chr2.14091_chr2_158152217_158159346_+_2.R 

fitVsDatCorrelation=0.931928125901029
cont.fitVsDatCorrelation=0.261742403435391

fstatistic=9162.48687722497,69,1083
cont.fstatistic=1280.10066070597,69,1083

residuals=-0.915433330294835,-0.109200809053033,0.00517186869414616,0.119306554284358,0.76365884443742
cont.residuals=-1.26065726203605,-0.388466417656908,-0.0430096937642902,0.353748725846157,1.48321893011425

predictedValues:
Include	Exclude	Both
chr2.14091_chr2_158152217_158159346_+_2.R.tl.Lung	103.278995616395	40.9323340584714	134.481449005331
chr2.14091_chr2_158152217_158159346_+_2.R.tl.cerebhem	76.8188641270733	48.5119511008017	94.109275299959
chr2.14091_chr2_158152217_158159346_+_2.R.tl.cortex	80.4304390598255	41.4984943096926	103.628846908180
chr2.14091_chr2_158152217_158159346_+_2.R.tl.heart	88.139696519774	42.6408842937977	110.015969592129
chr2.14091_chr2_158152217_158159346_+_2.R.tl.kidney	77.7744912300984	42.5497716476015	101.253247623987
chr2.14091_chr2_158152217_158159346_+_2.R.tl.liver	80.6344786612763	47.7834055598395	99.8564360020084
chr2.14091_chr2_158152217_158159346_+_2.R.tl.stomach	103.676637744583	44.8763143961181	127.094256210887
chr2.14091_chr2_158152217_158159346_+_2.R.tl.testicle	94.6670915246816	44.3843966222418	126.778947700370


diffExp=62.3466615579233,28.3069130262716,38.9319447501329,45.4988122259762,35.2247195824970,32.8510731014368,58.8003233484645,50.2826949024398
diffExpScore=0.99716908871058
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	90.1370860399286	85.8459161536425	93.6517969097636
cerebhem	98.5478482051438	68.6926878292193	97.526139490216
cortex	94.5704051184507	129.400196868933	90.1687962252207
heart	83.5374786016964	128.275713726476	91.1829619992137
kidney	97.2212727037711	90.1877222711667	96.4079600950746
liver	90.184743008057	110.728792820135	97.9298318837908
stomach	84.6630854087553	74.5431009193328	99.4042335492329
testicle	102.575793118988	78.2047267748889	100.007580028796
cont.diffExp=4.29116988628617,29.8551603759244,-34.8297917504826,-44.7382351247796,7.03355043260441,-20.5440498120782,10.1199844894225,24.3710663440995
cont.diffExpScore=6.90939842200733

cont.diffExp1.5=0,0,0,-1,0,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=0,1,0,-1,0,0,0,0
cont.diffExp1.4Score=2
cont.diffExp1.3=0,1,-1,-1,0,0,0,1
cont.diffExp1.3Score=4
cont.diffExp1.2=0,1,-1,-1,0,-1,0,1
cont.diffExp1.2Score=2.5

tran.correlation=-0.346224612916424
cont.tran.correlation=-0.383389875989045

tran.covariance=-0.00268023929850224
cont.tran.covariance=-0.00669324790188636

tran.mean=66.1623904045169
cont.tran.mean=94.2072855980366

weightedLogRatios:
wLogRatio
Lung	3.86372094190898
cerebhem	1.88986993395431
cortex	2.68434677054736
heart	2.98857104138973
kidney	2.44406644295024
liver	2.16012562127491
stomach	3.53585901719820
testicle	3.15991774205061

cont.weightedLogRatios:
wLogRatio
Lung	0.21837485469324
cerebhem	1.59159991230888
cortex	-1.47567828892084
heart	-1.98992166904938
kidney	0.340894988931523
liver	-0.944946508354584
stomach	0.556950699403648
testicle	1.21935788547160

varWeightedLogRatios=0.457515347522333
cont.varWeightedLogRatios=1.64217827969015

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.28750684221029	0.0881266231474856	37.3043550835760	1.50016573400509e-196	***
df.mm.trans1	1.15452671441969	0.075159052622477	15.3611131877735	2.52120591760300e-48	***
df.mm.trans2	0.410810807065816	0.0654671454598274	6.27506826791312	5.04510019849087e-10	***
df.mm.exp2	0.230875736200663	0.0820780008399439	2.81288206142937	0.00499870905877705	** 
df.mm.exp3	0.0243060363584346	0.0820780008399438	0.29613338665293	0.767184991996805	   
df.mm.exp4	0.0831829289147015	0.0820780008399438	1.01346192723325	0.311065933495294	   
df.mm.exp5	0.0389351365448624	0.0820780008399439	0.474367505865401	0.635333488971899	   
df.mm.exp6	0.204943161502241	0.0820780008399439	2.49693169186576	0.0126749487826447	*  
df.mm.exp7	0.152329881182151	0.0820780008399439	1.85591607523680	0.0637370091940651	.  
df.mm.exp8	0.0528813448397551	0.0820780008399439	0.64428158944656	0.519529280282399	   
df.mm.trans1:exp2	-0.5268595211842	0.0746228337464692	-7.06029903627358	2.96408439185390e-12	***
df.mm.trans2:exp2	-0.0609858686573799	0.0495306460851274	-1.23127545222335	0.218487168287451	   
df.mm.trans1:exp3	-0.274347358181635	0.0746228337464692	-3.67645323030387	0.00024809916561074	***
df.mm.trans2:exp3	-0.0105692059687529	0.0495306460851274	-0.213387201745517	0.83106512447203	   
df.mm.trans1:exp4	-0.24169393429844	0.0746228337464692	-3.23887370881136	0.00123649050014767	** 
df.mm.trans2:exp4	-0.042289725169266	0.0495306460851274	-0.853809277928325	0.393399479832793	   
df.mm.trans1:exp5	-0.322555656973966	0.0746228337464692	-4.32247933748868	1.68488083671272e-05	***
df.mm.trans2:exp5	-0.000180962718366863	0.0495306460851274	-0.00365355053224715	0.997085567775925	   
df.mm.trans1:exp6	-0.452450850135955	0.0746228337464692	-6.06316897148606	1.84090275341439e-09	***
df.mm.trans2:exp6	-0.0501850607949232	0.0495306460851274	-1.01321231927141	0.311185063178647	   
df.mm.trans1:exp7	-0.148487099895547	0.0746228337464692	-1.98983464498322	0.0468602842955644	*  
df.mm.trans2:exp7	-0.0603400591330861	0.0495306460851274	-1.21823686752199	0.223399297166941	   
df.mm.trans1:exp8	-0.139948929050428	0.0746228337464692	-1.87541697392389	0.0610042601094125	.  
df.mm.trans2:exp8	0.0280863209117289	0.0495306460851274	0.567049354927804	0.570798157542181	   
df.mm.trans1:probe2	0.252938672115799	0.0566801110637917	4.46256486391009	8.94468646772696e-06	***
df.mm.trans1:probe3	0.0659619765453552	0.0566801110637917	1.16375877371018	0.244778105165031	   
df.mm.trans1:probe4	1.15241060934208	0.0566801110637917	20.3318340016145	4.25015980408704e-78	***
df.mm.trans1:probe5	-0.0937251011262526	0.0566801110637917	-1.65358005422339	0.0985026712441439	.  
df.mm.trans1:probe6	0.627668883738587	0.0566801110637917	11.0738823894005	4.47816744996223e-27	***
df.mm.trans1:probe7	0.323039537357617	0.0566801110637917	5.69934552517101	1.54952054156077e-08	***
df.mm.trans1:probe8	0.315341013688985	0.0566801110637917	5.56352144995056	3.33068156970138e-08	***
df.mm.trans1:probe9	0.987244172242204	0.0566801110637917	17.4178235312752	4.31528956659067e-60	***
df.mm.trans1:probe10	1.1778086671768	0.0566801110637917	20.7799287099352	5.54796726655931e-81	***
df.mm.trans1:probe11	1.14345257284539	0.0566801110637917	20.1737885015516	4.35608602600610e-77	***
df.mm.trans1:probe12	1.00695195691600	0.0566801110637917	17.7655254729954	3.65059151151165e-62	***
df.mm.trans1:probe13	1.06518543160967	0.0566801110637917	18.7929312702094	2.04907767125221e-68	***
df.mm.trans1:probe14	0.274770137784888	0.0566801110637917	4.84773463968062	1.43105528777279e-06	***
df.mm.trans1:probe15	0.443689340270549	0.0566801110637917	7.82795467304555	1.17501253650993e-14	***
df.mm.trans1:probe16	0.463055502318575	0.0566801110637917	8.16962941017213	8.55808500385283e-16	***
df.mm.trans1:probe17	-0.112969193350654	0.0566801110637917	-1.99310112895704	0.0465009436823056	*  
df.mm.trans1:probe18	-0.137741295717994	0.0566801110637917	-2.43015218447562	0.0152541129835689	*  
df.mm.trans1:probe19	-0.250259119944265	0.0566801110637917	-4.41528986530401	1.10977612059999e-05	***
df.mm.trans1:probe20	-0.135041084806894	0.0566801110637917	-2.38251270635143	0.0173667086812670	*  
df.mm.trans1:probe21	-0.139359336386163	0.0566801110637917	-2.45869907046085	0.0140997537324113	*  
df.mm.trans1:probe22	-0.223603812599777	0.0566801110637917	-3.945013663578	8.49303733628897e-05	***
df.mm.trans2:probe2	0.00119748630157383	0.0566801110637917	0.0211270987141521	0.983148159758888	   
df.mm.trans2:probe3	0.0556293763527589	0.0566801110637917	0.9814620209574	0.326584151423918	   
df.mm.trans2:probe4	0.0885789354708662	0.0566801110637917	1.56278690723053	0.118394868538368	   
df.mm.trans2:probe5	0.123010166927553	0.0566801110637917	2.17025275037146	0.0302044837619337	*  
df.mm.trans2:probe6	0.0852533306285714	0.0566801110637917	1.50411368341571	0.132843652390472	   
df.mm.trans3:probe2	-0.339541997960797	0.0566801110637917	-5.99049634145306	2.84370812817408e-09	***
df.mm.trans3:probe3	0.171677306646785	0.0566801110637917	3.0288809147457	0.00251277666275079	** 
df.mm.trans3:probe4	0.132931814442621	0.0566801110637917	2.34529911723374	0.0191915615749824	*  
df.mm.trans3:probe5	0.238023847379298	0.0566801110637917	4.19942450556262	2.89574260370152e-05	***
df.mm.trans3:probe6	-0.181625870077794	0.0566801110637917	-3.20440215569409	0.00139294871118207	** 
df.mm.trans3:probe7	-0.251680280998365	0.0566801110637917	-4.44036322926585	9.90067520382984e-06	***
df.mm.trans3:probe8	0.699671584480116	0.0566801110637917	12.3442168928120	7.54265223360706e-33	***
df.mm.trans3:probe9	0.0408927887430227	0.0566801110637917	0.721466277597782	0.47077840419848	   
df.mm.trans3:probe10	-0.265698084023761	0.0566801110637917	-4.68767754750386	3.1150839369949e-06	***
df.mm.trans3:probe11	-0.377908375772028	0.0566801110637917	-6.66738947188555	4.14129659961164e-11	***
df.mm.trans3:probe12	0.123247392401649	0.0566801110637917	2.17443808927859	0.0298881705017913	*  
df.mm.trans3:probe13	-0.0418735428068555	0.0566801110637917	-0.738769596970763	0.460206987988075	   
df.mm.trans3:probe14	0.0638997961072905	0.0566801110637917	1.12737598617923	0.259833258441621	   
df.mm.trans3:probe15	0.268384907798293	0.0566801110637917	4.73508083807801	2.48009608537533e-06	***
df.mm.trans3:probe16	-0.191068523726407	0.0566801110637917	-3.37099769461223	0.000775401506595042	***
df.mm.trans3:probe17	0.405544289018583	0.0566801110637917	7.15496637898531	1.5394908990111e-12	***
df.mm.trans3:probe18	-0.250400768100865	0.0566801110637917	-4.41778894573878	1.09725040026860e-05	***
df.mm.trans3:probe19	0.425896738017838	0.0566801110637917	7.51404205151441	1.19734845490342e-13	***
df.mm.trans3:probe20	0.301264982882532	0.0566801110637917	5.31517982636744	1.29337731592416e-07	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.39124764498554	0.234540099110006	18.7228011826068	5.54609845904937e-68	***
df.mm.trans1	0.0507327900745026	0.200028221001827	0.253628162168374	0.799830977290305	   
df.mm.trans2	0.0454963281670128	0.174234189807773	0.261121701872678	0.794048302159816	   
df.mm.exp2	-0.174237573427706	0.218442302271522	-0.797636591520308	0.425256258271391	   
df.mm.exp3	0.496268970774031	0.218442302271522	2.27185378295991	0.0232908097573647	*  
df.mm.exp4	0.352307187950084	0.218442302271522	1.61281576089675	0.107075876461218	   
df.mm.exp5	0.0959919816280697	0.218442302271522	0.439438609783339	0.660431422759305	   
df.mm.exp6	0.210390858975501	0.218442302271522	0.96314155631809	0.33569148816844	   
df.mm.exp7	-0.263439620870430	0.218442302271522	-1.20599177966444	0.228084058829115	   
df.mm.exp8	-0.0296160127386654	0.218442302271522	-0.135578193558191	0.892179939999112	   
df.mm.trans1:exp2	0.263448082546163	0.198601128667731	1.32651855663381	0.184947640866187	   
df.mm.trans2:exp2	-0.048673685920945	0.131820807684265	-0.369241296393262	0.712020055761163	   
df.mm.trans1:exp3	-0.448256075653598	0.198601128667731	-2.25706711064846	0.0242024951801476	*  
df.mm.trans2:exp3	-0.0859130839664482	0.131820807684265	-0.651741447163832	0.514706260685921	   
df.mm.trans1:exp4	-0.428343500957362	0.198601128667730	-2.1568029538946	0.0312405487412005	*  
df.mm.trans2:exp4	0.0493207562402706	0.131820807684265	0.374150007928967	0.708365954285024	   
df.mm.trans1:exp5	-0.0203341288222274	0.198601128667731	-0.102386773723967	0.918468635394915	   
df.mm.trans2:exp5	-0.0466526972081647	0.131820807684265	-0.353909963288242	0.723475247591102	   
df.mm.trans1:exp6	-0.209862282158268	0.198601128667731	-1.05670236401012	0.290883098524362	   
df.mm.trans2:exp6	0.0441390280060917	0.131820807684265	0.334841128509945	0.73780977313197	   
df.mm.trans1:exp7	0.200787610312107	0.198601128667731	1.01100941197587	0.312237744937241	   
df.mm.trans2:exp7	0.122263098142270	0.131820807684265	0.927494682289556	0.353876402915689	   
df.mm.trans1:exp8	0.158886293433261	0.198601128667731	0.800027142338577	0.423870517582002	   
df.mm.trans2:exp8	-0.0636079135014117	0.131820807684265	-0.482533179843385	0.629524747182613	   
df.mm.trans1:probe2	0.219446969807376	0.150848386011794	1.45475185787018	0.146027732980381	   
df.mm.trans1:probe3	0.0890568465528275	0.150848386011794	0.590373214506017	0.555063629928338	   
df.mm.trans1:probe4	0.0372113340513492	0.150848386011794	0.246680359234601	0.805202357202286	   
df.mm.trans1:probe5	0.311690323705648	0.150848386011794	2.06624897982852	0.0390423138588782	*  
df.mm.trans1:probe6	0.0793480516594497	0.150848386011794	0.526011936602661	0.598987606171361	   
df.mm.trans1:probe7	-0.0175513152110708	0.150848386011794	-0.116350699368427	0.90739617713102	   
df.mm.trans1:probe8	0.101740698455878	0.150848386011794	0.674456659071734	0.500164972180673	   
df.mm.trans1:probe9	0.0244532277867053	0.150848386011794	0.162104669683329	0.871253667083578	   
df.mm.trans1:probe10	0.0703973231916654	0.150848386011794	0.466676011940633	0.640825555875045	   
df.mm.trans1:probe11	0.118061859278820	0.150848386011794	0.78265245257307	0.434002325554942	   
df.mm.trans1:probe12	-0.0183212156680501	0.150848386011794	-0.121454502447362	0.903353580141816	   
df.mm.trans1:probe13	0.206459882900071	0.150848386011794	1.36865821609738	0.171389962065792	   
df.mm.trans1:probe14	0.136438845585456	0.150848386011794	0.904476668214325	0.365943852953962	   
df.mm.trans1:probe15	0.322624270309982	0.150848386011794	2.1387319999881	0.0326805629637972	*  
df.mm.trans1:probe16	0.122290859980601	0.150848386011794	0.810687228506637	0.417723418549108	   
df.mm.trans1:probe17	-0.0653976629083385	0.150848386011794	-0.43353240056029	0.664714370371713	   
df.mm.trans1:probe18	0.141408556564766	0.150848386011794	0.93742174048657	0.348750660068804	   
df.mm.trans1:probe19	0.123288981315357	0.150848386011794	0.817303947194483	0.413934510520957	   
df.mm.trans1:probe20	0.18309520690649	0.150848386011794	1.21376974422633	0.225100291337824	   
df.mm.trans1:probe21	0.234785351576334	0.150848386011794	1.55643263931227	0.119897409411800	   
df.mm.trans1:probe22	0.0722242987164355	0.150848386011794	0.47878734818408	0.632186565704916	   
df.mm.trans2:probe2	0.0402141885470283	0.150848386011794	0.266586800231884	0.789838068222505	   
df.mm.trans2:probe3	0.190218769573391	0.150848386011794	1.26099307127169	0.207582917257726	   
df.mm.trans2:probe4	0.0371710790551624	0.150848386011794	0.246413501913478	0.805408851342982	   
df.mm.trans2:probe5	0.121493214930611	0.150848386011794	0.80539950172958	0.420765968045067	   
df.mm.trans2:probe6	0.0219638789915681	0.150848386011794	0.145602346649243	0.884262409572869	   
df.mm.trans3:probe2	0.0645781170281378	0.150848386011794	0.428099489397842	0.668663807231444	   
df.mm.trans3:probe3	-0.0575942879562269	0.150848386011794	-0.381802480483442	0.702682778140553	   
df.mm.trans3:probe4	-0.119345854479964	0.150848386011794	-0.791164278487097	0.429021361631509	   
df.mm.trans3:probe5	0.142461399012837	0.150848386011794	0.944401214884048	0.345175298709747	   
df.mm.trans3:probe6	0.115760885139523	0.150848386011794	0.76739889766187	0.443011650546031	   
df.mm.trans3:probe7	-0.0155880858439605	0.150848386011794	-0.103336112875226	0.917715346520946	   
df.mm.trans3:probe8	0.0111266712326986	0.150848386011795	0.0737606250015076	0.941214479082314	   
df.mm.trans3:probe9	0.216464818199218	0.150848386011794	1.43498265988933	0.151580752136244	   
df.mm.trans3:probe10	-0.000732967878115344	0.150848386011794	-0.00485897063597376	0.996124012450704	   
df.mm.trans3:probe11	0.208600391231157	0.150848386011794	1.38284801545604	0.166996518818006	   
df.mm.trans3:probe12	0.0319735022922657	0.150848386011794	0.211957868013024	0.83217978614618	   
df.mm.trans3:probe13	0.0489849000858213	0.150848386011794	0.324729361585555	0.7454486238576	   
df.mm.trans3:probe14	0.143221096134797	0.150848386011794	0.94943737829319	0.342610023209192	   
df.mm.trans3:probe15	0.0731489483292857	0.150848386011794	0.484917010140012	0.62783328081745	   
df.mm.trans3:probe16	-0.203096838900123	0.150848386011794	-1.34636401667727	0.178466866455980	   
df.mm.trans3:probe17	0.0526350692108751	0.150848386011794	0.348926963041949	0.727211967170906	   
df.mm.trans3:probe18	0.0464799528343671	0.150848386011794	0.308123633690936	0.758047509615256	   
df.mm.trans3:probe19	0.141398419607916	0.150848386011794	0.937354540849118	0.348785198409141	   
df.mm.trans3:probe20	0.141660924381854	0.150848386011794	0.939094730325967	0.3478915013326