chr7.22377_chr7_80136557_80141508_+_2.R 

fitVsDatCorrelation=0.933245893409156
cont.fitVsDatCorrelation=0.268468727240433

fstatistic=6927.74242043392,59,853
cont.fstatistic=951.036301140651,59,853

residuals=-1.22220112949738,-0.112993444282575,-0.00788450239722461,0.0987372301135056,0.992360911301088
cont.residuals=-0.894423584654457,-0.340393900806717,-0.144122773006820,0.200720230661457,2.39878311106211

predictedValues:
Include	Exclude	Both
chr7.22377_chr7_80136557_80141508_+_2.R.tl.Lung	71.044699173477	56.1515612966715	100.881290911283
chr7.22377_chr7_80136557_80141508_+_2.R.tl.cerebhem	58.9477283963692	70.4034516340287	76.8099995489425
chr7.22377_chr7_80136557_80141508_+_2.R.tl.cortex	77.6463121006157	94.54114188001	126.222615116008
chr7.22377_chr7_80136557_80141508_+_2.R.tl.heart	67.3616709273467	52.9674860851703	87.8099340786988
chr7.22377_chr7_80136557_80141508_+_2.R.tl.kidney	66.0208959817517	56.0756785448171	102.615220306013
chr7.22377_chr7_80136557_80141508_+_2.R.tl.liver	63.4146042560123	57.3363317698286	100.658682555749
chr7.22377_chr7_80136557_80141508_+_2.R.tl.stomach	74.3698763708856	106.468581836919	156.794806534907
chr7.22377_chr7_80136557_80141508_+_2.R.tl.testicle	60.4587352796318	60.2458078026625	100.982742703690


diffExp=14.8931378768055,-11.4557232376595,-16.8948297793942,14.3941848421765,9.94521743693462,6.07827248618371,-32.0987054660339,0.212927476969284
diffExpScore=6.65428880742692
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,-1,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,0,0,-1,0
diffExp1.3Score=0.5
diffExp1.2=1,0,-1,1,0,0,-1,0
diffExp1.2Score=4

cont.predictedValues:
Include	Exclude	Both
Lung	59.3725540686345	64.441752164881	77.5498438341284
cerebhem	59.3508797039573	67.4338430509366	63.423365650158
cortex	63.0133336955366	77.7922639931205	61.1106190144715
heart	67.7602447432596	71.773580949316	90.968035796881
kidney	62.0046356333866	58.4377347472819	81.4987587604404
liver	58.5158717480254	77.5360667143028	64.8253798378436
stomach	65.0356330103301	80.177970420397	70.579756761783
testicle	70.2884781092063	61.2740679738557	65.717873414277
cont.diffExp=-5.06919809624653,-8.08296334697926,-14.7789302975839,-4.01333620605641,3.56690088610475,-19.0201949662773,-15.1423374100669,9.01441013535064
cont.diffExpScore=1.44314230737887

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,-1,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,0,-1,0,0,-1,-1,0
cont.diffExp1.2Score=0.75

tran.correlation=0.632363067421367
cont.tran.correlation=-0.109827184275378

tran.covariance=0.0147491497458807
cont.tran.covariance=-0.000843903040483035

tran.mean=68.3409102085124
cont.tran.mean=66.5130569204018

weightedLogRatios:
wLogRatio
Lung	0.975291384704618
cerebhem	-0.73974667239586
cortex	-0.876194207696752
heart	0.983197977039298
kidney	0.670764510552008
liver	0.413045686214742
stomach	-1.61045136850268
testicle	0.0144658269200368

cont.weightedLogRatios:
wLogRatio
Lung	-0.337943297755896
cerebhem	-0.52952844976288
cortex	-0.89518134490626
heart	-0.244246053192178
kidney	0.242770984916953
liver	-1.18488999228115
stomach	-0.895776281839511
testicle	0.574256469010954

varWeightedLogRatios=0.920501564992036
cont.varWeightedLogRatios=0.359092455340244

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.59032821789605	0.0934990849978942	49.0948998912603	9.47284372852833e-251	***
df.mm.trans1	-0.0249956349432677	0.0807435227395888	-0.309568298424169	0.756964872431188	   
df.mm.trans2	-0.507307185638733	0.0713365373862134	-7.11146355327272	2.43015674338200e-12	***
df.mm.exp2	0.312139305235700	0.0917615962337245	3.40163334169401	0.00070099665029659	***
df.mm.exp3	0.385732780194223	0.0917615962337245	4.20364069530492	2.90373216891053e-05	***
df.mm.exp4	0.027160548812302	0.0917615962337245	0.295990369905094	0.767309478379204	   
df.mm.exp5	-0.0917320324057669	0.0917615962337245	-0.999677819162144	0.317749945374160	   
df.mm.exp6	-0.0905259854636477	0.0917615962337245	-0.98653455453271	0.324150611398435	   
df.mm.exp7	0.244543678674342	0.0917615962337245	2.66498937149555	0.00784455213444256	** 
df.mm.exp8	-0.0919748204867117	0.0917615962337245	-1.00232367637159	0.316471536229907	   
df.mm.trans1:exp2	-0.498797458179036	0.0848171515797065	-5.88085604018774	5.8559333449062e-09	***
df.mm.trans2:exp2	-0.0859515009968407	0.0626416178913968	-1.37211495951233	0.170388374047038	   
df.mm.trans1:exp3	-0.296877970373784	0.0848171515797065	-3.50021151199347	0.000488984294374799	***
df.mm.trans2:exp3	0.135247836756063	0.0626416178913968	2.15907317385297	0.0311226876541661	*  
df.mm.trans1:exp4	-0.0803936180288576	0.0848171515797064	-0.947846237836791	0.343476178846079	   
df.mm.trans2:exp4	-0.0855367802167906	0.0626416178913968	-1.36549442840202	0.172457673077319	   
df.mm.trans1:exp5	0.018394085335764	0.0848171515797065	0.216867520226475	0.828363447225917	   
df.mm.trans2:exp5	0.0903797267885974	0.0626416178913968	1.44280639343145	0.14944211382862	   
df.mm.trans1:exp6	-0.0230890733502055	0.0848171515797064	-0.272221749023340	0.785517397945416	   
df.mm.trans2:exp6	0.111405983936731	0.0626416178913968	1.77846594144292	0.075683470309154	.  
df.mm.trans1:exp7	-0.198801951083972	0.0848171515797064	-2.34388855769519	0.019312555379067	*  
df.mm.trans2:exp7	0.395251770110419	0.0626416178913968	6.30973118854746	4.48642127030287e-10	***
df.mm.trans1:exp8	-0.0693733534514528	0.0848171515797064	-0.81791656710211	0.41363323975091	   
df.mm.trans2:exp8	0.162353323782163	0.0626416178913968	2.59178050068308	0.0097113239736591	** 
df.mm.trans1:probe2	0.0279141089068309	0.0580703339794252	0.480694822880149	0.63085667317513	   
df.mm.trans1:probe3	-0.773074957640172	0.0580703339794252	-13.3127348279774	7.07377956577848e-37	***
df.mm.trans1:probe4	-0.523262234811879	0.0580703339794252	-9.01083563592514	1.31743813364923e-18	***
df.mm.trans1:probe5	0.145674715009405	0.0580703339794252	2.50859096248729	0.0123058847684911	*  
df.mm.trans1:probe6	-0.00220062507135955	0.0580703339794252	-0.037895856981626	0.969779583198097	   
df.mm.trans1:probe7	-0.75396815882549	0.0580703339794252	-12.9837062602848	2.63477749236651e-35	***
df.mm.trans1:probe8	-0.265757178737768	0.0580703339794252	-4.5764706438907	5.43086094862356e-06	***
df.mm.trans1:probe9	-0.141918340016314	0.0580703339794252	-2.44390431896941	0.014730905259951	*  
df.mm.trans1:probe10	-0.596845509931415	0.0580703339794252	-10.2779761890621	1.92991921174851e-23	***
df.mm.trans1:probe11	-0.538333311449624	0.0580703339794252	-9.27036706281661	1.48059909068482e-19	***
df.mm.trans1:probe12	-0.552549634067195	0.0580703339794252	-9.51517920084578	1.80050898635286e-20	***
df.mm.trans1:probe13	-0.544134963125561	0.0580703339794252	-9.37027438689009	6.29927383774725e-20	***
df.mm.trans1:probe14	-0.477922786789473	0.0580703339794252	-8.23006781670663	6.97196373687377e-16	***
df.mm.trans1:probe15	-0.601921416582364	0.0580703339794252	-10.3653858232610	8.59040725770714e-24	***
df.mm.trans1:probe16	-0.471678453117548	0.0580703339794252	-8.1225372887414	1.59431427497676e-15	***
df.mm.trans1:probe17	-0.600855388637771	0.0580703339794252	-10.3470282924610	1.01865641653127e-23	***
df.mm.trans1:probe18	-0.652883665855113	0.0580703339794252	-11.2429810733728	1.91416778250690e-27	***
df.mm.trans1:probe19	-0.62057953853677	0.0580703339794252	-10.6866879525206	4.1936293546867e-25	***
df.mm.trans1:probe20	-0.610956997452976	0.0580703339794252	-10.5209830146567	2.00767568542066e-24	***
df.mm.trans1:probe21	-0.652245953781972	0.0580703339794252	-11.2319993546631	2.13317732458015e-27	***
df.mm.trans1:probe22	-0.457246531286232	0.0580703339794252	-7.87401242514358	1.04177865025769e-14	***
df.mm.trans2:probe2	-0.179681839863828	0.0580703339794252	-3.09421054694624	0.00203773207041188	** 
df.mm.trans2:probe3	-0.239869554927595	0.0580703339794252	-4.13067290111648	3.97315993474864e-05	***
df.mm.trans2:probe4	-0.109333949527558	0.0580703339794252	-1.88278492709024	0.0600696225016917	.  
df.mm.trans2:probe5	-0.168813372315408	0.0580703339794252	-2.90705013639528	0.00374308130472438	** 
df.mm.trans2:probe6	-0.181766013631294	0.0580703339794252	-3.13010105462275	0.00180694709318235	** 
df.mm.trans3:probe2	-0.0474808994613864	0.0580703339794252	-0.817644676853577	0.413788432926509	   
df.mm.trans3:probe3	1.94962096090880	0.0580703339794252	33.5734415028432	3.66359482055526e-158	***
df.mm.trans3:probe4	0.232768685139643	0.0580703339794252	4.00839239571301	6.64813036631939e-05	***
df.mm.trans3:probe5	0.789424562090644	0.0580703339794252	13.5942831389663	3.05632694086626e-38	***
df.mm.trans3:probe6	0.239075249338702	0.0580703339794252	4.11699456427112	4.21146533483028e-05	***
df.mm.trans3:probe7	-0.0824642693985272	0.0580703339794252	-1.42007568662762	0.155951024362086	   
df.mm.trans3:probe8	1.28786079526977	0.0580703339794252	22.1776026934177	2.11247628909429e-86	***
df.mm.trans3:probe9	1.28397229931737	0.0580703339794252	22.110640861344	5.42661070718803e-86	***
df.mm.trans3:probe10	-0.0935864755616668	0.0580703339794252	-1.61160560217934	0.107417712358840	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.85673715815802	0.250715479921474	15.3829239397822	2.60396125184735e-47	***
df.mm.trans1	0.092405981177049	0.216511755753144	0.426794290479108	0.669636860387157	   
df.mm.trans2	0.303239658256317	0.191287157592221	1.58525884368438	0.113278165746214	   
df.mm.exp2	0.246108681065971	0.246056446847762	1.00021228550960	0.317491432289752	   
df.mm.exp3	0.486029753719575	0.246056446847762	1.97527746151795	0.0485586810090114	*  
df.mm.exp4	0.0803109878320584	0.246056446847762	0.326392536594449	0.744207446742789	   
df.mm.exp5	-0.104089755136738	0.246056446847762	-0.423032017531894	0.672378528401422	   
df.mm.exp6	0.349671104016842	0.246056446847762	1.42110116803071	0.155652811504649	   
df.mm.exp7	0.403767802409818	0.246056446847762	1.64095599844061	0.101175192497313	   
df.mm.exp8	0.283920734160860	0.246056446847762	1.15388455697129	0.248870694659315	   
df.mm.trans1:exp2	-0.246473804685282	0.227435090561126	-1.08371053946505	0.278799380139955	   
df.mm.trans2:exp2	-0.200723415331258	0.167971946389132	-1.19498177907787	0.232426287085633	   
df.mm.trans1:exp3	-0.426515470633749	0.227435090561126	-1.87532833909426	0.0610889782677439	.  
df.mm.trans2:exp3	-0.297749510594623	0.167971946389132	-1.77261451686011	0.0766494556443647	.  
df.mm.trans1:exp4	0.0518326075459721	0.227435090561126	0.227900661318757	0.819778084922365	   
df.mm.trans2:exp4	0.0274437185788036	0.167971946389132	0.163382750326809	0.87025578415305	   
df.mm.trans1:exp5	0.147466838794492	0.227435090561126	0.648390881242918	0.516906668292434	   
df.mm.trans2:exp5	0.00628983066363484	0.167971946389132	0.0374457211388355	0.970138379416998	   
df.mm.trans1:exp6	-0.364205141518158	0.227435090561126	-1.60135861453742	0.109667760285138	   
df.mm.trans2:exp6	-0.164689647532795	0.167971946389132	-0.98045924377912	0.327137472173132	   
df.mm.trans1:exp7	-0.312664549434829	0.227435090561126	-1.37474190400182	0.16957248654509	   
df.mm.trans2:exp7	-0.185280756886815	0.167971946389132	-1.10304584110483	0.270318353952937	   
df.mm.trans1:exp8	-0.115144911677781	0.227435090561126	-0.506275928633953	0.612793780481269	   
df.mm.trans2:exp8	-0.334325763987083	0.167971946389132	-1.99036667237616	0.0468693228147411	*  
df.mm.trans1:probe2	0.396270517520878	0.155714161835699	2.54485855910139	0.0111073240187996	*  
df.mm.trans1:probe3	0.116307813652832	0.155714161835699	0.746931507588585	0.45531073361435	   
df.mm.trans1:probe4	0.158712914008569	0.155714161835699	1.01925805679790	0.308369464217988	   
df.mm.trans1:probe5	0.205530937610918	0.155714161835699	1.31992450261385	0.187214331633002	   
df.mm.trans1:probe6	0.224815663483945	0.155714161835699	1.44377146454513	0.149170433509730	   
df.mm.trans1:probe7	0.106700693424019	0.155714161835699	0.685234356118513	0.493382212242799	   
df.mm.trans1:probe8	0.157760444747602	0.155714161835699	1.01314127686127	0.311279972940982	   
df.mm.trans1:probe9	0.116089528605580	0.155714161835699	0.745529675894676	0.456156958401852	   
df.mm.trans1:probe10	0.200788985953870	0.155714161835699	1.28947157783716	0.197583715864416	   
df.mm.trans1:probe11	0.241886679460134	0.155714161835699	1.55340192959045	0.120698065896411	   
df.mm.trans1:probe12	0.233270200550717	0.155714161835699	1.49806669991167	0.134485874125916	   
df.mm.trans1:probe13	0.0740109783436116	0.155714161835699	0.475300239047646	0.634694670314234	   
df.mm.trans1:probe14	0.196691270201033	0.155714161835699	1.26315595114959	0.206878292572337	   
df.mm.trans1:probe15	0.150302029405917	0.155714161835699	0.965243158579936	0.334696603771872	   
df.mm.trans1:probe16	0.165454427308758	0.155714161835699	1.06255221335190	0.28828578986743	   
df.mm.trans1:probe17	0.498287809806892	0.155714161835699	3.20001600324997	0.00142499391950212	** 
df.mm.trans1:probe18	0.125489754470685	0.155714161835699	0.805898146907762	0.420526183723724	   
df.mm.trans1:probe19	0.209352473102414	0.155714161835699	1.34446649318455	0.179154998479717	   
df.mm.trans1:probe20	0.273421041375149	0.155714161835699	1.75591634153127	0.079461564500644	.  
df.mm.trans1:probe21	0.237538140090209	0.155714161835699	1.52547550775019	0.127511207405884	   
df.mm.trans1:probe22	0.221363378082492	0.155714161835699	1.42160080671444	0.155507672350957	   
df.mm.trans2:probe2	-0.149109720063054	0.155714161835699	-0.957586120011273	0.338542821809753	   
df.mm.trans2:probe3	-0.0999817590590533	0.155714161835699	-0.64208520201617	0.520990378865297	   
df.mm.trans2:probe4	0.144047593534270	0.155714161835699	0.925077024697732	0.355187471323846	   
df.mm.trans2:probe5	-0.0618361123041885	0.155714161835699	-0.397112963748503	0.691383500635463	   
df.mm.trans2:probe6	0.259438912538346	0.155714161835699	1.66612278215318	0.0960561047302567	.  
df.mm.trans3:probe2	-0.0110477103577085	0.155714161835699	-0.0709486550707281	0.943455250016663	   
df.mm.trans3:probe3	0.214713236690531	0.155714161835699	1.37889344269845	0.168289072847314	   
df.mm.trans3:probe4	0.0543260641301384	0.155714161835699	0.348883258206535	0.727263052664383	   
df.mm.trans3:probe5	0.0415900431990303	0.155714161835699	0.267092233029606	0.789462707170374	   
df.mm.trans3:probe6	0.231913265913101	0.155714161835699	1.48935243383838	0.136764214153965	   
df.mm.trans3:probe7	0.0493560512779445	0.155714161835699	0.316965719084834	0.751347173828848	   
df.mm.trans3:probe8	0.248375859270962	0.155714161835699	1.59507559455661	0.111065747227056	   
df.mm.trans3:probe9	0.132736036904622	0.155714161835699	0.852433942679392	0.39421256045874	   
df.mm.trans3:probe10	0.023417935819627	0.155714161835699	0.150390533163813	0.880492063783664