chr3.15116_chr3_103919110_103922362_+_2.R 

fitVsDatCorrelation=0.788637929112273
cont.fitVsDatCorrelation=0.263988133745907

fstatistic=9724.2998401964,59,853
cont.fstatistic=3943.08160372062,59,853

residuals=-0.539425647521988,-0.0901393081571895,-0.00674565694315481,0.0745216633351554,0.975836814768879
cont.residuals=-0.559838229713989,-0.184236231031750,-0.0225557045620277,0.154200777632198,1.22933457866389

predictedValues:
Include	Exclude	Both
chr3.15116_chr3_103919110_103922362_+_2.R.tl.Lung	59.6345905838924	62.9524874940313	67.3814519659176
chr3.15116_chr3_103919110_103922362_+_2.R.tl.cerebhem	69.2508157706362	89.672623996162	72.6250434004117
chr3.15116_chr3_103919110_103922362_+_2.R.tl.cortex	59.951825306753	59.7180596893221	60.2141731106595
chr3.15116_chr3_103919110_103922362_+_2.R.tl.heart	59.5186243144559	55.5582674374529	65.5144593217587
chr3.15116_chr3_103919110_103922362_+_2.R.tl.kidney	59.3406061141743	53.7695398180437	72.6292544279392
chr3.15116_chr3_103919110_103922362_+_2.R.tl.liver	59.0845245515105	51.4803286497381	74.7800543110817
chr3.15116_chr3_103919110_103922362_+_2.R.tl.stomach	58.837235252618	61.355885663563	57.4354238112863
chr3.15116_chr3_103919110_103922362_+_2.R.tl.testicle	64.361511809987	60.9157413312552	66.9782823798446


diffExp=-3.3178969101389,-20.4218082255258,0.233765617430976,3.96035687700295,5.57106629613052,7.60419590177239,-2.51865041094497,3.44577047873188
diffExpScore=7.30592065650703
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,-1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	61.6819129852151	62.2671417689653	52.644682665032
cerebhem	61.4618396527589	64.2045099656172	57.7675056688025
cortex	62.5602227750409	62.4721189317933	59.564152071169
heart	65.6300089750685	51.3935906734484	61.2527323425857
kidney	64.5333141306157	59.2827842956366	62.5055698584169
liver	65.3624615164035	65.9787766007249	53.9747377684704
stomach	64.780635141816	65.8480070385135	61.3269326482116
testicle	61.9631213882952	61.0574042710116	59.4291146198599
cont.diffExp=-0.585228783750154,-2.74267031285824,0.0881038432476018,14.2364183016201,5.25052983497911,-0.6163150843214,-1.06737189669749,0.905717117283587
cont.diffExpScore=1.54788219576947

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

tran.correlation=0.880394762172609
cont.tran.correlation=-0.295827977381944

tran.covariance=0.00848747364988717
cont.tran.covariance=-0.000706557949984905

tran.mean=61.5876667364747
cont.tran.mean=62.5298656319328

weightedLogRatios:
wLogRatio
Lung	-0.222821256373037
cerebhem	-1.12855357702679
cortex	0.0159852044568394
heart	0.27899875052518
kidney	0.397698781583871
liver	0.55246640665116
stomach	-0.171677544570119
testicle	0.227635287116955

cont.weightedLogRatios:
wLogRatio
Lung	-0.0389690550623464
cerebhem	-0.180750542865287
cortex	0.00582804244173981
heart	0.993183073175748
kidney	0.350037197856965
liver	-0.0392729062362943
stomach	-0.0682979825782669
testicle	0.060654536274406

varWeightedLogRatios=0.277962416335658
cont.varWeightedLogRatios=0.143799407387727

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.91147470225539	0.087456021650236	44.7250472688845	7.16785679890429e-226	***
df.mm.trans1	0.0186105412379287	0.0789944683161707	0.235592967895436	0.813805080914374	   
df.mm.trans2	0.219224165229166	0.0720439050764747	3.04292451938105	0.00241473318048952	** 
df.mm.exp2	0.428344366574543	0.0985013487198058	4.34861422855234	1.53550225673508e-05	***
df.mm.exp3	0.0650217787539623	0.0985013487198058	0.660110542637558	0.509361095314864	   
df.mm.exp4	-0.0987955333353457	0.0985013487198057	-1.00298660494870	0.316151756889773	   
df.mm.exp5	-0.237613105787355	0.0985013487198058	-2.4122827644042	0.0160631081922192	*  
df.mm.exp6	-0.314628663971893	0.0985013487198058	-3.19415589797534	0.00145388676580993	** 
df.mm.exp7	0.120558483846750	0.0985013487198057	1.22392723971412	0.221317629229801	   
df.mm.exp8	0.0493927350671298	0.0985013487198058	0.501442220934771	0.616189316940041	   
df.mm.trans1:exp2	-0.278845226136054	0.0952709134248567	-2.92686630275659	0.00351491318314372	** 
df.mm.trans2:exp2	-0.0745591143321653	0.0817129123905882	-0.912452048897392	0.361788606355724	   
df.mm.trans1:exp3	-0.0597162352330622	0.0952709134248567	-0.626804478789451	0.530955123513251	   
df.mm.trans2:exp3	-0.117767571846013	0.0817129123905882	-1.44123576556767	0.149885074878406	   
df.mm.trans1:exp4	0.0968490259557377	0.0952709134248567	1.01656447360637	0.309648905732894	   
df.mm.trans2:exp4	-0.0261524079991975	0.0817129123905882	-0.320052329969453	0.749007039226753	   
df.mm.trans1:exp5	0.232671150216666	0.0952709134248567	2.44220551532951	0.0147999146639535	*  
df.mm.trans2:exp5	0.0799399631287401	0.0817129123905881	0.978302703820257	0.328202003460049	   
df.mm.trans1:exp6	0.305361917533488	0.0952709134248567	3.20519565265150	0.00139989845014078	** 
df.mm.trans2:exp6	0.113448155603678	0.0817129123905881	1.38837488818652	0.165385373174572	   
df.mm.trans1:exp7	-0.134019361407405	0.0952709134248567	-1.40671855227997	0.159875081589359	   
df.mm.trans2:exp7	-0.146247656558291	0.0817129123905881	-1.78977412846609	0.0738448567133749	.  
df.mm.trans1:exp8	0.0268872920405657	0.0952709134248567	0.282219316200559	0.77784380788497	   
df.mm.trans2:exp8	-0.0822813905086274	0.0817129123905881	-1.00695701696841	0.314240983005896	   
df.mm.trans1:probe2	0.114691072304755	0.0476354567124283	2.40768285265190	0.0162654893036855	*  
df.mm.trans1:probe3	0.227149332536890	0.0476354567124283	4.76849280375695	2.18214326840897e-06	***
df.mm.trans1:probe4	0.229045683220461	0.0476354567124283	4.80830245006765	1.79890769792092e-06	***
df.mm.trans1:probe5	0.0151290174793286	0.0476354567124283	0.317599925002532	0.750866158560523	   
df.mm.trans1:probe6	0.0402900031320695	0.0476354567124283	0.845798611217211	0.397902294118863	   
df.mm.trans1:probe7	-0.00201912770277474	0.0476354567124283	-0.0423870755551703	0.966200050810502	   
df.mm.trans1:probe8	0.516743204915881	0.0476354567124284	10.8478692255523	8.98357655286586e-26	***
df.mm.trans1:probe9	0.424431290054383	0.0476354567124283	8.90998679023155	3.03927269499323e-18	***
df.mm.trans1:probe10	0.00939687309971264	0.0476354567124283	0.197266358889783	0.843666098380355	   
df.mm.trans1:probe11	-0.00113370286473986	0.0476354567124283	-0.0237995590466139	0.98101805798535	   
df.mm.trans1:probe12	-0.0795889285043711	0.0476354567124283	-1.67079175885399	0.095129641164514	.  
df.mm.trans1:probe13	-0.108893781991685	0.0476354567124283	-2.2859816931969	0.0224997566153830	*  
df.mm.trans1:probe14	-0.107404755806996	0.0476354567124283	-2.25472291481093	0.0244036047265376	*  
df.mm.trans1:probe15	-0.103554231542714	0.0476354567124283	-2.17388975963563	0.0299877647036422	*  
df.mm.trans1:probe16	0.0181487674576920	0.0476354567124283	0.380992829926136	0.70330343709117	   
df.mm.trans1:probe17	0.424549796763706	0.0476354567124283	8.91247457385958	2.97751278094147e-18	***
df.mm.trans1:probe18	0.465172507113209	0.0476354567124283	9.76525762986635	2.00143001683815e-21	***
df.mm.trans1:probe19	0.407090232198887	0.0476354567124283	8.54595001904694	5.83003336534032e-17	***
df.mm.trans1:probe20	0.530101509867127	0.0476354567124283	11.1282969966533	5.91081674028432e-27	***
df.mm.trans1:probe21	0.31245331899651	0.0476354567124283	6.55925943741375	9.36603516396948e-11	***
df.mm.trans1:probe22	0.296492687893571	0.0476354567124283	6.22420164213969	7.58293279522539e-10	***
df.mm.trans1:probe23	0.116042773381387	0.0476354567124283	2.43605879716717	0.0150519992012283	*  
df.mm.trans1:probe24	0.232388305250839	0.0476354567124283	4.87847333245381	1.27550436382411e-06	***
df.mm.trans1:probe25	0.209825717747132	0.0476354567124283	4.40482221077115	1.19336297796733e-05	***
df.mm.trans1:probe26	0.0349490634144221	0.0476354567124283	0.733677513063577	0.463346904480789	   
df.mm.trans1:probe27	0.466235268272579	0.0476354567124283	9.78756792628663	1.64167592822087e-21	***
df.mm.trans1:probe28	0.397326560669236	0.0476354567124283	8.340983546518	2.94270832931396e-16	***
df.mm.trans1:probe29	-0.0242411406318957	0.0476354567124283	-0.508888594859867	0.610961914383686	   
df.mm.trans2:probe2	0.116073955811041	0.0476354567124283	2.43671340261879	0.0150249739495545	*  
df.mm.trans2:probe3	-0.0184349870831599	0.0476354567124283	-0.387001371571821	0.698851722133701	   
df.mm.trans2:probe4	0.103615558764351	0.0476354567124283	2.17517718765394	0.0298908545159194	*  
df.mm.trans2:probe5	-0.188225461612692	0.0476354567124283	-3.95137308641744	8.41307649148863e-05	***
df.mm.trans2:probe6	0.092103602689264	0.0476354567124283	1.93350938661692	0.0535040637134314	.  
df.mm.trans3:probe2	0.120782577132818	0.0476354567124283	2.5355603885982	0.0114042698149628	*  
df.mm.trans3:probe3	0.0623985566845387	0.0476354567124283	1.30991830436799	0.190576132205561	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.45120927699162	0.137192028752783	32.4451013477801	4.70764547530485e-151	***
df.mm.trans1	-0.24468075009373	0.123918412523784	-1.97453102497394	0.0486435634021413	*  
df.mm.trans2	-0.33947726371087	0.113015082440442	-3.00382264367034	0.00274402426195205	** 
df.mm.exp2	-0.0657958574489332	0.154518803974421	-0.425811330120216	0.6703527460348	   
df.mm.exp3	-0.106063271670490	0.154518803974421	-0.686410125773736	0.492641059388494	   
df.mm.exp4	-0.281321314456578	0.154518803974421	-1.82062834568114	0.0690136295013035	.  
df.mm.exp5	-0.175614504666961	0.154518803974421	-1.13652513577592	0.256056037482502	   
df.mm.exp6	0.090905745192048	0.154518803974421	0.588315097281601	0.556476546422334	   
df.mm.exp7	-0.0477225948523806	0.154518803974421	-0.30884651980791	0.757513695460794	   
df.mm.exp8	-0.136289755572203	0.154518803974421	-0.882026990027467	0.378010689615306	   
df.mm.trans1:exp2	0.0622216027744803	0.149451228711952	0.416333832185510	0.677270471806509	   
df.mm.trans2:exp2	0.0964354471430588	0.128182828519195	0.752327345691374	0.452061776504175	   
df.mm.trans1:exp3	0.120202185433196	0.149451228711952	0.804290379337533	0.421453386522026	   
df.mm.trans2:exp3	0.109349764570537	0.128182828519195	0.853076545694749	0.393856330751344	   
df.mm.trans1:exp4	0.34336361624461	0.149451228711952	2.29749610761915	0.0218317871145121	*  
df.mm.trans2:exp4	0.0894009168534325	0.128182828519195	0.697448463934034	0.485712229538379	   
df.mm.trans1:exp5	0.220805349828391	0.149451228711952	1.47744084629752	0.139926610399757	   
df.mm.trans2:exp5	0.126499585881587	0.128182828519195	0.986868423352384	0.323986985773114	   
df.mm.trans1:exp6	-0.0329483778998879	0.149451228711952	-0.220462408933363	0.825563799648038	   
df.mm.trans2:exp6	-0.0330064887550410	0.128182828519195	-0.257495400408474	0.796858469181759	   
df.mm.trans1:exp7	0.0967385696947255	0.149451228711952	0.647291899360537	0.517617198474236	   
df.mm.trans2:exp7	0.103637890192942	0.128182828519195	0.808516174827758	0.419018932402834	   
df.mm.trans1:exp8	0.140838403875949	0.149451228711952	0.942370331042218	0.346269884355318	   
df.mm.trans2:exp8	0.116670363635200	0.128182828519195	0.910187152078088	0.362980935272265	   
df.mm.trans1:probe2	-0.125246392682636	0.0747256143559761	-1.67608381359021	0.0940882246377327	.  
df.mm.trans1:probe3	-0.144863803109940	0.0747256143559761	-1.93860973052481	0.0528784507415904	.  
df.mm.trans1:probe4	-0.0683830809095441	0.0747256143559761	-0.9151223646524	0.36038601188732	   
df.mm.trans1:probe5	-0.12650194431413	0.0747256143559761	-1.69288597229195	0.0908423207906157	.  
df.mm.trans1:probe6	-0.10613256236169	0.0747256143559761	-1.42029695274365	0.155886642842835	   
df.mm.trans1:probe7	-0.0895512560339115	0.0747256143559761	-1.19840106776920	0.231093763200748	   
df.mm.trans1:probe8	-0.0673629380028613	0.0747256143559761	-0.901470514273182	0.367592660937102	   
df.mm.trans1:probe9	-0.0423535177125632	0.0747256143559761	-0.566787146249484	0.571007909869407	   
df.mm.trans1:probe10	-0.119433107213258	0.0747256143559761	-1.59828872927435	0.110349066469035	   
df.mm.trans1:probe11	-0.0467406825398549	0.0747256143559761	-0.625497467537607	0.531811916726264	   
df.mm.trans1:probe12	-0.0716473429631285	0.0747256143559761	-0.958805673002789	0.337928330655151	   
df.mm.trans1:probe13	-0.075452918955494	0.0747256143559761	-1.00973300260943	0.312909559434187	   
df.mm.trans1:probe14	-0.0488925501483012	0.0747256143559761	-0.654294388472847	0.51309852459802	   
df.mm.trans1:probe15	-0.123271104056484	0.0747256143559761	-1.64964992417791	0.0993827243486111	.  
df.mm.trans1:probe16	-0.036814250889967	0.0747256143559761	-0.4926590595106	0.622380294363063	   
df.mm.trans1:probe17	-0.105636363039625	0.0747256143559761	-1.41365666846708	0.157827567890505	   
df.mm.trans1:probe18	-0.0586118368477379	0.0747256143559761	-0.784360722262171	0.433046239467314	   
df.mm.trans1:probe19	-0.056048524992811	0.0747256143559761	-0.750057734230305	0.453426759039666	   
df.mm.trans1:probe20	-0.114354835875026	0.0747256143559761	-1.53032981877225	0.12630585907457	   
df.mm.trans1:probe21	-0.125186315357287	0.0747256143559761	-1.67527984127273	0.0942458448109146	.  
df.mm.trans1:probe22	-0.166127720339176	0.0747256143559761	-2.22316968245695	0.0264657006329567	*  
df.mm.trans1:probe23	-0.0373144137645808	0.0747256143559761	-0.499352385205202	0.617659921793762	   
df.mm.trans1:probe24	-0.125556482202786	0.0747256143559761	-1.68023352213156	0.0932780309850004	.  
df.mm.trans1:probe25	-0.112143485903173	0.0747256143559761	-1.50073688747404	0.133793670794474	   
df.mm.trans1:probe26	-0.218723907275223	0.0747256143559761	-2.92702722032195	0.00351311339311443	** 
df.mm.trans1:probe27	-0.121863013893356	0.0747256143559761	-1.63080645028662	0.103300308962493	   
df.mm.trans1:probe28	-0.171057574363316	0.0747256143559761	-2.28914242910651	0.0223146480675972	*  
df.mm.trans1:probe29	6.28554192780006e-05	0.0747256143559761	0.000841149581970265	0.999329056471708	   
df.mm.trans2:probe2	0.0203795146116971	0.0747256143559761	0.272724617754411	0.785130917219038	   
df.mm.trans2:probe3	0.0459218577779252	0.0747256143559761	0.614539715380107	0.539022617495354	   
df.mm.trans2:probe4	-7.60973643981694e-05	0.0747256143559761	-0.00101835715977735	0.999187706800576	   
df.mm.trans2:probe5	0.0157971002950758	0.0747256143559761	0.211401410764212	0.83262455191338	   
df.mm.trans2:probe6	0.09529431013378	0.0747256143559761	1.27525629538245	0.202565751365330	   
df.mm.trans3:probe2	0.202594944336025	0.0747256143559761	2.71118472671108	0.00683910319041865	** 
df.mm.trans3:probe3	0.0869469844926977	0.0747256143559761	1.16354994525039	0.244931813369141