chr19.12215_chr19_23361611_23373288_+_2.R 

fitVsDatCorrelation=0.92145756282924
cont.fitVsDatCorrelation=0.298371462628939

fstatistic=9740.51447462476,54,738
cont.fstatistic=1602.25305230943,54,738

residuals=-0.813081784128564,-0.0983167767804217,0.00474354931979067,0.0889371777524171,0.808240203683625
cont.residuals=-0.87606987095898,-0.308097867356556,-0.0369708444789107,0.256930319734464,1.22730646786425

predictedValues:
Include	Exclude	Both
chr19.12215_chr19_23361611_23373288_+_2.R.tl.Lung	68.4420151383852	83.7167622763605	76.4350709790568
chr19.12215_chr19_23361611_23373288_+_2.R.tl.cerebhem	70.4396085778335	81.9871816321349	76.0209090625863
chr19.12215_chr19_23361611_23373288_+_2.R.tl.cortex	71.2822087517836	84.31793153203	83.8588210982723
chr19.12215_chr19_23361611_23373288_+_2.R.tl.heart	66.1265698466216	85.113174284337	86.5212069560132
chr19.12215_chr19_23361611_23373288_+_2.R.tl.kidney	62.9453604050639	85.8396327494	71.4084892282085
chr19.12215_chr19_23361611_23373288_+_2.R.tl.liver	70.3823199953096	85.9234108676853	70.9502609377827
chr19.12215_chr19_23361611_23373288_+_2.R.tl.stomach	71.3777533071188	134.545822879371	88.6046398901456
chr19.12215_chr19_23361611_23373288_+_2.R.tl.testicle	68.4030446042574	84.6346705939696	80.9804214177629


diffExp=-15.2747471379753,-11.5475730543014,-13.0357227802465,-18.9866044377153,-22.8942723443361,-15.5410908723757,-63.1680695722522,-16.2316259897122
diffExpScore=0.994371895240885
diffExp1.5=0,0,0,0,0,0,-1,0
diffExp1.5Score=0.5
diffExp1.4=0,0,0,0,0,0,-1,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,-1,0,-1,0
diffExp1.3Score=0.666666666666667
diffExp1.2=-1,0,0,-1,-1,-1,-1,-1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	81.1362422260151	72.9352836562036	61.2004311577153
cerebhem	76.8982189797498	61.7074989043556	80.6216927838715
cortex	84.0945444672108	82.657823110006	75.1939315531689
heart	79.946298171495	83.1540507746275	68.6242907478321
kidney	83.6155565044388	77.300844876654	77.1956206528582
liver	83.0324681798304	77.9502746690309	71.4278056360051
stomach	78.351075635883	69.6812328678066	54.4012867456061
testicle	80.866228116571	76.6291131554424	81.6931867533087
cont.diffExp=8.20095856981153,15.1907200753942,1.43672135720483,-3.20775260313248,6.3147116277848,5.08219351079953,8.66984276807636,4.23711496112854
cont.diffExpScore=1.11540888067756

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=0,1,0,0,0,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=0.341479717956839
cont.tran.correlation=0.75391340275958

tran.covariance=0.00232558319855683
cont.tran.covariance=0.00238687682612531

tran.mean=79.7173417151039
cont.tran.mean=78.1222971434575

weightedLogRatios:
wLogRatio
Lung	-0.871626431672868
cerebhem	-0.657425207901398
cortex	-0.730677097665681
heart	-1.08985509104988
kidney	-1.33310454910395
liver	-0.868624958753838
stomach	-2.9064822059715
testicle	-0.922372904500311

cont.weightedLogRatios:
wLogRatio
Lung	0.462762151422122
cerebhem	0.931464674256435
cortex	0.0762237285141427
heart	-0.173135376255462
kidney	0.344485286043173
liver	0.277126674304702
stomach	0.504556124586887
testicle	0.234968584455226

varWeightedLogRatios=0.535036616634738
cont.varWeightedLogRatios=0.105628115693852

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.00879907828552	0.0835137236567189	48.001680475458	3.51934730535825e-229	***
df.mm.trans1	0.0508254436975732	0.0735681544803899	0.690862018444694	0.489869490950489	   
df.mm.trans2	0.383028798566337	0.0663827923440676	5.77000130667999	1.16654604260086e-08	***
df.mm.exp2	0.0133257376116684	0.0884021201616042	0.150740022833255	0.880221991176144	   
df.mm.exp3	-0.0448778416607142	0.0884021201616041	-0.507655716612621	0.611846486873296	   
df.mm.exp4	-0.141821568450414	0.0884021201616042	-1.60427790861979	0.109080639538374	   
df.mm.exp5	0.00934663490495793	0.0884021201616042	0.105728628316513	0.915826395996065	   
df.mm.exp6	0.128434861000564	0.0884021201616041	1.45284819827599	0.146690950159571	   
df.mm.exp7	0.368722367856017	0.0884021201616041	4.17096747433174	3.39377963400914e-05	***
df.mm.exp8	-0.0474305595895497	0.0884021201616042	-0.536531923700969	0.591752670061352	   
df.mm.trans1:exp2	0.0154430967248263	0.0833846119222224	0.185203197194596	0.85312054709933	   
df.mm.trans2:exp2	-0.034202047716364	0.0682237733909092	-0.501321548434338	0.61629434336696	   
df.mm.trans1:exp3	0.0855377188616686	0.0833846119222224	1.02582139425743	0.305311890609911	   
df.mm.trans2:exp3	0.0520331713961163	0.0682237733909092	0.762683868245987	0.445895654800714	   
df.mm.trans1:exp4	0.107405306479308	0.0833846119222224	1.28807107214808	0.198124936553486	   
df.mm.trans2:exp4	0.158364177909535	0.0682237733909092	2.32124624655599	0.0205450734521959	*  
df.mm.trans1:exp5	-0.0930664724485865	0.0833846119222224	-1.11611087829245	0.2647379435719	   
df.mm.trans2:exp5	0.0156949615027324	0.0682237733909092	0.230051208290741	0.818115727605299	   
df.mm.trans1:exp6	-0.100479658266260	0.0833846119222224	-1.20501440193765	0.228584000471862	   
df.mm.trans2:exp6	-0.102417756437396	0.0682237733909093	-1.50120333934862	0.133730683728571	   
df.mm.trans1:exp7	-0.326723017852159	0.0833846119222224	-3.91826513694052	9.74738877846547e-05	***
df.mm.trans2:exp7	0.105743240126842	0.0682237733909092	1.54994710598831	0.121582915873700	   
df.mm.trans1:exp8	0.0468610025261876	0.0833846119222224	0.561986215992677	0.574296046568677	   
df.mm.trans2:exp8	0.0583353365548021	0.0682237733909092	0.855058781644219	0.392796102041964	   
df.mm.trans1:probe2	-0.130033586304770	0.0486861242555764	-2.67085516239007	0.00773248404828808	** 
df.mm.trans1:probe3	0.0276480944498899	0.0486861242555764	0.567884481926555	0.570286133165895	   
df.mm.trans1:probe4	-0.0423862419905442	0.0486861242555764	-0.870602099440878	0.384254543634057	   
df.mm.trans1:probe5	0.201976970374498	0.0486861242555764	4.14855307262139	3.73526512250864e-05	***
df.mm.trans1:probe6	-0.0399176660030423	0.0486861242555764	-0.819898207413178	0.412538854972899	   
df.mm.trans1:probe7	0.780008984888679	0.0486861242555764	16.0211763991326	8.47570171835207e-50	***
df.mm.trans1:probe8	0.110848555475369	0.0486861242555764	2.27679974880467	0.0230836473777086	*  
df.mm.trans1:probe9	-0.119308854246508	0.0486861242555764	-2.45057202787800	0.0144940169639291	*  
df.mm.trans1:probe10	0.0193965671221548	0.0486861242555764	0.398400312588717	0.690450359464838	   
df.mm.trans1:probe11	-0.221402218529498	0.0486861242555764	-4.54754248597102	6.34263997851832e-06	***
df.mm.trans1:probe12	-0.266541609622947	0.0486861242555764	-5.47469353328979	6.01117416556311e-08	***
df.mm.trans1:probe13	-0.22432826751629	0.0486861242555763	-4.6076427513245	4.7972172181141e-06	***
df.mm.trans1:probe14	-0.224291042520253	0.0486861242555764	-4.60687815983963	4.81438671892577e-06	***
df.mm.trans1:probe15	-0.0612823981574721	0.0486861242555764	-1.25872410454716	0.208528025890324	   
df.mm.trans1:probe16	-0.109470224879791	0.0486861242555764	-2.24848920618799	0.0248393019116979	*  
df.mm.trans1:probe17	0.620507946287692	0.0486861242555763	12.7450676301600	9.04867532907747e-34	***
df.mm.trans1:probe18	0.780740477006376	0.0486861242555764	16.0362010520267	7.08428113126899e-50	***
df.mm.trans1:probe19	0.792349442065988	0.0486861242555764	16.2746460964232	4.07118972614452e-51	***
df.mm.trans1:probe20	0.63008284599292	0.0486861242555764	12.9417335149809	1.13413319972225e-34	***
df.mm.trans1:probe21	0.838273100154378	0.0486861242555764	17.2179057785312	4.18513365035719e-56	***
df.mm.trans1:probe22	1.12891312881331	0.0486861242555763	23.187574408	8.9274612722276e-90	***
df.mm.trans2:probe2	0.0391934976296089	0.0486861242555764	0.805023982271906	0.421065113319416	   
df.mm.trans2:probe3	-0.057955784361308	0.0486861242555764	-1.19039634490252	0.234273415837075	   
df.mm.trans2:probe4	0.184445062237889	0.0486861242555764	3.78845235799938	0.000163935821865441	***
df.mm.trans2:probe5	0.113559521561152	0.0486861242555763	2.33248226876769	0.0199433176602818	*  
df.mm.trans2:probe6	0.112482517053624	0.0486861242555764	2.31036088358873	0.0211431197542361	*  
df.mm.trans3:probe2	-0.485281370528528	0.0486861242555764	-9.96754985015973	4.85386889213437e-22	***
df.mm.trans3:probe3	-0.320297879303492	0.0486861242555764	-6.57883296731729	8.98337531070431e-11	***
df.mm.trans3:probe4	0.223026110038651	0.0486861242555764	4.58089678422299	5.43415984619192e-06	***
df.mm.trans3:probe5	0.0514947124081865	0.0486861242555764	1.05768765116456	0.290543946304919	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.81235231807657	0.205183940499477	23.453844907949	2.48471149120116e-91	***
df.mm.trans1	-0.226476835257789	0.180748782003881	-1.25299231755224	0.210605353267022	   
df.mm.trans2	-0.513009139805257	0.163095145541609	-3.14545928452773	0.00172480695234368	** 
df.mm.exp2	-0.496427609444382	0.217194187602326	-2.28563947739394	0.0225580523237466	*  
df.mm.exp3	-0.0449673943415558	0.217194187602326	-0.207037742758979	0.836037493239521	   
df.mm.exp4	0.00185546012621580	0.217194187602326	0.00854286271054855	0.993186173354624	   
df.mm.exp5	-0.143956290005822	0.217194187602326	-0.662799919256589	0.507665651681446	   
df.mm.exp6	-0.0649324274863489	0.217194187602326	-0.298960244761419	0.765054543559117	   
df.mm.exp7	0.0371948833621399	0.217194187602326	0.171251743763246	0.8640727654999	   
df.mm.exp8	-0.242745280993098	0.217194187602326	-1.11764169968284	0.264083748602220	   
df.mm.trans1:exp2	0.442780580996201	0.204866727312365	2.16131036408407	0.030992305640326	*  
df.mm.trans2:exp2	0.329260548433687	0.16761823143739	1.96434806411064	0.0498646201705243	*  
df.mm.trans1:exp3	0.0807793451428617	0.204866727312365	0.394301925952550	0.693472053248358	   
df.mm.trans2:exp3	0.170104344912839	0.16761823143739	1.01483199920516	0.31051850347336	   
df.mm.trans1:exp4	-0.0166300681934089	0.204866727312366	-0.0811750566408602	0.935324744624501	   
df.mm.trans2:exp4	0.129266938102892	0.16761823143739	0.771198556352606	0.440836088757768	   
df.mm.trans1:exp5	0.174056130893980	0.204866727312365	0.849606635383951	0.395819345027919	   
df.mm.trans2:exp5	0.202088652684765	0.16761823143739	1.20564840084386	0.228339495418784	   
df.mm.trans1:exp6	0.0880343972001308	0.204866727312365	0.429715446500508	0.667528079275235	   
df.mm.trans2:exp6	0.131431023945526	0.16761823143739	0.784109358620806	0.433227536306246	   
df.mm.trans1:exp7	-0.0721249305336764	0.204866727312365	-0.352057805969174	0.724895415957998	   
df.mm.trans2:exp7	-0.0828363803885982	0.16761823143739	-0.494196721193422	0.621314316897353	   
df.mm.trans1:exp8	0.239411821214303	0.204866727312365	1.16862227632145	0.242933197261509	   
df.mm.trans2:exp8	0.292149830140799	0.16761823143739	1.74294781442033	0.081759219469538	.  
df.mm.trans1:probe2	-0.38334023766108	0.119616398179877	-3.20474653554288	0.00140998296836589	** 
df.mm.trans1:probe3	-0.178542456076321	0.119616398179877	-1.49262524865388	0.135962666815979	   
df.mm.trans1:probe4	-0.370184636922009	0.119616398179877	-3.09476495325776	0.00204408957082267	** 
df.mm.trans1:probe5	-0.33173497510891	0.119616398179877	-2.77332355894926	0.00568875201216948	** 
df.mm.trans1:probe6	-0.103337735716672	0.119616398179877	-0.863909441256329	0.387918327551689	   
df.mm.trans1:probe7	-0.169662961557561	0.119616398179877	-1.41839216143613	0.156498435060722	   
df.mm.trans1:probe8	-0.300959590355249	0.119616398179877	-2.51603956426335	0.0120792993986300	*  
df.mm.trans1:probe9	-0.250530430954353	0.119616398179877	-2.09444887796746	0.0365604821402826	*  
df.mm.trans1:probe10	-0.138306573187995	0.119616398179877	-1.15625094295192	0.247952684645355	   
df.mm.trans1:probe11	-0.101105684910454	0.119616398179877	-0.845249367552536	0.398245568845215	   
df.mm.trans1:probe12	-0.170136865177713	0.119616398179877	-1.42235402308188	0.155346012827881	   
df.mm.trans1:probe13	-0.308872366821464	0.119616398179877	-2.58219083270662	0.0100090981569231	*  
df.mm.trans1:probe14	-0.465606353796771	0.119616398179877	-3.89249601962265	0.000108200074642727	***
df.mm.trans1:probe15	-0.29870629720463	0.119616398179877	-2.49720190333302	0.0127345682994840	*  
df.mm.trans1:probe16	-0.193742300835619	0.119616398179877	-1.61969682906078	0.105724625419540	   
df.mm.trans1:probe17	-0.325115792020001	0.119616398179877	-2.71798680588173	0.0067221546078269	** 
df.mm.trans1:probe18	-0.240557175919148	0.119616398179877	-2.01107188963675	0.0446810447036289	*  
df.mm.trans1:probe19	-0.216683237250225	0.119616398179877	-1.81148438297214	0.0704723027256873	.  
df.mm.trans1:probe20	-0.160520378836365	0.119616398179877	-1.34195964164526	0.180021798947457	   
df.mm.trans1:probe21	-0.168654341394524	0.119616398179877	-1.40996003859692	0.158972775118865	   
df.mm.trans1:probe22	-0.24683454343299	0.119616398179877	-2.06355104474726	0.0394094332184248	*  
df.mm.trans2:probe2	0.0718342178294564	0.119616398179877	0.600538211503687	0.548331975110348	   
df.mm.trans2:probe3	0.00598269448028352	0.119616398179877	0.0500156715242908	0.960123432998742	   
df.mm.trans2:probe4	-0.043407913739742	0.119616398179877	-0.362892666893931	0.716788973481441	   
df.mm.trans2:probe5	-0.156043413639351	0.119616398179877	-1.30453195392738	0.192458936137198	   
df.mm.trans2:probe6	0.0141572037297940	0.119616398179877	0.118355041158358	0.905818553196641	   
df.mm.trans3:probe2	-0.0564132134796687	0.119616398179877	-0.471617724142098	0.637339068525307	   
df.mm.trans3:probe3	0.0210508081571396	0.119616398179877	0.175985972470796	0.860353240616183	   
df.mm.trans3:probe4	0.216182071485179	0.119616398179877	1.80729460821992	0.0711234498610091	.  
df.mm.trans3:probe5	0.0256197915405839	0.119616398179877	0.214182937543874	0.830463564250093