chr2.14097_chr2_158901858_158916894_+_2.R 

fitVsDatCorrelation=0.820005623689725
cont.fitVsDatCorrelation=0.288613386644813

fstatistic=3976.94346610894,53,715
cont.fstatistic=1412.52240133163,53,715

residuals=-0.747502744479051,-0.138609128691278,0.00415139041103416,0.119285789021980,1.46418489529962
cont.residuals=-0.74402945166294,-0.250422312416728,-0.0940148462831173,0.127542949648149,2.19760471920308

predictedValues:
Include	Exclude	Both
chr2.14097_chr2_158901858_158916894_+_2.R.tl.Lung	59.1667814190373	59.704938501923	74.1291765555115
chr2.14097_chr2_158901858_158916894_+_2.R.tl.cerebhem	59.2483005733726	60.3008148452274	112.060038577024
chr2.14097_chr2_158901858_158916894_+_2.R.tl.cortex	73.6560457882068	67.1615281697538	99.921469779318
chr2.14097_chr2_158901858_158916894_+_2.R.tl.heart	65.947233447419	64.8097955147054	82.4417036936258
chr2.14097_chr2_158901858_158916894_+_2.R.tl.kidney	54.8592163770319	61.1301748193129	69.6103957563635
chr2.14097_chr2_158901858_158916894_+_2.R.tl.liver	54.9795047724166	56.0233238071782	68.1739683117863
chr2.14097_chr2_158901858_158916894_+_2.R.tl.stomach	78.5217765133407	123.044779293604	99.0834457208626
chr2.14097_chr2_158901858_158916894_+_2.R.tl.testicle	59.5619299818043	61.3256935316523	84.3780365781193


diffExp=-0.538157082885753,-1.05251427185484,6.49451761845305,1.13743793271367,-6.27095844228099,-1.04381903476153,-44.5230027802632,-1.76376354984803
diffExpScore=1.29373630241430
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=0,0,0,0,0,0,-1,0
diffExp1.3Score=0.5
diffExp1.2=0,0,0,0,0,0,-1,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	64.4352927653967	101.398800376566	79.1081832475269
cerebhem	67.0933358931246	69.497413217028	69.2646494580317
cortex	63.4327834809105	74.4095338671486	74.5734924588796
heart	67.4878863738144	59.252234644427	66.2676304155192
kidney	62.4719206358773	75.4397554792013	64.6729972059372
liver	66.3644056848009	67.0749283235149	87.0380359169987
stomach	66.1812488263758	58.6675309632367	72.8024408792362
testicle	65.1618475384489	60.2060421770062	70.5786087601612
cont.diffExp=-36.9635076111691,-2.40407732390344,-10.9767503862381,8.23565172938737,-12.9678348433240,-0.710522638713925,7.51371786313918,4.95580536144266
cont.diffExpScore=1.91183694098753

cont.diffExp1.5=-1,0,0,0,0,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=-1,0,0,0,0,0,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=-1,0,0,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=-1,0,0,0,-1,0,0,0
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.79455557883224
cont.tran.correlation=-0.498264452381526

tran.covariance=0.0269203513124814
cont.tran.covariance=-0.00263551203217984

tran.mean=66.2151148347491
cont.tran.mean=68.0359350154298

weightedLogRatios:
wLogRatio
Lung	-0.0369865290211737
cerebhem	-0.0720283773812534
cortex	0.392599284263576
heart	0.0727270693264433
kidney	-0.439315365736503
liver	-0.075538274587926
stomach	-2.06078576984305
testicle	-0.119694298427689

cont.weightedLogRatios:
wLogRatio
Lung	-1.99149556730870
cerebhem	-0.148694098525203
cortex	-0.675087065982553
heart	0.539693600331686
kidney	-0.79766705043763
liver	-0.0447329617561211
stomach	0.497967441454263
testicle	0.327268164398402

varWeightedLogRatios=0.563138586919697
cont.varWeightedLogRatios=0.724491376402154

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.84941892884013	0.126940621556953	30.3245634189135	1.66285851055320e-130	***
df.mm.trans1	0.00584871772785626	0.111679708285738	0.0523704602889186	0.958248138851261	   
df.mm.trans2	0.286081067128842	0.100977124358632	2.83312749244859	0.00473932464097772	** 
df.mm.exp2	-0.401917870444484	0.134550273511979	-2.98712042683957	0.00291251670074573	** 
df.mm.exp3	0.0381564402989737	0.134550273511979	0.283585007321272	0.776810521049184	   
df.mm.exp4	0.0842544664726317	0.134550273511979	0.626193201050093	0.531388076357367	   
df.mm.exp5	0.0108960865060362	0.134550273511979	0.080981526247631	0.935479306169422	   
df.mm.exp6	-0.0533000179939485	0.134550273511979	-0.396134594176081	0.69212392307406	   
df.mm.exp7	0.715996163191015	0.134550273511979	5.32140251002366	1.37933761215727e-07	***
df.mm.exp8	-0.0960574253189025	0.134550273511979	-0.713914753286254	0.47551287057972	   
df.mm.trans1:exp2	0.403294708020265	0.126581524312609	3.18604717560737	0.00150500556119787	** 
df.mm.trans2:exp2	0.41184874832163	0.104022342721129	3.95923354106476	8.27085843635777e-05	***
df.mm.trans1:exp3	0.180889527613594	0.126581524312609	1.42903578224310	0.153430676828607	   
df.mm.trans2:exp3	0.079529406864434	0.104022342721129	0.764541585817214	0.444796809662231	   
df.mm.trans1:exp4	0.0242402028455560	0.126581524312609	0.191498743416075	0.84818923250819	   
df.mm.trans2:exp4	-0.00221244814088369	0.104022342721129	-0.0212689705212175	0.983037030107434	   
df.mm.trans1:exp5	-0.0864861448704917	0.126581524312609	-0.683244615200739	0.494673617554506	   
df.mm.trans2:exp5	0.0126947783736950	0.104022342721129	0.122038958569968	0.902902455525784	   
df.mm.trans1:exp6	-0.0200997664449873	0.126581524312609	-0.158789100969809	0.873879875105432	   
df.mm.trans2:exp6	-0.0103466203773069	0.104022342721129	-0.099465365868993	0.920796665774647	   
df.mm.trans1:exp7	-0.432980428781993	0.126581524312609	-3.42056576687047	0.000660416650164827	***
df.mm.trans2:exp7	0.00713744627294649	0.104022342721129	0.0686145503575233	0.945315620313574	   
df.mm.trans1:exp8	0.102713776880231	0.126581524312609	0.811443671878732	0.417380965902309	   
df.mm.trans2:exp8	0.122841585564818	0.104022342721129	1.18091539136107	0.238029008679822	   
df.mm.trans1:probe2	0.089799845667508	0.0739076872707919	1.21502713700793	0.224756816609003	   
df.mm.trans1:probe3	0.0245829851663365	0.0739076872707919	0.332617432287745	0.739520578088981	   
df.mm.trans1:probe4	-0.033763599658914	0.0739076872707919	-0.456834747584603	0.647928581160643	   
df.mm.trans1:probe5	0.361832691276306	0.0739076872707919	4.89573824642327	1.21151305110805e-06	***
df.mm.trans1:probe6	-0.0435890391747266	0.0739076872707919	-0.589776798386613	0.555526621801365	   
df.mm.trans1:probe7	0.0756880497110263	0.0739076872707919	1.02408900218608	0.306139586938177	   
df.mm.trans1:probe8	0.198924297677734	0.0739076872707919	2.69152377815438	0.00727894133415213	** 
df.mm.trans1:probe9	0.178532202690102	0.0739076872707919	2.41561073391424	0.0159585679405565	*  
df.mm.trans1:probe10	0.584227619722074	0.0739076872707919	7.90482886552126	1.01663279024059e-14	***
df.mm.trans1:probe11	0.0551295731932124	0.0739076872707919	0.745924750577325	0.455958032507659	   
df.mm.trans1:probe12	0.143786699619373	0.0739076872707919	1.94549044800374	0.052107543332821	.  
df.mm.trans1:probe13	0.243378954575420	0.0739076872707919	3.29301272388215	0.00103997442474238	** 
df.mm.trans1:probe14	0.261157146708891	0.0739076872707919	3.53355863716898	0.000436374751141435	***
df.mm.trans1:probe15	0.328929549881345	0.0739076872707919	4.4505458366756	9.93261117872812e-06	***
df.mm.trans1:probe16	0.443009964920429	0.0739076872707919	5.99409860164175	3.24460332143921e-09	***
df.mm.trans1:probe17	0.676165711910125	0.0739076872707919	9.14878731670641	5.91040589504964e-19	***
df.mm.trans1:probe18	0.732019918854554	0.0739076872707919	9.90451664618447	9.28142161730176e-22	***
df.mm.trans1:probe19	0.685146519792126	0.0739076872707919	9.2703011701855	2.14856888206835e-19	***
df.mm.trans1:probe20	0.593350749877395	0.0739076872707919	8.02826839518608	4.06368971901651e-15	***
df.mm.trans1:probe21	0.254098099598389	0.0739076872707919	3.43804696076328	0.000619868981604388	***
df.mm.trans2:probe2	-0.130356753250280	0.0739076872707919	-1.76377800556339	0.0781963878288718	.  
df.mm.trans2:probe3	-0.0236854466743971	0.0739076872707919	-0.320473384420968	0.748703138950673	   
df.mm.trans2:probe4	-0.0258463329731324	0.0739076872707919	-0.349711023677869	0.726658559322728	   
df.mm.trans2:probe5	-0.108487863563836	0.0739076872707919	-1.46788334975691	0.142575663190579	   
df.mm.trans2:probe6	-0.218561430719057	0.0739076872707919	-2.95722189111757	0.00320656148317140	** 
df.mm.trans3:probe2	0.0483416200207313	0.0739076872707919	0.654081081493073	0.513269883928524	   
df.mm.trans3:probe3	-0.372539656325563	0.0739076872707919	-5.04060768348233	5.88577259547802e-07	***
df.mm.trans3:probe4	1.26744354376985	0.0739076872707919	17.1490083179851	1.78075086265898e-55	***
df.mm.trans3:probe5	-0.120943073484337	0.0739076872707919	-1.63640722569509	0.102194447727534	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.13921522214309	0.212348379418277	19.4925679841888	3.41065350331515e-68	***
df.mm.trans1	-0.0640969839157973	0.186819670311307	-0.343095477092906	0.731627483413383	   
df.mm.trans2	0.451522044677051	0.168916210216074	2.67305336829114	0.00768785638419348	** 
df.mm.exp2	-0.204466856148707	0.225077931556651	-0.908426937881484	0.363958785080675	   
df.mm.exp3	-0.266126664597432	0.225077931556651	-1.18237564543483	0.237449728064467	   
df.mm.exp4	-0.313856377385023	0.225077931556651	-1.39443425312458	0.163619619467995	   
df.mm.exp5	-0.125198621427674	0.225077931556651	-0.556245654835164	0.578216964879456	   
df.mm.exp6	-0.479280479973777	0.225077931556651	-2.12939792301736	0.0335623714204804	*  
df.mm.exp7	-0.437372316058124	0.225077931556651	-1.94320390734548	0.0523836410641963	.  
df.mm.exp8	-0.395986697558114	0.225077931556651	-1.7593315116211	0.0789488766489822	.  
df.mm.trans1:exp2	0.244890071838134	0.211747675585613	1.15651834741922	0.247855459385960	   
df.mm.trans2:exp2	-0.173304872353342	0.174010302054603	-0.99594604633788	0.319613289069998	   
df.mm.trans1:exp3	0.250445974692889	0.211747675585613	1.18275666545217	0.237298742310840	   
df.mm.trans2:exp3	-0.0433505188787696	0.174010302054603	-0.249126163031236	0.803334738487093	   
df.mm.trans1:exp4	0.360142990722527	0.211747675585613	1.70081201470811	0.0894131131957713	.  
df.mm.trans2:exp4	-0.223401388274433	0.174010302054603	-1.28384001198005	0.199613822581248	   
df.mm.trans1:exp5	0.0942543000849105	0.211747675585613	0.445125547773968	0.656363752216554	   
df.mm.trans2:exp5	-0.170528241995530	0.174010302054603	-0.979989345355082	0.327422846273687	   
df.mm.trans1:exp6	0.508779826454121	0.211747675585613	2.40276463506402	0.0165255160781271	*  
df.mm.trans2:exp6	0.0660295472015641	0.174010302054603	0.379457689699571	0.704460687382048	   
df.mm.trans1:exp7	0.464107981214038	0.211747675585613	2.19179728859121	0.0287159240722321	*  
df.mm.trans2:exp7	-0.109802505833696	0.174010302054603	-0.631011523669678	0.528234641977586	   
df.mm.trans1:exp8	0.407199327457058	0.211747675585613	1.9230403655242	0.0548718423126331	.  
df.mm.trans2:exp8	-0.125301847256113	0.174010302054603	-0.72008292484197	0.471709262913792	   
df.mm.trans1:probe2	0.0495316152143469	0.123634006404043	0.400630996721686	0.688811502087255	   
df.mm.trans1:probe3	0.0537016727657224	0.123634006404043	0.434360046460214	0.664158053017993	   
df.mm.trans1:probe4	0.0430054059301532	0.123634006404043	0.347844474032567	0.728059365120865	   
df.mm.trans1:probe5	0.116044429605365	0.123634006404043	0.938612546665562	0.348246663326855	   
df.mm.trans1:probe6	0.0396044372959395	0.123634006404043	0.320336115020895	0.748807140595365	   
df.mm.trans1:probe7	0.208237954419059	0.123634006404043	1.68430968530233	0.0925582679698396	.  
df.mm.trans1:probe8	0.0961742148433776	0.123634006404043	0.777894510100038	0.43688852708467	   
df.mm.trans1:probe9	0.0256749948889589	0.123634006404043	0.207669359229949	0.835546278265653	   
df.mm.trans1:probe10	0.0211242657378851	0.123634006404043	0.170861289319136	0.864381174663473	   
df.mm.trans1:probe11	0.138855607426223	0.123634006404043	1.12311823797439	0.261764250631265	   
df.mm.trans1:probe12	0.0892002703210568	0.123634006404042	0.721486530409324	0.470846081908108	   
df.mm.trans1:probe13	0.0425530992936748	0.123634006404043	0.344186041780519	0.730807579074776	   
df.mm.trans1:probe14	0.086714367424466	0.123634006404043	0.701379579507266	0.48329437471815	   
df.mm.trans1:probe15	0.259350594736334	0.123634006404043	2.09772862887548	0.0362795928958311	*  
df.mm.trans1:probe16	0.246440615086947	0.123634006404043	1.99330768495495	0.0466073271564452	*  
df.mm.trans1:probe17	0.181282069672039	0.123634006404043	1.46627998998593	0.143011673123691	   
df.mm.trans1:probe18	0.159261217640505	0.123634006404043	1.28816676149789	0.198104632103153	   
df.mm.trans1:probe19	0.283649170438110	0.123634006404043	2.29426497359577	0.0220642975641063	*  
df.mm.trans1:probe20	0.11535233271729	0.123634006404043	0.933014597458829	0.351127387002396	   
df.mm.trans1:probe21	0.0983666606209273	0.123634006404043	0.795627865519943	0.426512417420317	   
df.mm.trans2:probe2	0.130223686571018	0.123634006404043	1.05329989991136	0.292559380049806	   
df.mm.trans2:probe3	-0.0150659961766270	0.123634006404043	-0.121859645374514	0.903044415739065	   
df.mm.trans2:probe4	0.136106253704215	0.123634006404043	1.10088039418065	0.271319190170093	   
df.mm.trans2:probe5	0.165269084812802	0.123634006404043	1.33676073128856	0.181725929113226	   
df.mm.trans2:probe6	-0.104969098639282	0.123634006404043	-0.84903095590252	0.396148235828872	   
df.mm.trans3:probe2	-0.201988024992722	0.123634006404043	-1.63375782171626	0.102749925661573	   
df.mm.trans3:probe3	-0.180254232077119	0.123634006404043	-1.45796643916916	0.145288878546781	   
df.mm.trans3:probe4	-0.189199124483988	0.123634006404043	-1.53031621304640	0.126380763680268	   
df.mm.trans3:probe5	-0.207678413571428	0.123634006404043	-1.6797839009821	0.0934362120803247	.