chr4.16131_chr4_130790967_130793010_+_2.R 

fitVsDatCorrelation=0.90770825036319
cont.fitVsDatCorrelation=0.257848251126720

fstatistic=10724.9261292812,62,922
cont.fstatistic=2010.71158793497,62,922

residuals=-0.850686254893063,-0.0981970658810034,-0.00235485733777582,0.0931653350694976,0.910778074017932
cont.residuals=-0.909334478857216,-0.306322323396515,-0.00825758690344587,0.249408680585883,1.17306689204061

predictedValues:
Include	Exclude	Both
chr4.16131_chr4_130790967_130793010_+_2.R.tl.Lung	88.884162496135	184.987668403229	59.4662759261227
chr4.16131_chr4_130790967_130793010_+_2.R.tl.cerebhem	66.0705855577682	118.391988732842	63.798347436894
chr4.16131_chr4_130790967_130793010_+_2.R.tl.cortex	73.8399418238145	113.470649398746	62.9993359434312
chr4.16131_chr4_130790967_130793010_+_2.R.tl.heart	84.4531151059075	146.091517587846	60.8674859421523
chr4.16131_chr4_130790967_130793010_+_2.R.tl.kidney	96.6231150641147	173.873211681911	62.7374707554355
chr4.16131_chr4_130790967_130793010_+_2.R.tl.liver	87.3788255888423	177.619576044071	62.2521313237226
chr4.16131_chr4_130790967_130793010_+_2.R.tl.stomach	81.271344941921	139.316660293076	73.2986452441975
chr4.16131_chr4_130790967_130793010_+_2.R.tl.testicle	98.926623551018	156.619795631309	75.42906500319


diffExp=-96.1035059070941,-52.3214031750741,-39.6307075749312,-61.6384024819382,-77.2500966177958,-90.2407504552284,-58.0453153511551,-57.6931720802914
diffExpScore=0.998127071997926
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	83.7162253787645	91.8961240044408	87.2030776805454
cerebhem	79.878785017279	71.5936824392677	80.1729899662027
cortex	82.6415278166951	103.419316586628	82.4980182098832
heart	82.8263239420552	86.7486074880847	90.1166290394005
kidney	86.2872940340772	72.4018678374245	96.1477297283282
liver	87.8579520280134	79.477526675723	78.8103476420069
stomach	81.4131443572867	67.6911379443819	73.7733405864436
testicle	79.362093360183	82.4601138313447	91.2544221437076
cont.diffExp=-8.17989862567634,8.28510257801126,-20.7777887699327,-3.92228354602949,13.8854261966527,8.38042535229036,13.7220064129049,-3.09802047116169
cont.diffExpScore=8.6338051106633

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

tran.correlation=0.784957225154158
cont.tran.correlation=0.0338401085117514

tran.covariance=0.0201947109606701
cont.tran.covariance=0.000264858960863989

tran.mean=117.988673868909
cont.tran.mean=82.479482671353

weightedLogRatios:
wLogRatio
Lung	-3.55762637555189
cerebhem	-2.6144606983324
cortex	-1.94058434090664
heart	-2.58137076126089
kidney	-2.85797685464053
liver	-3.42277537540775
stomach	-2.51545387662436
testicle	-2.21639784526417

cont.weightedLogRatios:
wLogRatio
Lung	-0.417097584286299
cerebhem	0.473685540383164
cortex	-1.01523501326740
heart	-0.205426300867069
kidney	0.766710127973575
liver	0.443653038600940
stomach	0.7950377950637
testicle	-0.168231382742336

varWeightedLogRatios=0.306784654681607
cont.varWeightedLogRatios=0.408525357233868

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.60134712641027	0.078087388917943	71.7317764626034	0	***
df.mm.trans1	-1.09278321929268	0.0670637030316405	-16.2947044361255	1.18860480183843e-52	***
df.mm.trans2	-0.368913665845813	0.0588862531572191	-6.26485208459194	5.71851270963051e-10	***
df.mm.exp2	-0.813216363520014	0.0749252322481015	-10.8537049418438	6.53552717637604e-26	***
df.mm.exp3	-0.731893957424504	0.0749252322481015	-9.76832417417097	1.63026091174154e-21	***
df.mm.exp4	-0.310483133755179	0.0749252322481015	-4.14390619073518	3.72855269647897e-05	***
df.mm.exp5	-0.0320283066245401	0.0749252322481015	-0.427470234840034	0.669136674793447	   
df.mm.exp6	-0.103509521644129	0.0749252322481015	-1.38150418141349	0.167458669568767	   
df.mm.exp7	-0.582212940833152	0.0749252322481015	-7.7705857341257	2.07937076911099e-14	***
df.mm.exp8	-0.297206876574034	0.0749252322481015	-3.96671278361723	7.85196161773402e-05	***
df.mm.trans1:exp2	0.516606035210561	0.0687820951281278	7.51076329164186	1.38730346962732e-13	***
df.mm.trans2:exp2	0.366928255374533	0.0487525017918996	7.52634720041177	1.23995689662761e-13	***
df.mm.trans1:exp3	0.546459782751073	0.0687820951281278	7.94479699597872	5.64947712994483e-15	***
df.mm.trans2:exp3	0.243148999721800	0.0487525017918996	4.9874158409282	7.31080205901809e-07	***
df.mm.trans1:exp4	0.259345686314417	0.0687820951281279	3.77054065932865	0.000173266322077094	***
df.mm.trans2:exp4	0.0744272263025762	0.0487525017918996	1.52663398937493	0.127195003880552	   
df.mm.trans1:exp5	0.115512328597043	0.0687820951281279	1.67939531911416	0.0934138251812689	.  
df.mm.trans2:exp5	-0.0299344938404069	0.0487525017918996	-0.61400938906033	0.53936058800168	   
df.mm.trans1:exp6	0.0864285278033698	0.0687820951281279	1.25655561439892	0.209232857139953	   
df.mm.trans2:exp6	0.0628644060244017	0.0487525017918996	1.28946010386788	0.197561550746522	   
df.mm.trans1:exp7	0.492672457519502	0.0687820951281278	7.1628009673411	1.61609240954104e-12	***
df.mm.trans2:exp7	0.298673248984474	0.0487525017918996	6.12631635314558	1.33050205590641e-09	***
df.mm.trans1:exp8	0.404251298649817	0.0687820951281278	5.87727515273815	5.82368916632418e-09	***
df.mm.trans2:exp8	0.130738895449500	0.0487525017918996	2.68168587547691	0.0074561456496212	** 
df.mm.trans1:probe2	0.100053674279669	0.0492720813173858	2.03063624682654	0.0425784588829313	*  
df.mm.trans1:probe3	-0.257893727747205	0.0492720813173858	-5.23407416232297	2.05378647773892e-07	***
df.mm.trans1:probe4	0.123570432605065	0.0492720813173858	2.50791988690485	0.0123152460251661	*  
df.mm.trans1:probe5	-0.0132509986492618	0.0492720813173858	-0.268935232589538	0.788039690422861	   
df.mm.trans1:probe6	-0.328870312721571	0.0492720813173858	-6.67457724391942	4.27517491972611e-11	***
df.mm.trans1:probe7	-0.325441686034611	0.0492720813173858	-6.60499165720808	6.70830881431457e-11	***
df.mm.trans1:probe8	-0.545498807934486	0.0492720813173858	-11.0711541576793	7.7969338652473e-27	***
df.mm.trans1:probe9	-0.108200120626062	0.0492720813173858	-2.19597219628479	0.0283423694625115	*  
df.mm.trans1:probe10	0.212572410285259	0.0492720813173858	4.31425676776216	1.77425157933001e-05	***
df.mm.trans1:probe11	-0.0761043191003925	0.0492720813173858	-1.54457285070154	0.122792760929882	   
df.mm.trans1:probe12	0.165869557801453	0.0492720813173858	3.36640047196312	0.000793032120965156	***
df.mm.trans1:probe13	0.102818631127201	0.0492720813173858	2.08675234287132	0.0371847450405532	*  
df.mm.trans1:probe14	-0.195113289556433	0.0492720813173858	-3.95991572386828	8.07495817587523e-05	***
df.mm.trans1:probe15	0.0621380670794505	0.0492720813173858	1.26112121546457	0.207584181038368	   
df.mm.trans1:probe16	-0.0223567834283986	0.0492720813173858	-0.453741405490616	0.650121740402985	   
df.mm.trans1:probe17	0.0743973269953703	0.0492720813173858	1.50992864531417	0.131404244176781	   
df.mm.trans1:probe18	0.220917831444807	0.0492720813173858	4.48363100437682	8.26242608769389e-06	***
df.mm.trans1:probe19	0.388883389290729	0.0492720813173858	7.89257078031144	8.37097670819159e-15	***
df.mm.trans1:probe20	0.109380699406529	0.0492720813173858	2.21993259635114	0.0266659002418461	*  
df.mm.trans1:probe21	0.142944107009859	0.0492720813173858	2.90111769561926	0.00380676736390072	** 
df.mm.trans1:probe22	-0.573863635658424	0.0492720813173858	-11.6468316400496	2.40898934618950e-29	***
df.mm.trans2:probe2	-0.0577500030523354	0.0492720813173858	-1.17206339793806	0.241474367050408	   
df.mm.trans2:probe3	-0.36871524070644	0.0492720813173858	-7.48324874549875	1.69067119533913e-13	***
df.mm.trans2:probe4	0.126270794901476	0.0492720813173859	2.56272500623839	0.0105431890726728	*  
df.mm.trans2:probe5	0.0551913842912414	0.0492720813173858	1.12013503013454	0.262947919593617	   
df.mm.trans2:probe6	0.0142614598004041	0.0492720813173859	0.289443015579938	0.77230745379555	   
df.mm.trans3:probe2	0.0710384915100875	0.0492720813173858	1.44175950377443	0.149709794331595	   
df.mm.trans3:probe3	-0.257840795980074	0.0492720813173858	-5.23299988728291	2.06541621985404e-07	***
df.mm.trans3:probe4	-0.137071129841316	0.0492720813173858	-2.78192286943133	0.00551407333992585	** 
df.mm.trans3:probe5	-0.145475983582357	0.0492720813173858	-2.95250331816256	0.00323203082082335	** 
df.mm.trans3:probe6	-0.0931251462542231	0.0492720813173858	-1.89001852092178	0.0590689301003861	.  
df.mm.trans3:probe7	0.142082486682411	0.0492720813173858	2.88363070695527	0.004022637012205	** 
df.mm.trans3:probe8	-0.160707390619346	0.0492720813173859	-3.26163186783505	0.00114837776223341	** 
df.mm.trans3:probe9	-0.364997543314257	0.0492720813173858	-7.40779633324453	2.89871976146905e-13	***
df.mm.trans3:probe10	0.477370784959576	0.0492720813173858	9.68846397789845	3.32213007748742e-21	***
df.mm.trans3:probe11	0.0113152081073871	0.0492720813173858	0.229647455614879	0.818416663144184	   
df.mm.trans3:probe12	-0.105717519564991	0.0492720813173858	-2.14558664335716	0.0321665419202006	*  
df.mm.trans3:probe13	-0.142002909442998	0.0492720813173858	-2.88201564955794	0.00404312540277669	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.57281117109657	0.179805911213366	25.4319290185642	1.57637396339528e-108	***
df.mm.trans1	-0.149725676002539	0.154422505349975	-0.969584554163323	0.332507889928866	   
df.mm.trans2	-0.0500329290208834	0.135592911398293	-0.368993692258113	0.712217144149032	   
df.mm.exp2	-0.212521578121264	0.172524652750264	-1.23183310172429	0.218325505735533	   
df.mm.exp3	0.160677761959865	0.172524652750264	0.931332185855504	0.35192555310717	   
df.mm.exp4	-0.101196447817504	0.172524652750264	-0.586562246057612	0.557641323715625	   
df.mm.exp5	-0.305823442768939	0.172524652750264	-1.77263618789386	0.0766191525280478	.  
df.mm.exp6	0.00429928590572143	0.172524652750264	0.0249198351492688	0.980124298236533	   
df.mm.exp7	-0.166357457375619	0.172524652750264	-0.964253251484168	0.335171805472541	   
df.mm.exp8	-0.207167942515978	0.172524652750264	-1.20080196779681	0.230136429554439	   
df.mm.trans1:exp2	0.165599066147264	0.158379316571509	1.04558517950477	0.296026633752643	   
df.mm.trans2:exp2	-0.0371304381353898	0.112258690296782	-0.330757806252922	0.740902584058345	   
df.mm.trans1:exp3	-0.173598260008837	0.158379316571509	-1.09609173575677	0.273324844280753	   
df.mm.trans2:exp3	-0.0425448553910695	0.112258690296782	-0.378989415238965	0.704782982378978	   
df.mm.trans1:exp4	0.0905095703809458	0.158379316571509	0.571473424309673	0.567818048700225	   
df.mm.trans2:exp4	0.0435519622631297	0.112258690296782	0.387960719548659	0.698134655216504	   
df.mm.trans1:exp5	0.336072989516021	0.158379316571509	2.12194999189987	0.0341080674046792	*  
df.mm.trans2:exp5	0.067396688445322	0.112258690296782	0.600369452620043	0.548407577555	   
df.mm.trans1:exp6	0.043989232571241	0.158379316571509	0.277746068890124	0.781269560309448	   
df.mm.trans2:exp6	-0.149483839774094	0.112258690296782	-1.33160149453818	0.18332028273815	   
df.mm.trans1:exp7	0.138461385631817	0.158379316571509	0.874239064981071	0.382215732070881	   
df.mm.trans2:exp7	-0.139346125372018	0.112258690296782	-1.24129477195595	0.214812584469508	   
df.mm.trans1:exp8	0.153755972864423	0.158379316571509	0.970808412315644	0.331898297651412	   
df.mm.trans2:exp8	0.0988237979950026	0.112258690296782	0.880322028822346	0.378914281484083	   
df.mm.trans1:probe2	-0.0436296143701337	0.113455086684501	-0.38455406139224	0.700656514981934	   
df.mm.trans1:probe3	-0.0987869761438596	0.113455086684501	-0.870714386024566	0.384136765541832	   
df.mm.trans1:probe4	0.0164436342403416	0.113455086684501	0.144935187313976	0.884793720269173	   
df.mm.trans1:probe5	0.089191434918425	0.113455086684501	0.786138704970106	0.431988222452331	   
df.mm.trans1:probe6	0.040743730287315	0.113455086684501	0.359117704441196	0.719589261263696	   
df.mm.trans1:probe7	-0.0187878100031943	0.113455086684501	-0.165596894350271	0.8685104939153	   
df.mm.trans1:probe8	-0.0169875226181775	0.113455086684501	-0.149729052390721	0.881011131892493	   
df.mm.trans1:probe9	-0.00111881757241871	0.113455086684501	-0.0098613257907946	0.992134061200606	   
df.mm.trans1:probe10	0.0850157737741095	0.113455086684501	0.749334174945575	0.453846951440472	   
df.mm.trans1:probe11	-0.0744060881480453	0.113455086684501	-0.655819763770976	0.512103712194792	   
df.mm.trans1:probe12	-0.00289524557250278	0.113455086684501	-0.0255188696876496	0.979646619509288	   
df.mm.trans1:probe13	-0.114614286622028	0.113455086684501	-1.01021725840067	0.312656248784293	   
df.mm.trans1:probe14	-0.0436662610030496	0.113455086684501	-0.384877067032505	0.700417259982013	   
df.mm.trans1:probe15	0.0447895844949758	0.113455086684501	0.394778108270524	0.693097957436366	   
df.mm.trans1:probe16	0.0474518581481895	0.113455086684501	0.418243549362795	0.675866453083001	   
df.mm.trans1:probe17	0.0318769144497238	0.113455086684501	0.280965053055469	0.77880024107231	   
df.mm.trans1:probe18	0.0725789475506246	0.113455086684501	0.639715235972221	0.522516665664148	   
df.mm.trans1:probe19	0.0618022990154237	0.113455086684501	0.544729203612395	0.586071501711929	   
df.mm.trans1:probe20	-0.0764907555510954	0.113455086684501	-0.674194148419301	0.50035688309457	   
df.mm.trans1:probe21	0.110092144298487	0.113455086684501	0.970358822294445	0.332122150112752	   
df.mm.trans1:probe22	0.043553088873113	0.113455086684501	0.383879561030406	0.701156223154834	   
df.mm.trans2:probe2	0.0328916931612852	0.113455086684501	0.289909374030546	0.771950754794458	   
df.mm.trans2:probe3	0.0825743243157454	0.113455086684501	0.727815091670328	0.466911568162584	   
df.mm.trans2:probe4	-0.0552777984002649	0.113455086684501	-0.487221860347106	0.626216929360208	   
df.mm.trans2:probe5	-0.0839048090493215	0.113455086684501	-0.739542064629027	0.459766152324627	   
df.mm.trans2:probe6	-0.0165518168682501	0.113455086684501	-0.145888715543251	0.88404112858537	   
df.mm.trans3:probe2	0.135731286476945	0.113455086684501	1.19634377305964	0.231869983962512	   
df.mm.trans3:probe3	0.159284260279480	0.113455086684501	1.40394110951077	0.160673120750145	   
df.mm.trans3:probe4	0.195044926414783	0.113455086684501	1.71913778495598	0.0859249324333473	.  
df.mm.trans3:probe5	0.141575816194262	0.113455086684501	1.24785781168155	0.212399953536686	   
df.mm.trans3:probe6	0.140377218740213	0.113455086684501	1.23729330118602	0.216293235206840	   
df.mm.trans3:probe7	0.215842277360171	0.113455086684501	1.90244689478217	0.0574240994343627	.  
df.mm.trans3:probe8	-0.0618394965700389	0.113455086684501	-0.545057065109858	0.585846088008292	   
df.mm.trans3:probe9	-0.00258728373646107	0.113455086684501	-0.0228044754278480	0.9818111723507	   
df.mm.trans3:probe10	0.090210057322125	0.113455086684501	0.7951169044803	0.426750134842093	   
df.mm.trans3:probe11	0.156195653483059	0.113455086684501	1.37671794229387	0.168933670761775	   
df.mm.trans3:probe12	-0.0186572811903422	0.113455086684501	-0.164446405494580	0.869415778206057	   
df.mm.trans3:probe13	0.0862543285938708	0.113455086684501	0.760250872080587	0.44729900115281