chr5.17888_chr5_110040331_110041353_-_1.R 

fitVsDatCorrelation=0.940785468726644
cont.fitVsDatCorrelation=0.367831286344808

fstatistic=11938.7216216845,37,347
cont.fstatistic=1578.58010879814,37,347

residuals=-0.398105076302837,-0.0745940008323934,0.000726129289334002,0.073570447149954,0.411546521616178
cont.residuals=-0.759095893248455,-0.274150023617661,-0.0195111243567864,0.256647533982547,0.908569262466356

predictedValues:
Include	Exclude	Both
chr5.17888_chr5_110040331_110041353_-_1.R.tl.Lung	106.860318859511	45.6690872419320	65.9068660629084
chr5.17888_chr5_110040331_110041353_-_1.R.tl.cerebhem	93.4148088071251	48.3837100867656	70.5917465903503
chr5.17888_chr5_110040331_110041353_-_1.R.tl.cortex	90.2455002834648	50.8949977193082	71.4339379533907
chr5.17888_chr5_110040331_110041353_-_1.R.tl.heart	96.4732315484212	45.5163157275675	68.3089995631835
chr5.17888_chr5_110040331_110041353_-_1.R.tl.kidney	111.140221501057	45.3482036654534	68.0307360091065
chr5.17888_chr5_110040331_110041353_-_1.R.tl.liver	107.970188530377	47.8343306121241	67.9449180413224
chr5.17888_chr5_110040331_110041353_-_1.R.tl.stomach	92.7348338628325	45.0687793502135	69.2672800582104
chr5.17888_chr5_110040331_110041353_-_1.R.tl.testicle	103.473389482092	43.6689784352468	69.3317020098538


diffExp=61.191231617579,45.0310987203595,39.3505025641567,50.9569158208537,65.7920178356033,60.1358579182533,47.666054512619,59.8044110468451
diffExpScore=0.997679427210429
diffExp1.5=1,1,1,1,1,1,1,1
diffExp1.5Score=0.888888888888889
diffExp1.4=1,1,1,1,1,1,1,1
diffExp1.4Score=0.888888888888889
diffExp1.3=1,1,1,1,1,1,1,1
diffExp1.3Score=0.888888888888889
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	72.2390857419653	64.7750462140779	71.1913393394637
cerebhem	74.9271053803153	62.3387195735823	60.5619139653531
cortex	85.1823443649838	71.6170989791348	57.2882837358292
heart	68.4277998202787	64.483835599534	61.0386046471361
kidney	67.693443020788	78.8703282473483	59.9129454401176
liver	83.9516992861543	59.299858384177	65.2982887311053
stomach	72.712523285896	57.9317986577977	56.6468899022826
testicle	70.359858882959	78.3280119274453	68.5579926596242
cont.diffExp=7.46403952788745,12.5883858067329,13.5652453858491,3.94396422074463,-11.1768852265604,24.6518409019772,14.7807246280982,-7.96815304448631
cont.diffExpScore=1.63365518127868

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,0,0,1,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,0,0,0,0,1,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,1,0,0,0,1,1,0
cont.diffExp1.2Score=0.75

tran.correlation=-0.455135925193622
cont.tran.correlation=-0.305882282608808

tran.covariance=-0.00180993367952090
cont.tran.covariance=-0.00327234906134431

tran.mean=73.4185559820933
cont.tran.mean=70.8211598354024

weightedLogRatios:
wLogRatio
Lung	3.60992979020923
cerebhem	2.76845730846693
cortex	2.41487995806035
heart	3.15026145030711
kidney	3.82107234195594
liver	3.48016359538999
stomach	3.00813653393720
testicle	3.63012219576844

cont.weightedLogRatios:
wLogRatio
Lung	0.460831105812121
cerebhem	0.77703391908458
cortex	0.755951217302611
heart	0.249099573403644
kidney	-0.655793157659058
liver	1.47968080484038
stomach	0.948277559042854
testicle	-0.462093527395452

varWeightedLogRatios=0.235597907641410
cont.varWeightedLogRatios=0.514853649977886

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.20982611725803	0.0677348922990518	62.1515141512517	3.86935415186434e-190	***
df.mm.trans1	0.521714039864911	0.0564324606682323	9.24492807308331	2.44146167525773e-18	***
df.mm.trans2	-0.413523394097096	0.0564324606682323	-7.32775762744441	1.65558487747926e-12	***
df.mm.exp2	-0.145401726303268	0.0777520759014404	-1.87006873601139	0.0623160595169207	.  
df.mm.exp3	-0.141176264462669	0.0777520759014404	-1.81572341093023	0.0702757697502736	.  
df.mm.exp4	-0.141406663692448	0.0777520759014404	-1.81868666595728	0.0698211384529285	.  
df.mm.exp5	0.000502056686727278	0.0777520759014404	0.00645714832570762	0.994851687438739	   
df.mm.exp6	0.0261998378427702	0.0777520759014404	0.336966409436856	0.736345934592046	   
df.mm.exp7	-0.204740287015983	0.0777520759014404	-2.63324528177891	0.00883569053770745	** 
df.mm.exp8	-0.127651380738997	0.0777520759014404	-1.64177456690429	0.101542676864526	   
df.mm.trans1:exp2	0.0109290610839812	0.065712497762077	0.166316324233355	0.868004885495101	   
df.mm.trans2:exp2	0.203143273865658	0.0657124977620769	3.09139479983202	0.00215341452418788	** 
df.mm.trans1:exp3	-0.0278125483470414	0.0657124977620769	-0.423245947030372	0.672378023228003	   
df.mm.trans2:exp3	0.249519265502199	0.0657124977620769	3.79713561346618	0.000172748794208138	***
df.mm.trans1:exp4	0.0391496898513752	0.0657124977620769	0.595772359667763	0.551715697684558	   
df.mm.trans2:exp4	0.138055871738249	0.0657124977620769	2.10090738352549	0.0363700951712456	*  
df.mm.trans1:exp5	0.0387680537296223	0.0657124977620769	0.589964695452432	0.55559828562913	   
df.mm.trans2:exp5	-0.00755313242725499	0.0657124977620769	-0.114942099060096	0.908557497754953	   
df.mm.trans1:exp6	-0.0158672313733377	0.0657124977620769	-0.241464438481515	0.809337798248252	   
df.mm.trans2:exp6	0.0201221164523440	0.0657124977620769	0.30621445140009	0.75962501158058	   
df.mm.trans1:exp7	0.0629619084048146	0.0657124977620769	0.958142066563634	0.338658215523086	   
df.mm.trans2:exp7	0.191508398877667	0.0657124977620769	2.91433753699418	0.00379575591249467	** 
df.mm.trans1:exp8	0.0954433035089	0.0657124977620769	1.45243761475128	0.147283577594500	   
df.mm.trans2:exp8	0.082867714082828	0.0657124977620769	1.26106474270487	0.208132701392155	   
df.mm.trans1:probe2	-0.0664868920164454	0.0359922173342973	-1.8472574612148	0.0655609124667924	.  
df.mm.trans1:probe3	-0.0444639305589633	0.0359922173342973	-1.23537625220420	0.217526251025715	   
df.mm.trans1:probe4	0.056302164424456	0.0359922173342973	1.56428718746386	0.118661623540864	   
df.mm.trans1:probe5	-0.297327384175054	0.0359922173342973	-8.26087988448904	3.08561301930825e-15	***
df.mm.trans1:probe6	-0.248200024655657	0.0359922173342973	-6.89593592832485	2.54084996647069e-11	***
df.mm.trans2:probe2	0.00146189351930561	0.0359922173342973	0.0406169340923755	0.967624643054014	   
df.mm.trans2:probe3	0.0541834899821726	0.0359922173342973	1.50542239392794	0.133125215880411	   
df.mm.trans2:probe4	0.00865643628895038	0.0359922173342973	0.240508557962657	0.81007805906996	   
df.mm.trans2:probe5	0.0666746856671445	0.0359922173342973	1.85247507948363	0.0648066355640352	.  
df.mm.trans2:probe6	0.120212673463778	0.0359922173342973	3.33996297997529	0.000928977436827807	***
df.mm.trans3:probe2	-0.156066631465423	0.0359922173342973	-4.33612161251054	1.90298751490041e-05	***
df.mm.trans3:probe3	-0.0417799319327106	0.0359922173342973	-1.16080461352677	0.246519314465766	   
df.mm.trans3:probe4	-0.321249987906669	0.0359922173342973	-8.92554034453852	2.61594302964330e-17	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.32316014099869	0.185798539827181	23.2679984730765	7.9765497635883e-73	***
df.mm.trans1	0.00387547171862307	0.154795681149391	0.025036045513976	0.980040603591415	   
df.mm.trans2	-0.167925079019761	0.154795681149391	-1.08481759809370	0.278755559439743	   
df.mm.exp2	0.159901713731296	0.213275930332024	0.749741020856709	0.453918695139415	   
df.mm.exp3	0.482501393560611	0.213275930332024	2.26233402339149	0.024294706039683	*  
df.mm.exp4	0.0951567060838729	0.213275930332024	0.446167112883927	0.655754815083909	   
df.mm.exp5	0.304371291183925	0.213275930332024	1.42712443317014	0.154443241606447	   
df.mm.exp6	0.148352192601587	0.213275930332024	0.695588069270804	0.487152414218574	   
df.mm.exp7	0.123412456619851	0.213275930332024	0.578651591990359	0.563199671216316	   
df.mm.exp8	0.201317688723200	0.213275930332024	0.943930655511814	0.345861840535293	   
df.mm.trans1:exp2	-0.123367254272513	0.180251059951293	-0.684419022589098	0.494167457592008	   
df.mm.trans2:exp2	-0.198239418909983	0.180251059951293	-1.09979613414507	0.272183362490166	   
df.mm.trans1:exp3	-0.317688460149192	0.180251059951293	-1.76247762556867	0.0788689596193196	.  
df.mm.trans2:exp3	-0.382087975450829	0.180251059951293	-2.11975438898432	0.0347362499106535	*  
df.mm.trans1:exp4	-0.149358787091210	0.180251059951293	-0.828615305405521	0.407891699896576	   
df.mm.trans2:exp4	-0.0996625644536186	0.180251059951293	-0.552909727579683	0.580681237023342	   
df.mm.trans1:exp5	-0.369363222602377	0.180251059951293	-2.04915978137485	0.0411980797817573	*  
df.mm.trans2:exp5	-0.107486641807686	0.180251059951293	-0.596316281506087	0.551352757318823	   
df.mm.trans1:exp6	0.00190817917625125	0.180251059951293	0.0105862299881447	0.991559651878726	   
df.mm.trans2:exp6	-0.236665714629322	0.180251059951293	-1.31297821323921	0.190057913934245	   
df.mm.trans1:exp7	-0.116880080323428	0.180251059951293	-0.648429364881464	0.517136142770506	   
df.mm.trans2:exp7	-0.235066463082662	0.180251059951293	-1.30410585738681	0.193061881615597	   
df.mm.trans1:exp8	-0.227676027685372	0.180251059951293	-1.26310506993354	0.20739947313104	   
df.mm.trans2:exp8	-0.0113328382992000	0.180251059951293	-0.062872519597179	0.949904217758253	   
df.mm.trans1:probe2	-0.0886471445363202	0.0987275715495392	-0.897896536347388	0.369863283667513	   
df.mm.trans1:probe3	-0.123561862148030	0.0987275715495392	-1.25154361855269	0.211579250378254	   
df.mm.trans1:probe4	-0.0904833573084949	0.0987275715495392	-0.916495320287427	0.360043663669316	   
df.mm.trans1:probe5	-0.139530094515331	0.0987275715495392	-1.41328397250527	0.158468641875622	   
df.mm.trans1:probe6	-0.0283211367996746	0.0987275715495392	-0.28686147501829	0.774389600171235	   
df.mm.trans2:probe2	0.0208554125114764	0.0987275715495392	0.211242028788398	0.83282242123853	   
df.mm.trans2:probe3	0.0399621568770286	0.0987275715495392	0.404772002894617	0.685894510724445	   
df.mm.trans2:probe4	0.122120875422603	0.0987275715495392	1.23694803291425	0.216942844254662	   
df.mm.trans2:probe5	-0.0293939022065946	0.0987275715495392	-0.297727390082166	0.76608940806396	   
df.mm.trans2:probe6	0.00330923664008164	0.0987275715495392	0.0335188700394716	0.973280090158244	   
df.mm.trans3:probe2	-0.00883687739074481	0.0987275715495392	-0.0895076952876398	0.928730077308452	   
df.mm.trans3:probe3	0.207569741234607	0.0987275715495392	2.10244957894516	0.0362339749588834	*  
df.mm.trans3:probe4	0.226309691480703	0.0987275715495392	2.29226433840871	0.0224884860642474	*