chr11.4568_chr11_50549795_50561431_+_2.R 

fitVsDatCorrelation=0.812199755525664
cont.fitVsDatCorrelation=0.204065416584819

fstatistic=6748.75203496379,65,991
cont.fstatistic=2386.78284114405,65,991

residuals=-0.633563207800842,-0.109575689030125,-0.00653013740132383,0.106140779028293,0.963982321085596
cont.residuals=-0.752470435373994,-0.241612124068326,-0.05965358011146,0.19463794348095,1.37947905913783

predictedValues:
Include	Exclude	Both
chr11.4568_chr11_50549795_50561431_+_2.R.tl.Lung	73.7401087765806	63.3154697709183	92.3561749912154
chr11.4568_chr11_50549795_50561431_+_2.R.tl.cerebhem	85.7272986998589	81.2854049397536	84.3828756412157
chr11.4568_chr11_50549795_50561431_+_2.R.tl.cortex	113.855546073484	62.8924168502655	112.634854786210
chr11.4568_chr11_50549795_50561431_+_2.R.tl.heart	79.163799847159	62.0734289502574	88.8625312781751
chr11.4568_chr11_50549795_50561431_+_2.R.tl.kidney	64.0838568845486	60.8257183799162	84.7584695985826
chr11.4568_chr11_50549795_50561431_+_2.R.tl.liver	60.7834634871806	58.9970781495262	75.7022241833108
chr11.4568_chr11_50549795_50561431_+_2.R.tl.stomach	65.9444143578216	95.91557690381	74.0252847966189
chr11.4568_chr11_50549795_50561431_+_2.R.tl.testicle	67.2962157596645	63.2138916257388	77.9777681573766


diffExp=10.4246390056623,4.44189376010529,50.9631292232187,17.0903708969016,3.25813850463243,1.78638533765443,-29.9711625459883,4.08232413392572
diffExpScore=1.93446934360033
diffExp1.5=0,0,1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,1,0,0,0,-1,0
diffExp1.4Score=2
diffExp1.3=0,0,1,0,0,0,-1,0
diffExp1.3Score=2
diffExp1.2=0,0,1,1,0,0,-1,0
diffExp1.2Score=1.5

cont.predictedValues:
Include	Exclude	Both
Lung	87.8302780779498	81.4438248494403	87.240393688081
cerebhem	84.7657476764282	80.7561956488669	84.2212927871216
cortex	91.103671238807	78.595825175335	80.8322797698714
heart	87.5638693114815	90.4836080259083	77.1249950325793
kidney	87.2244296472967	78.863612204734	80.4667015999383
liver	88.2435022808222	90.0896478944628	78.8447311558763
stomach	82.032160790995	85.2382892147098	90.9236217818655
testicle	87.6584612521265	81.7531616023332	92.8357611534246
cont.diffExp=6.38645322850947,4.00955202756134,12.5078460634721,-2.91973871442683,8.36081744256278,-1.84614561364062,-3.20612842371477,5.90529964979335
cont.diffExpScore=1.49486878091226

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=-0.0571931137349844
cont.tran.correlation=-0.163580823794007

tran.covariance=-0.000215721232087225
cont.tran.covariance=-0.000296359699837805

tran.mean=72.4446055910302
cont.tran.mean=85.227892805731

weightedLogRatios:
wLogRatio
Lung	0.643861729694469
cerebhem	0.235408450988133
cortex	2.63408045417115
heart	1.03358486954987
kidney	0.215716606583170
liver	0.122075763285131
stomach	-1.63954816499268
testicle	0.261447287162375

cont.weightedLogRatios:
wLogRatio
Lung	0.335011269974778
cerebhem	0.213969155315885
cortex	0.655425090406796
heart	-0.147232711286512
kidney	0.445187926645069
liver	-0.0929757102644222
stomach	-0.169700790266056
testicle	0.309562549122576

varWeightedLogRatios=1.39392964164027
cont.varWeightedLogRatios=0.091531182225555

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.28103796409393	0.0984840020275832	33.3154410517861	6.9612323201553e-164	***
df.mm.trans1	0.862645538975975	0.0842717364489865	10.2364751852262	1.90530568188947e-23	***
df.mm.trans2	0.825981982237851	0.0736875378170229	11.2092493073780	1.53781836545829e-27	***
df.mm.exp2	0.490749320536266	0.09304789252927	5.27415836293006	1.63754862257529e-07	***
df.mm.exp3	0.229180903931738	0.09304789252927	2.46304239356786	0.0139454543548355	*  
df.mm.exp4	0.0897225747335888	0.0930478925292699	0.964262298636855	0.335149673446431	   
df.mm.exp5	-0.0946244746953293	0.0930478925292699	-1.01694377081741	0.309428385455686	   
df.mm.exp6	-0.0650258378103268	0.0930478925292699	-0.698842671690514	0.484814328502686	   
df.mm.exp7	0.524849870599996	0.0930478925292699	5.64064221481314	2.20964378064460e-08	***
df.mm.exp8	0.0761803385106882	0.0930478925292699	0.818721804867577	0.413141982422408	   
df.mm.trans1:exp2	-0.340124875675239	0.0849992757291969	-4.00150322173166	6.76292772846116e-05	***
df.mm.trans2:exp2	-0.240912528592946	0.0583391326248513	-4.12951851962094	3.94151412627327e-05	***
df.mm.trans1:exp3	0.205202733314509	0.0849992757291969	2.41417037444265	0.0159514555810407	*  
df.mm.trans2:exp3	-0.235884993770823	0.0583391326248513	-4.04334077586783	5.6782419856912e-05	***
df.mm.trans1:exp4	-0.0187503209812437	0.0849992757291969	-0.220593891187747	0.825454095239968	   
df.mm.trans2:exp4	-0.109534240014385	0.0583391326248513	-1.87754317018634	0.0607372119892196	.  
df.mm.trans1:exp5	-0.0457299037121034	0.0849992757291969	-0.538003451438768	0.590695467235549	   
df.mm.trans2:exp5	0.0545074864396125	0.0583391326248513	0.934321166379383	0.350365845770711	   
df.mm.trans1:exp6	-0.128203260271752	0.0849992757291969	-1.50828650211327	0.131799938558072	   
df.mm.trans2:exp6	-0.00561592985801146	0.0583391326248512	-0.0962635131057671	0.92333075165039	   
df.mm.trans1:exp7	-0.636584558070175	0.0849992757291969	-7.48929390996576	1.52914778845725e-13	***
df.mm.trans2:exp7	-0.109511160747918	0.0583391326248513	-1.87714756494800	0.0607914570283855	.  
df.mm.trans1:exp8	-0.167623200808044	0.0849992757291969	-1.97205446011191	0.0488811302039183	*  
df.mm.trans2:exp8	-0.077785944764926	0.0583391326248513	-1.33334078285200	0.182726397813402	   
df.mm.trans1:probe2	-0.146764183674939	0.0627761254900215	-2.33789808672196	0.0195907250236448	*  
df.mm.trans1:probe3	-0.115572941121545	0.0627761254900215	-1.84103335813414	0.0659154438181287	.  
df.mm.trans1:probe4	-0.063834882899502	0.0627761254900215	-1.01686560617139	0.309465554428907	   
df.mm.trans1:probe5	0.539176495022892	0.0627761254900215	8.58887818918669	3.36725661458298e-17	***
df.mm.trans1:probe6	0.232604914631721	0.0627761254900215	3.70530855187446	0.000222812437326276	***
df.mm.trans1:probe7	0.172435507043824	0.0627761254900216	2.74683258480539	0.00612647003401675	** 
df.mm.trans1:probe8	-0.00220232754431677	0.0627761254900215	-0.0350822470664717	0.97202122238373	   
df.mm.trans1:probe9	-0.0160952362613795	0.0627761254900215	-0.256391042545911	0.797702117903028	   
df.mm.trans1:probe10	0.396683576667614	0.0627761254900215	6.31901974789234	3.97141899346813e-10	***
df.mm.trans1:probe11	0.501224309423165	0.0627761254900215	7.9843141880879	3.89608900502796e-15	***
df.mm.trans1:probe12	0.235332218079758	0.0627761254900215	3.7487534670671	0.000187996311326910	***
df.mm.trans1:probe13	0.261569588309267	0.0627761254900215	4.1667048781283	3.36005320024140e-05	***
df.mm.trans1:probe14	0.238737219747838	0.0627761254900215	3.80299385927834	0.000151698401966480	***
df.mm.trans1:probe15	0.302308090698660	0.0627761254900215	4.81565385469215	1.69607501882143e-06	***
df.mm.trans1:probe16	0.288370449867462	0.0627761254900215	4.59363249350742	4.91679945950232e-06	***
df.mm.trans1:probe17	0.294612494710955	0.0627761254900215	4.69306591337474	3.06933962931794e-06	***
df.mm.trans1:probe18	0.63367943380767	0.0627761254900215	10.0942743576679	7.14258820375626e-23	***
df.mm.trans1:probe19	0.565031137077258	0.0627761254900215	9.00073288478232	1.12137921208719e-18	***
df.mm.trans1:probe20	0.565639986358857	0.0627761254900215	9.0104316241812	1.03339887534611e-18	***
df.mm.trans1:probe21	0.545592803926756	0.0627761254900215	8.69108756980358	1.46546035459593e-17	***
df.mm.trans1:probe22	0.532279211252931	0.0627761254900215	8.47900706037581	8.15966736501493e-17	***
df.mm.trans2:probe2	0.238381800090100	0.0627761254900215	3.7973321581943	0.000155152998712745	***
df.mm.trans2:probe3	0.226636425065381	0.0627761254900215	3.61023276438756	0.000321241930758332	***
df.mm.trans2:probe4	0.196116481271884	0.0627761254900215	3.12406157183207	0.00183555442066813	** 
df.mm.trans2:probe5	0.142861270801475	0.0627761254900215	2.27572615682029	0.0230751396725863	*  
df.mm.trans2:probe6	0.100418327556132	0.0627761254900215	1.59962608033358	0.110000296787720	   
df.mm.trans3:probe2	-0.510126675286313	0.0627761254900215	-8.1261255183294	1.31237089905968e-15	***
df.mm.trans3:probe3	-0.494357229836088	0.0627761254900215	-7.8749242005174	8.91917546257453e-15	***
df.mm.trans3:probe4	-0.950430240700029	0.0627761254900215	-15.1399952335558	9.76135428704897e-47	***
df.mm.trans3:probe5	0.154700034779223	0.0627761254900215	2.46431320142262	0.0138964105542898	*  
df.mm.trans3:probe6	-0.367892936095171	0.0627761254900215	-5.86039570335778	6.28129372336136e-09	***
df.mm.trans3:probe7	-0.409551312610398	0.0627761254900215	-6.52399792777109	1.09001022065779e-10	***
df.mm.trans3:probe8	-0.440425708720067	0.0627761254900215	-7.01581541202434	4.23149779478661e-12	***
df.mm.trans3:probe9	-0.616768949706282	0.0627761254900215	-9.82489672454092	8.38383141328612e-22	***
df.mm.trans3:probe10	-0.637620688310527	0.0627761254900215	-10.1570570552634	3.9926690253615e-23	***
df.mm.trans3:probe11	-0.612279401205629	0.0627761254900215	-9.75337991037616	1.59774969641241e-21	***
df.mm.trans3:probe12	-0.120620708029643	0.0627761254900215	-1.92144238097039	0.0549625251906042	.  
df.mm.trans3:probe13	-0.382995053295648	0.0627761254900215	-6.10096673386646	1.50997530427373e-09	***
df.mm.trans3:probe14	-0.775352742794465	0.0627761254900215	-12.3510767308777	1.06574902444417e-32	***
df.mm.trans3:probe15	-0.320978000963893	0.0627761254900215	-5.11305848295645	3.80362810981629e-07	***
df.mm.trans3:probe16	-0.619507040124496	0.0627761254900215	-9.86851347209965	5.64714906156911e-22	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.485537325835	0.165264017849684	27.141645133636	9.57440231663913e-122	***
df.mm.trans1	0.0488881026382007	0.141414701575881	0.345707356402177	0.729636027456703	   
df.mm.trans2	-0.0777716361939835	0.123653571284410	-0.628947756107299	0.529528203313838	   
df.mm.exp2	-0.0087739019196031	0.156141792120977	-0.0561918868768023	0.95520027112147	   
df.mm.exp3	0.0772879408748458	0.156141792120977	0.494985614197153	0.620719999134855	   
df.mm.exp4	0.225457394840440	0.156141792120977	1.44392729056010	0.149075483465609	   
df.mm.exp5	0.0417085698051165	0.156141792120977	0.267119835366058	0.789432472646837	   
df.mm.exp6	0.206772479830359	0.156141792120977	1.32426096192206	0.185721723903154	   
df.mm.exp7	-0.0641100779941723	0.156141792120977	-0.410588844429944	0.68146280207331	   
df.mm.exp8	-0.0603316554442991	0.156141792120977	-0.386390181800622	0.699290664127592	   
df.mm.trans1:exp2	-0.0267408498068329	0.142635570571004	-0.187476726175546	0.85132524668001	   
df.mm.trans2:exp2	0.000295070437814617	0.0978977220355867	0.00301406847553977	0.997595731541482	   
df.mm.trans1:exp3	-0.040696132438969	0.142635570571004	-0.28531545305321	0.775462093872933	   
df.mm.trans2:exp3	-0.112882874610947	0.0978977220355867	-1.15306947152369	0.249159911268414	   
df.mm.trans1:exp4	-0.228495226778521	0.142635570571004	-1.60195122341363	0.109485076839952	   
df.mm.trans2:exp4	-0.120202204268540	0.0978977220355867	-1.22783453760901	0.219800639974718	   
df.mm.trans1:exp5	-0.0486304156380243	0.142635570571004	-0.340941712108315	0.733219729845384	   
df.mm.trans2:exp5	-0.073902154063187	0.0978977220355867	-0.754891457395943	0.450493469690901	   
df.mm.trans1:exp6	-0.202078709290624	0.142635570571004	-1.41674835023028	0.156870784790708	   
df.mm.trans2:exp6	-0.105880734493018	0.0978977220355867	-1.08154441483868	0.279718125345937	   
df.mm.trans1:exp7	-0.00418484088256029	0.142635570571004	-0.0293393917506510	0.976599817645172	   
df.mm.trans2:exp7	0.109647297863261	0.0978977220355867	1.12001888893189	0.262977079115742	   
df.mm.trans1:exp8	0.058373502671878	0.142635570571004	0.409249266772624	0.682445175502573	   
df.mm.trans2:exp8	0.0641226215654978	0.0978977220355867	0.654996053352382	0.512622295096167	   
df.mm.trans1:probe2	-0.139123003518929	0.105343350289636	-1.32066241615078	0.186918849350511	   
df.mm.trans1:probe3	-0.119442825769797	0.105343350289636	-1.13384305171039	0.257134595376626	   
df.mm.trans1:probe4	-0.159980445586062	0.105343350289636	-1.51865727780827	0.129167731657914	   
df.mm.trans1:probe5	-0.0331829591281700	0.105343350289636	-0.314998137394863	0.752829380533416	   
df.mm.trans1:probe6	-0.158918745874991	0.105343350289636	-1.50857880861063	0.13172518235985	   
df.mm.trans1:probe7	-0.146177418156601	0.105343350289636	-1.38762833871046	0.165562175725011	   
df.mm.trans1:probe8	-0.00469815418520626	0.105343350289636	-0.0445984883933247	0.964436332231754	   
df.mm.trans1:probe9	-0.0557877506992698	0.105343350289636	-0.529580182763167	0.596521650449259	   
df.mm.trans1:probe10	-0.137401961186955	0.105343350289636	-1.30432496032427	0.192425652818411	   
df.mm.trans1:probe11	-0.206324981197238	0.105343350289636	-1.95859520918937	0.05044037650244	.  
df.mm.trans1:probe12	-0.114782825567135	0.105343350289636	-1.08960675022719	0.276151289806086	   
df.mm.trans1:probe13	-0.154597401235434	0.105343350289636	-1.46755728586927	0.14254180721719	   
df.mm.trans1:probe14	-0.0854209317549086	0.105343350289636	-0.810881099946492	0.417628648252882	   
df.mm.trans1:probe15	-0.172790981857514	0.105343350289636	-1.64026472845637	0.101267480386459	   
df.mm.trans1:probe16	-0.096035234565637	0.105343350289636	-0.911640215557918	0.362179846229163	   
df.mm.trans1:probe17	0.0207547393701299	0.105343350289636	0.197019928766893	0.843852341491692	   
df.mm.trans1:probe18	-0.025307139198463	0.105343350289636	-0.240234804844182	0.810197917689934	   
df.mm.trans1:probe19	-0.087797952170694	0.105343350289636	-0.833445603631346	0.404794293164257	   
df.mm.trans1:probe20	-0.164613728589394	0.105343350289636	-1.56263995911272	0.118456565286025	   
df.mm.trans1:probe21	-0.108714653026703	0.105343350289636	-1.03200299523223	0.302322501530891	   
df.mm.trans1:probe22	-0.0923827554355129	0.105343350289636	-0.876968078018322	0.380716513973303	   
df.mm.trans2:probe2	-0.0153791484699342	0.105343350289636	-0.145990690704729	0.883958427196333	   
df.mm.trans2:probe3	-0.0479029916340127	0.105343350289636	-0.454731993071285	0.649401653037049	   
df.mm.trans2:probe4	-0.0898702152162223	0.105343350289636	-0.85311711625963	0.393800505042615	   
df.mm.trans2:probe5	-0.0252073849439429	0.105343350289636	-0.239287860834467	0.810931856302803	   
df.mm.trans2:probe6	0.00561194090765875	0.105343350289636	0.0532728538842653	0.957525245669396	   
df.mm.trans3:probe2	-0.0820179025913541	0.105343350289636	-0.778576933103516	0.436414829622928	   
df.mm.trans3:probe3	-0.0259423326021204	0.105343350289636	-0.246264548552835	0.805528449041874	   
df.mm.trans3:probe4	0.0315949001586052	0.105343350289636	0.299923061794947	0.764298740241911	   
df.mm.trans3:probe5	0.0465597434076069	0.105343350289636	0.441980849095775	0.658599495975557	   
df.mm.trans3:probe6	-0.00116886507412936	0.105343350289636	-0.0110957651424188	0.991149275199932	   
df.mm.trans3:probe7	0.0547379823977049	0.105343350289636	0.519614975669615	0.603447994189912	   
df.mm.trans3:probe8	0.116174920146146	0.105343350289636	1.10282158130275	0.270372392188839	   
df.mm.trans3:probe9	0.0774995732583895	0.105343350289636	0.735685480339371	0.462096209723719	   
df.mm.trans3:probe10	-0.0534756614266983	0.105343350289636	-0.507632055366283	0.611824360554773	   
df.mm.trans3:probe11	-0.0439202503579007	0.105343350289636	-0.416924753552496	0.676823741037965	   
df.mm.trans3:probe12	0.0300258414266526	0.105343350289636	0.285028351045397	0.775681976323232	   
df.mm.trans3:probe13	0.064864568245832	0.105343350289636	0.6157443072343	0.538204676831837	   
df.mm.trans3:probe14	-0.0319498484555408	0.105343350289636	-0.303292503681498	0.761730616346464	   
df.mm.trans3:probe15	0.0576225221901622	0.105343350289636	0.54699724312671	0.584503774007673	   
df.mm.trans3:probe16	-0.0483866027945692	0.105343350289636	-0.459322801691163	0.646103111310037