411	-0.492501685040358	0.622587602281793	   
df.mm.trans1:probe4	0.0954807000262314	0.0437898220576411	2.18043133174985	0.0297054333429606	*  
df.mm.trans1:probe5	-0.000827759897677473	0.0437898220576411	-0.0189030203545445	0.984926243904365	   
df.mm.trans1:probe6	-0.0299933620604531	0.0437898220576411	-0.684939117153125	0.49370954106813	   
df.mm.trans2:probe2	0.197665077788974	0.0437898220576411	4.51395024005315	7.99583882984976e-06	***
df.mm.trans2:probe3	0.0471401604675082	0.0437898220576411	1.07650952327363	0.282234628383279	   
df.mm.trans2:probe4	0.0840912665116603	0.0437898220576411	1.92033816444766	0.0554012946931902	.  
df.mm.trans2:probe5	0.0735590857039296	0.0437898220576411	1.67982152581262	0.0936360210990204	.  
df.mm.trans2:probe6	0.094744566925172	0.0437898220576411	2.16362073361382	0.0309810834860730	*  
df.mm.trans3:probe2	0.344422382063658	0.0437898220576411	7.86535240107372	2.40997787807464e-14	***
df.mm.trans3:probe3	-0.0729927598028604	0.0437898220576411	-1.66688870547999	0.0961821216178615	.  
df.mm.trans3:probe4	0.548958896291359	0.0437898220576411	12.5362212152577	2.00073974385132e-31	***
df.mm.trans3:probe5	-0.0794237322656401	0.0437898220576411	-1.81374868710573	0.0703342914874061	.  
df.mm.trans3:probe6	0.207389302057079	0.0437898220576411	4.73601609488364	2.86615111732969e-06	***
df.mm.trans3:probe7	0.291303753345556	0.0437898220576411	6.65231644380992	7.80508472871225e-11	***
df.mm.trans3:probe8	0.374780446735668	0.0437898220576411	8.55861999718427	1.51547078414627e-16	***
df.mm.trans3:probe9	0.000524539299283644	0.0437898220576411	0.0119785665854770	0.990447640850236	   
df.mm.trans3:probe10	0.689243409806808	0.0437898220576411	15.7398084171146	2.15967262180613e-45	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.15703029648321	0.158607879578334	26.2094815688531	5.71880919395633e-95	***
df.mm.trans1	0.000605285488416272	0.12697390208778	0.00476700706573405	0.996198453158972	   
df.mm.trans2	0.0397202100884927	0.12697390208778	0.312821843192889	0.754550484693762	   
df.mm.exp2	-0.14948131805356	0.170026705224214	-0.879163763459623	0.379747856990794	   
df.mm.exp3	-0.0269572887890768	0.170026705224214	-0.158547380857191	0.874091482589453	   
df.mm.exp4	-0.112787497807144	0.170026705224214	-0.66335166383664	0.507420521375727	   
df.mm.exp5	0.0426981495706060	0.170026705224214	0.251126136416629	0.80182294921037	   
df.mm.exp6	0.0494037447460124	0.170026705224214	0.290564618545444	0.771508525394147	   
df.mm.exp7	-0.253486572768581	0.170026705224214	-1.49086328782475	0.136647464982092	   
df.mm.exp8	-0.109042764765275	0.170026705224214	-0.641327282214168	0.521613013223025	   
df.mm.trans1:exp2	0.0903010428675285	0.133379921195409	0.677021264206872	0.49871524368429	   
df.mm.trans2:exp2	0.0684714556013267	0.133379921195409	0.513356545630375	0.607935700810686	   
df.mm.trans1:exp3	-0.048739152108409	0.133379921195409	-0.365415961200064	0.714960236708731	   
df.mm.trans2:exp3	0.0927734948770359	0.133379921195409	0.695558177314543	0.487038702025431	   
df.mm.trans1:exp4	0.089524742752103	0.133379921195409	0.671201046977262	0.502411997895118	   
df.mm.trans2:exp4	0.000576059656825211	0.133379921195409	0.00431893835040773	0.99655577233783	   
df.mm.trans1:exp5	-0.00425616902251844	0.133379921195409	-0.0319101179875712	0.974556857059609	   
df.mm.trans2:exp5	-0.0569512464589297	0.133379921195409	-0.426985156000303	0.669579620182228	   
df.mm.trans1:exp6	-0.0403017155683454	0.133379921195409	-0.30215729029635	0.762661690531132	   
df.mm.trans2:exp6	-0.0160206749914336	0.133379921195409	-0.120113093843881	0.904443299825592	   
df.mm.trans1:exp7	0.196847014849131	0.133379921195409	1.47583694070968	0.140636584974565	   
df.mm.trans2:exp7	0.141523526468817	0.133379921195409	1.06105570613944	0.289192668513426	   
df.mm.trans1:exp8	0.0539800659893611	0.133379921195409	0.404709085937136	0.685869789844458	   
df.mm.trans2:exp8	-0.0183994792355766	0.133379921195409	-0.137947894035867	0.89033885072119	   
df.mm.trans1:probe2	0.0337565937698985	0.0913189894462334	0.369655796396802	0.711800319627444	   
df.mm.trans1:probe3	0.137713593615321	0.0913189894462334	1.50804990780591	0.132192853445814	   
df.mm.trans1:probe4	-0.0160483685228278	0.0913189894462334	-0.175739664007963	0.860571822308592	   
df.mm.trans1:probe5	0.0276179852698557	0.0913189894462334	0.302434197282884	0.762450746342964	   
df.mm.trans1:probe6	0.152140863681845	0.0913189894462334	1.66603753068710	0.0963516239267208	.  
df.mm.trans2:probe2	0.0483425580566875	0.0913189894462334	0.529381220158492	0.596783239124001	   
df.mm.trans2:probe3	0.0920890208997941	0.0913189894462334	1.00843232561190	0.313749797778934	   
df.mm.trans2:probe4	0.0322515889104659	0.0913189894462334	0.353175052703084	0.724110659906557	   
df.mm.trans2:probe5	-0.00215715104373530	0.0913189894462334	-0.0236221519403189	0.981163717919965	   
df.mm.trans2:probe6	-0.047339403173108	0.0913189894462334	-0.518396047308215	0.604418386758765	   
df.mm.trans3:probe2	0.040377714428852	0.0913189894462334	0.442161205174368	0.658569656320927	   
df.mm.trans3:probe3	-0.0265068238886749	0.0913189894462334	-0.290266285790225	0.771736594534215	   
df.mm.trans3:probe4	-0.0368019561886004	0.0913189894462334	-0.403004417939476	0.687122562107662	   
df.mm.trans3:probe5	0.0307804529994963	0.0913189894462334	0.337065195159864	0.736213565892933	   
df.mm.trans3:probe6	-0.144924183487642	0.0913189894462334	-1.58701037283127	0.113162002132036	   
df.mm.trans3:probe7	-0.0249987073418302	0.0913189894462334	-0.273751467174841	0.78439216611757	   
df.mm.trans3:probe8	-0.0479006549680418	0.0913189894462334	-0.524542105190998	0.600141198854152	   
df.mm.trans3:probe9	-0.0272259652698419	0.0913189894462334	-0.298141333308029	0.765722975508121	   
df.mm.trans3:probe10	-0.0208574937377361	0.0913189894462334	-0.228402590350789	0.819429543359449