chr6.19907_chr6_107618541_107620436_-_1.R 

fitVsDatCorrelation=0.884434690218732
cont.fitVsDatCorrelation=0.261116443987181

fstatistic=7676.02162345353,39,393
cont.fstatistic=1786.24155252577,39,393

residuals=-0.806286017358683,-0.0880986554629236,-0.0116234769828665,0.0815689701395603,0.60311391505135
cont.residuals=-0.726395669211223,-0.237464858695302,-0.0434445917929407,0.184898430967347,1.31777480627609

predictedValues:
Include	Exclude	Both
chr6.19907_chr6_107618541_107620436_-_1.R.tl.Lung	76.3615770928746	52.7924792275255	63.5014012132413
chr6.19907_chr6_107618541_107620436_-_1.R.tl.cerebhem	109.725464462254	62.288831293255	66.172342267521
chr6.19907_chr6_107618541_107620436_-_1.R.tl.cortex	104.518437744589	51.7778411643671	82.5474995848604
chr6.19907_chr6_107618541_107620436_-_1.R.tl.heart	77.1367943505134	48.1052286719484	69.1709072840186
chr6.19907_chr6_107618541_107620436_-_1.R.tl.kidney	85.3812923802195	54.3043607872438	70.7251784988843
chr6.19907_chr6_107618541_107620436_-_1.R.tl.liver	69.8636570454681	53.3777540841415	61.912005595253
chr6.19907_chr6_107618541_107620436_-_1.R.tl.stomach	72.3593331125862	50.9404124968483	62.6120969484475
chr6.19907_chr6_107618541_107620436_-_1.R.tl.testicle	75.195397612353	50.8181752937052	63.8069056123929


diffExp=23.5690978653491,47.4366331689994,52.7405965802215,29.0315656785650,31.0769315929757,16.4859029613266,21.4189206157378,24.3772223186478
diffExpScore=0.995953659213874
diffExp1.5=0,1,1,1,1,0,0,0
diffExp1.5Score=0.8
diffExp1.4=1,1,1,1,1,0,1,1
diffExp1.4Score=0.875
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	64.4260586082381	60.8241166409175	66.7448162535813
cerebhem	67.5820243374663	68.3364375670917	63.7255435346935
cortex	68.6983192020459	68.9533390856894	71.6098568043887
heart	66.0164142769446	60.3103176844349	66.1720611583087
kidney	68.5247647950411	67.9972228098029	68.6589109982639
liver	73.0784122589602	67.231015628628	63.2728334775632
stomach	74.3261442949043	69.638945260859	73.1278538415194
testicle	79.7990747588287	68.0583814591104	76.841361524625
cont.diffExp=3.60194196732057,-0.754413229625413,-0.255019883643470,5.70609659250966,0.527541985238216,5.84739663033223,4.68719903404532,11.7406932997183
cont.diffExpScore=1.03173896064875

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

tran.correlation=0.651455025801391
cont.tran.correlation=0.59462240246927

tran.covariance=0.00801945629980229
cont.tran.covariance=0.00247595249909825

tran.mean=68.4341898012433
cont.tran.mean=68.3625617918102

weightedLogRatios:
wLogRatio
Lung	1.53215140905793
cerebhem	2.49970312659005
cortex	3.01903482396671
heart	1.94045605075545
kidney	1.91003667016963
liver	1.10674291789337
stomach	1.44120904873857
testicle	1.61599889424167

cont.weightedLogRatios:
wLogRatio
Lung	0.237994897457424
cerebhem	-0.0468342712973083
cortex	-0.0156792532634241
heart	0.374682079279853
kidney	0.0326393655368562
liver	0.354429011646201
stomach	0.278526543186076
testicle	0.684318171387114

varWeightedLogRatios=0.381009778743011
cont.varWeightedLogRatios=0.0601049725755121

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.51696898097569	0.0836826313605584	42.0274664383142	1.79130005695686e-147	***
df.mm.trans1	0.755831387311035	0.0683265823889312	11.0620399979712	6.02789400491838e-25	***
df.mm.trans2	0.436194230244514	0.0683265823889312	6.38396089770147	4.8705301805591e-10	***
df.mm.exp2	0.48671459842593	0.0928375440726905	5.24264836265853	2.59043152378025e-07	***
df.mm.exp3	0.0321654726562885	0.0928375440726905	0.346470525233880	0.729174556822684	   
df.mm.exp4	-0.168395509912607	0.0928375440726905	-1.81387294972770	0.0704597951438207	.  
df.mm.exp5	0.0321434881387227	0.0928375440726905	0.346233718909613	0.729352362594015	   
df.mm.exp6	-0.0525608788702731	0.0928375440726904	-0.566159729829978	0.571608342552788	   
df.mm.exp7	-0.0754439116890483	0.0928375440726905	-0.81264441495756	0.41691395378786	   
df.mm.exp8	-0.0583037455677916	0.0928375440726905	-0.628019042836167	0.53035622862778	   
df.mm.trans1:exp2	-0.124212781928499	0.0758015373170788	-1.63865782047289	0.102084822970389	   
df.mm.trans2:exp2	-0.321301203379518	0.0758015373170789	-4.23871618903336	2.80458782443254e-05	***
df.mm.trans1:exp3	0.281718368898073	0.0758015373170789	3.71652579709091	0.000231283296357655	***
df.mm.trans2:exp3	-0.0515719333573103	0.0758015373170789	-0.68035471551961	0.496680489297744	   
df.mm.trans1:exp4	0.178496253540061	0.0758015373170789	2.35478408298513	0.0190245124062702	*  
df.mm.trans2:exp4	0.0754176436207461	0.0758015373170789	0.99493554207579	0.320379802215183	   
df.mm.trans1:exp5	0.079503877844837	0.0758015373170789	1.04884255199563	0.294895158786650	   
df.mm.trans2:exp5	-0.00390769696031038	0.0758015373170789	-0.0515516848156315	0.958912109948212	   
df.mm.trans1:exp6	-0.0363731869525215	0.0758015373170788	-0.479847615759717	0.631602694961427	   
df.mm.trans2:exp6	0.0635862061597944	0.0758015373170788	0.838851142211172	0.402062784110523	   
df.mm.trans1:exp7	0.0216087038952469	0.0758015373170789	0.285069467718806	0.775741088839056	   
df.mm.trans2:exp7	0.039731737213562	0.0758015373170788	0.52415476809347	0.600466382354172	   
df.mm.trans1:exp8	0.0429141206528243	0.0758015373170789	0.566137867010717	0.571623188923231	   
df.mm.trans2:exp8	0.0201890758416713	0.0758015373170788	0.266341245260239	0.790116092635483	   
df.mm.trans1:probe2	0.173051364645187	0.0464187720363452	3.72804701748012	0.00022131034499583	***
df.mm.trans1:probe3	0.187529261477522	0.0464187720363452	4.03994447183328	6.4317464366388e-05	***
df.mm.trans1:probe4	0.0685275309556522	0.0464187720363452	1.47628918106658	0.140667065196768	   
df.mm.trans1:probe5	0.315715752473167	0.0464187720363452	6.80146713545042	3.86970468258810e-11	***
df.mm.trans1:probe6	0.00732749542125636	0.0464187720363452	0.157856296058824	0.874651111842774	   
df.mm.trans2:probe2	-0.0109313763182291	0.0464187720363452	-0.235494732813483	0.813947432111278	   
df.mm.trans2:probe3	-0.0186028188711842	0.0464187720363452	-0.400760684850053	0.688814110453565	   
df.mm.trans2:probe4	0.204813250392221	0.0464187720363452	4.41229359173601	1.32274588381277e-05	***
df.mm.trans2:probe5	-0.0278394609480050	0.0464187720363452	-0.599745743515299	0.549021318848988	   
df.mm.trans2:probe6	0.0110267714333274	0.0464187720363452	0.237549830587798	0.812354055846922	   
df.mm.trans3:probe2	-0.575324540699684	0.0464187720363452	-12.3942214638770	5.25731372848073e-30	***
df.mm.trans3:probe3	-0.751220597254492	0.0464187720363452	-16.1835517033130	1.66204364323906e-45	***
df.mm.trans3:probe4	-0.815399790058624	0.0464187720363452	-17.5661645986709	2.12130298298379e-51	***
df.mm.trans3:probe5	-0.510501199679006	0.0464187720363452	-10.9977316780222	1.04061669048373e-24	***
df.mm.trans3:probe6	-0.695149631462955	0.0464187720363452	-14.9756144113132	1.96026112549319e-40	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.06697525728914	0.17309982697143	23.4949700900648	6.99823033478924e-77	***
df.mm.trans1	0.115123324772397	0.141335416881354	0.814539818204514	0.41582906771692	   
df.mm.trans2	0.0294856622463849	0.141335416881354	0.208621893202729	0.834851500858839	   
df.mm.exp2	0.210571754662952	0.192037015975211	1.09651648976952	0.273524256827637	   
df.mm.exp3	0.119294116011593	0.192037015975211	0.621203758066058	0.534825699973362	   
df.mm.exp4	0.0245203517666099	0.192037015975211	0.127685548757824	0.89846313578341	   
df.mm.exp5	0.144883227479191	0.192037015975211	0.754454690640962	0.451028074037889	   
df.mm.exp6	0.279583703788652	0.192037015975211	1.45588444169921	0.146222937678255	   
df.mm.exp7	0.186949483600163	0.192037015975211	0.97350754306813	0.330899920487539	   
df.mm.exp8	0.185506822387157	0.192037015975211	0.965995130913215	0.334640673103199	   
df.mm.trans1:exp2	-0.162747907183411	0.156797566955323	-1.03794918724590	0.299931897390836	   
df.mm.trans2:exp2	-0.0941150030168297	0.156797566955323	-0.600232547254042	0.548697214781264	   
df.mm.trans1:exp3	-0.0550875708869132	0.156797566955323	-0.351329245450662	0.725529632025499	   
df.mm.trans2:exp3	0.00614954909039189	0.156797566955323	0.0392196716428904	0.968735165270285	   
df.mm.trans1:exp4	-0.000135127536174516	0.156797566955323	-0.00086179612859056	0.999312823530934	   
df.mm.trans2:exp4	-0.0330035223960133	0.156797566955323	-0.210484914000083	0.833398311528943	   
df.mm.trans1:exp5	-0.0832062057333764	0.156797566955323	-0.530660056460473	0.595954101197443	   
df.mm.trans2:exp5	-0.0334027297728742	0.156797566955323	-0.213030918919755	0.831413306963373	   
df.mm.trans1:exp6	-0.153568886623538	0.156797566955323	-0.979408606941555	0.327980644307942	   
df.mm.trans2:exp6	-0.179435386248123	0.156797566955323	-1.14437608779511	0.253164201389208	   
df.mm.trans1:exp7	-0.0440049070474839	0.156797566955323	-0.280647894619579	0.779128158277822	   
df.mm.trans2:exp7	-0.0516118800119705	0.156797566955323	-0.329162505606203	0.742208207339604	   
df.mm.trans1:exp8	0.0284868994596875	0.156797566955323	0.181679473813547	0.855927942588067	   
df.mm.trans2:exp8	-0.0731273002892248	0.156797566955323	-0.466380325340516	0.641201697693146	   
df.mm.trans1:probe2	-0.0189045752159564	0.0960185079876055	-0.196884700795358	0.844019544909307	   
df.mm.trans1:probe3	-0.059573190175001	0.0960185079876055	-0.620434449811394	0.535331408456459	   
df.mm.trans1:probe4	0.0241429149963449	0.0960185079876055	0.251440222331526	0.801605196746736	   
df.mm.trans1:probe5	-0.0408304202126677	0.0960185079876055	-0.425234895525957	0.670898190603652	   
df.mm.trans1:probe6	-0.103799457641509	0.0960185079876055	-1.08103593585216	0.280344045387060	   
df.mm.trans2:probe2	-0.0877404020620408	0.0960185079876055	-0.913786351203945	0.361389382069912	   
df.mm.trans2:probe3	0.00510236211060936	0.0960185079876055	0.0531393604998319	0.957647871383897	   
df.mm.trans2:probe4	0.126349947475354	0.0960185079876055	1.31589159343805	0.18897748535062	   
df.mm.trans2:probe5	-0.0135785417605268	0.0960185079876055	-0.141415879553967	0.88761387089076	   
df.mm.trans2:probe6	0.108171987051793	0.0960185079876055	1.12657433779076	0.26060991626278	   
df.mm.trans3:probe2	-0.0537901970162222	0.0960185079876055	-0.56020654917035	0.575657748207427	   
df.mm.trans3:probe3	-0.0679138467624422	0.0960185079876055	-0.707299542409145	0.479799545590684	   
df.mm.trans3:probe4	0.0415826194359583	0.0960185079876055	0.433068793792609	0.665202371954614	   
df.mm.trans3:probe5	-0.0649426830852028	0.0960185079876055	-0.676355886446245	0.499212567208585	   
df.mm.trans3:probe6	0.0808184524344826	0.0960185079876055	0.841696607542736	0.400469673924491