chr11.4901_chr11_28388633_28437347_-_2.R 

fitVsDatCorrelation=0.75012904074989
cont.fitVsDatCorrelation=0.313741988679742

fstatistic=7788.83726904638,51,669
cont.fstatistic=3771.23660421963,51,669

residuals=-0.613668225916382,-0.0946932031610033,-0.0105225974312507,0.0770989516108974,0.888093906596685
cont.residuals=-0.640390878479565,-0.168977130425557,-0.0106000670533581,0.131548869236801,1.19701609980011

predictedValues:
Include	Exclude	Both
chr11.4901_chr11_28388633_28437347_-_2.R.tl.Lung	56.4960482396025	84.3262520106047	71.7175014808302
chr11.4901_chr11_28388633_28437347_-_2.R.tl.cerebhem	66.9533876007463	106.553411769860	73.8866371089057
chr11.4901_chr11_28388633_28437347_-_2.R.tl.cortex	63.0352290664617	71.1216534471627	74.5577306169274
chr11.4901_chr11_28388633_28437347_-_2.R.tl.heart	54.4399335362395	72.2233303797525	61.5340238167507
chr11.4901_chr11_28388633_28437347_-_2.R.tl.kidney	52.5552815815451	67.8658807955868	61.7665603167142
chr11.4901_chr11_28388633_28437347_-_2.R.tl.liver	55.1234621123529	66.5173699783987	57.0082015548308
chr11.4901_chr11_28388633_28437347_-_2.R.tl.stomach	55.1688746682549	80.032041217738	62.2930860708519
chr11.4901_chr11_28388633_28437347_-_2.R.tl.testicle	54.1574988298276	72.5242503194151	59.6256392017914


diffExp=-27.8302037710021,-39.600024169114,-8.086424380701,-17.7833968435129,-15.3105992140417,-11.3939078660459,-24.8631665494832,-18.3667514895875
diffExpScore=0.993911144390587
diffExp1.5=0,-1,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=-1,-1,0,0,0,0,-1,0
diffExp1.4Score=0.75
diffExp1.3=-1,-1,0,-1,0,0,-1,-1
diffExp1.3Score=0.833333333333333
diffExp1.2=-1,-1,0,-1,-1,-1,-1,-1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	68.5836680334282	63.2095810201924	54.168034956368
cerebhem	64.6621300987374	58.0787492767773	59.4836459817253
cortex	69.1949595215994	57.6415991466147	54.530672672756
heart	59.41426548756	53.5864693698488	58.1516509144281
kidney	65.1164399408524	60.0410982870798	66.6354527543814
liver	63.0084418881112	62.0977251981047	64.9160785038175
stomach	64.9120478290011	59.8740601825342	60.9214718244893
testicle	62.3770292450972	58.2184382801729	63.4498194683989
cont.diffExp=5.37408701323577,6.58338082196013,11.5533603749846,5.82779611771121,5.07534165377268,0.910716690006488,5.03798764646692,4.15859096492427
cont.diffExpScore=0.978032243136196

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

tran.correlation=0.723265857080841
cont.tran.correlation=0.543031158686963

tran.covariance=0.00905716708771178
cont.tran.covariance=0.00142329504170713

tran.mean=67.4433690970968
cont.tran.mean=61.876043925357

weightedLogRatios:
wLogRatio
Lung	-1.69598542416791
cerebhem	-2.06133550331818
cortex	-0.507419885852082
heart	-1.16979018223235
kidney	-1.04560455011118
liver	-0.77100072084859
stomach	-1.56118372361498
testicle	-1.20837091813863

cont.weightedLogRatios:
wLogRatio
Lung	0.341673920145839
cerebhem	0.441904117503279
cortex	0.757330234801474
heart	0.416349152890113
kidney	0.335594899992617
liver	0.0602173477130326
stomach	0.333875369013717
testicle	0.282789668354242

varWeightedLogRatios=0.254965674822955
cont.varWeightedLogRatios=0.0377419016542276

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.12481378225694	0.0901866695759199	45.7364020830666	4.23632804987819e-208	***
df.mm.trans1	-0.218256964181848	0.0798839323229977	-2.73217601881892	0.00645779436256217	** 
df.mm.trans2	0.285591750986078	0.0729484352423991	3.9149811786516	9.967566091395e-05	***
df.mm.exp2	0.37398195025461	0.0984435879799257	3.7989467666586	0.000158547094284589	***
df.mm.exp3	-0.0996172419733414	0.0984435879799257	-1.01192209688309	0.311941141357042	   
df.mm.exp4	-0.0388582788803546	0.0984435879799257	-0.394726357274569	0.693170657356259	   
df.mm.exp5	-0.140092218732957	0.0984435879799257	-1.42307103598788	0.155181709429692	   
df.mm.exp6	-0.0322857033117641	0.0984435879799257	-0.327961464776637	0.743043411444344	   
df.mm.exp7	0.0648464472905513	0.0984435879799257	0.65871682068084	0.510304268258743	   
df.mm.exp8	-0.00839734034277228	0.0984435879799257	-0.0853010390527886	0.932047586351645	   
df.mm.trans1:exp2	-0.204155973476312	0.0930204471299253	-2.19474298152060	0.0285249871849817	*  
df.mm.trans2:exp2	-0.140028800138090	0.0789304667454899	-1.77407794368696	0.0765050303491045	.  
df.mm.trans1:exp3	0.209140310562299	0.0930204471299253	2.24832622305271	0.0248801494612701	*  
df.mm.trans2:exp3	-0.070684146676797	0.0789304667454898	-0.895524245469332	0.370829005601688	   
df.mm.trans1:exp4	0.00178554275587449	0.0930204471299253	0.0191951641920249	0.98469113858109	   
df.mm.trans2:exp4	-0.116071820244426	0.0789304667454899	-1.47055788506482	0.141880878330503	   
df.mm.trans1:exp5	0.067787123794552	0.0930204471299253	0.72873358370199	0.466419662484672	   
df.mm.trans2:exp5	-0.0770675932388154	0.0789304667454898	-0.976398549464034	0.329219926421860	   
df.mm.trans1:exp6	0.0076904454566112	0.0930204471299253	0.0826747848875598	0.934134864698187	   
df.mm.trans2:exp6	-0.204944408731401	0.0789304667454899	-2.59651839374320	0.00962424262120102	** 
df.mm.trans1:exp7	-0.0886182107889084	0.0930204471299253	-0.952674530419445	0.341099071189106	   
df.mm.trans2:exp7	-0.117112605859936	0.0789304667454899	-1.48374399251387	0.138347808764937	   
df.mm.trans1:exp8	-0.0338769062971487	0.0930204471299253	-0.364187738743413	0.715832896285007	   
df.mm.trans2:exp8	-0.142374894840793	0.0789304667454899	-1.80380150670943	0.0717121474104869	.  
df.mm.trans1:probe2	-0.00523287636825363	0.0509493972022768	-0.102707326398354	0.91822603675587	   
df.mm.trans1:probe3	-0.0332069556007270	0.0509493972022768	-0.651763463832366	0.514777613944883	   
df.mm.trans1:probe4	0.0611594352892622	0.0509493972022768	1.20039566015767	0.230410591514181	   
df.mm.trans1:probe5	-0.00971423082854651	0.0509493972022768	-0.190664293631965	0.848846458368285	   
df.mm.trans1:probe6	-0.0542892421170602	0.0509493972022768	-1.06555219684982	0.287010524340599	   
df.mm.trans1:probe7	-0.0183803030737599	0.0509493972022768	-0.360756045862277	0.718395704322965	   
df.mm.trans1:probe8	0.190357985825156	0.0509493972022768	3.73621664392626	0.000202756052973947	***
df.mm.trans1:probe9	0.198739989870236	0.0509493972022768	3.90073289937481	0.000105589114504420	***
df.mm.trans1:probe10	0.322526905197688	0.0509493972022768	6.33033800021632	4.48389362063856e-10	***
df.mm.trans1:probe11	0.213432791340765	0.0509493972022768	4.1891131801502	3.17588159997339e-05	***
df.mm.trans1:probe12	0.116567976030195	0.0509493972022768	2.28791668657830	0.0224534969475505	*  
df.mm.trans1:probe13	0.125150092088531	0.0509493972022768	2.45636060406499	0.0142882395669773	*  
df.mm.trans1:probe14	0.227963870721668	0.0509493972022768	4.47431929011088	9.00748052631826e-06	***
df.mm.trans1:probe15	0.402147666671688	0.0509493972022768	7.89307997256771	1.20809001972630e-14	***
df.mm.trans1:probe16	0.263999468527888	0.0509493972022768	5.18160141286403	2.91590376801782e-07	***
df.mm.trans1:probe17	0.322349016298834	0.0509493972022768	6.32684651830247	4.58062660060515e-10	***
df.mm.trans1:probe18	0.202756147076544	0.0509493972022768	3.97955929236163	7.65891672426887e-05	***
df.mm.trans1:probe19	0.381866516984705	0.0509493972022768	7.4950154065344	2.10853414177250e-13	***
df.mm.trans1:probe20	0.154538745328358	0.0509493972022768	3.03318103479843	0.00251358112742590	** 
df.mm.trans2:probe2	-0.117589367558368	0.0509493972022768	-2.30796386248733	0.0213053332900556	*  
df.mm.trans2:probe3	0.105595717340593	0.0509493972022768	2.07256068057806	0.0385956017685624	*  
df.mm.trans2:probe4	0.094074735367356	0.0509493972022768	1.84643470841991	0.065270622108602	.  
df.mm.trans2:probe5	0.0373101294393434	0.0509493972022768	0.732297759897267	0.46424331335306	   
df.mm.trans2:probe6	0.123485735782699	0.0509493972022768	2.42369375426449	0.0156277243270223	*  
df.mm.trans3:probe2	0.113892376796663	0.0509493972022768	2.23540185067339	0.0257201528406698	*  
df.mm.trans3:probe3	0.0764265576723692	0.0509493972022768	1.50004831988383	0.134073645071565	   
df.mm.trans3:probe4	0.132026033275208	0.0509493972022768	2.59131688547844	0.00976944700531032	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.40963560194795	0.12949356159838	34.0529331923411	3.26395242157462e-148	***
df.mm.trans1	-0.166293795361605	0.114700486886046	-1.4498089753256	0.147580417760394	   
df.mm.trans2	-0.282877245196789	0.104742227836843	-2.70069914530964	0.00709449529880423	** 
df.mm.exp2	-0.23714521234644	0.141349169272881	-1.67772625453936	0.093867623728896	.  
df.mm.exp3	-0.09001015520242	0.141349169272881	-0.636792955101501	0.524477544267943	   
df.mm.exp4	-0.379642658483034	0.141349169272881	-2.68584994475714	0.0074140275317365	** 
df.mm.exp5	-0.310449755018333	0.141349169272881	-2.19633236343255	0.0284105764504506	*  
df.mm.exp6	-0.283536608771221	0.141349169272881	-2.00593049276322	0.0452657943998897	*  
df.mm.exp7	-0.226728430756746	0.141349169272881	-1.60403086854396	0.109179206798341	   
df.mm.exp8	-0.335269494507974	0.141349169272881	-2.37192405326926	0.0179777449687465	*  
df.mm.trans1:exp2	0.178266496095550	0.133562410686291	1.33470558954091	0.182426777369003	   
df.mm.trans2:exp2	0.152489160056662	0.113331463569479	1.34551478692567	0.178914898330384	   
df.mm.trans1:exp3	0.0988837448169337	0.133562410686291	0.740356095018306	0.459343697705005	   
df.mm.trans2:exp3	-0.00220121843920053	0.113331463569479	-0.0194228360763298	0.984509584469764	   
df.mm.trans1:exp4	0.236122584668179	0.133562410686291	1.76788202200677	0.0775363822733135	.  
df.mm.trans2:exp4	0.214483369478789	0.113331463569479	1.89253154175758	0.0588516441817328	.  
df.mm.trans1:exp5	0.258572374932293	0.133562410686291	1.93596666609757	0.0532927169285588	.  
df.mm.trans2:exp5	0.259023166122192	0.113331463569479	2.28553623119316	0.0225933505663071	*  
df.mm.trans1:exp6	0.198750893336826	0.133562410686291	1.48807506779470	0.137202289026333	   
df.mm.trans2:exp6	0.265790077685558	0.113331463569479	2.34524525947389	0.0193058287020878	*  
df.mm.trans1:exp7	0.171707242975949	0.133562410686291	1.28559556610020	0.199029073292541	   
df.mm.trans2:exp7	0.172515901955830	0.113331463569479	1.52222424843272	0.128425412634910	   
df.mm.trans1:exp8	0.240412149965046	0.133562410686291	1.79999858290759	0.0723112578052717	.  
df.mm.trans2:exp8	0.253015719925992	0.113331463569479	2.23252847847393	0.0259102096199784	*  
df.mm.trans1:probe2	-0.0296429426754904	0.0731551451676506	-0.405206532056731	0.68545524523876	   
df.mm.trans1:probe3	-0.0468658572837847	0.0731551451676506	-0.640636515399998	0.521978239016891	   
df.mm.trans1:probe4	-0.0648307894626141	0.0731551451676506	-0.886209566176658	0.375823050875141	   
df.mm.trans1:probe5	-0.0413120475640658	0.0731551451676506	-0.56471827742793	0.572454697100495	   
df.mm.trans1:probe6	-1.43591718156824e-05	0.0731551451676506	-0.000196283826418159	0.999843446624245	   
df.mm.trans1:probe7	0.0224356160436628	0.0731551451676506	0.3066854148433	0.7591782602851	   
df.mm.trans1:probe8	-0.126494695508776	0.0731551451676506	-1.72912917087221	0.0842472898072376	.  
df.mm.trans1:probe9	-0.0392524168954974	0.0731551451676506	-0.536563994310204	0.591747196908486	   
df.mm.trans1:probe10	0.0857012395574784	0.0731551451676506	1.17149982220766	0.241814987204315	   
df.mm.trans1:probe11	0.00850833736818808	0.0731551451676506	0.116305385611489	0.907445421036941	   
df.mm.trans1:probe12	-0.0538808950104663	0.0731551451676506	-0.736529124328668	0.461666938624037	   
df.mm.trans1:probe13	-0.0835138035409971	0.0731551451676506	-1.14159849385313	0.254029399441938	   
df.mm.trans1:probe14	0.0809909275298517	0.0731551451676506	1.10711184215743	0.268643484574865	   
df.mm.trans1:probe15	0.062287195630517	0.0731551451676506	0.851439710600978	0.394829803519303	   
df.mm.trans1:probe16	0.0464542150456309	0.0731551451676506	0.635009539509096	0.525639307672673	   
df.mm.trans1:probe17	-0.0557871772078053	0.0731551451676506	-0.762587198480122	0.445978411009511	   
df.mm.trans1:probe18	0.0331787503350756	0.0731551451676506	0.453539532442173	0.650307360467348	   
df.mm.trans1:probe19	-0.097304412075726	0.0731551451676506	-1.33011029986657	0.183935197125365	   
df.mm.trans1:probe20	-0.0675538974346758	0.0731551451676506	-0.923433304381553	0.356114370523802	   
df.mm.trans2:probe2	0.00743267561341662	0.0731551451676506	0.101601542808548	0.919103398051926	   
df.mm.trans2:probe3	0.102202302327777	0.0731551451676506	1.39706239518161	0.162858013450958	   
df.mm.trans2:probe4	0.0634666232216346	0.0731551451676506	0.867561988650112	0.385945240211421	   
df.mm.trans2:probe5	-0.0204356693743452	0.0731551451676506	-0.279346986838896	0.780064888064002	   
df.mm.trans2:probe6	0.044309381536903	0.0731551451676506	0.60569056947886	0.544925673143881	   
df.mm.trans3:probe2	0.00948096690680536	0.0731551451676506	0.129600821447045	0.8969212085734	   
df.mm.trans3:probe3	0.0269265051164302	0.0731551451676506	0.368073975586028	0.712934503588445	   
df.mm.trans3:probe4	0.0900981764808808	0.0731551451676506	1.23160409666882	0.218529751139496