chr1.779_chr1_128971534_128976458_+_2.R 

fitVsDatCorrelation=0.897967217708916
cont.fitVsDatCorrelation=0.261270533528889

fstatistic=5503.80989269451,54,738
cont.fstatistic=1133.10052861383,54,738

residuals=-0.793245122001247,-0.103020302635932,-0.00635406792445297,0.0943039113884193,0.935723714539177
cont.residuals=-0.82994608745322,-0.328099887644478,-0.115316242939219,0.216760990789348,2.11510320290146

predictedValues:
Include	Exclude	Both
chr1.779_chr1_128971534_128976458_+_2.R.tl.Lung	63.2058013866942	50.2399890333932	99.901300513238
chr1.779_chr1_128971534_128976458_+_2.R.tl.cerebhem	75.6958208896362	47.2877062660654	97.494183808364
chr1.779_chr1_128971534_128976458_+_2.R.tl.cortex	147.539411224969	54.8850550037306	321.146009155957
chr1.779_chr1_128971534_128976458_+_2.R.tl.heart	79.2266536618574	54.1320249825617	114.182259218306
chr1.779_chr1_128971534_128976458_+_2.R.tl.kidney	59.0194139354476	50.8122924344902	92.2059226750125
chr1.779_chr1_128971534_128976458_+_2.R.tl.liver	60.9546892131454	53.9788785421196	86.1082974909128
chr1.779_chr1_128971534_128976458_+_2.R.tl.stomach	64.3353413071202	51.9807993783892	98.9351654047975
chr1.779_chr1_128971534_128976458_+_2.R.tl.testicle	66.7115255394501	50.422749306655	102.036268981607


diffExp=12.9658123533010,28.4081146235708,92.6543562212382,25.0946286792957,8.2071215009574,6.97581067102573,12.3545419287310,16.2887762327951
diffExpScore=0.99509681731879
diffExp1.5=0,1,1,0,0,0,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=0,1,1,1,0,0,0,0
diffExp1.4Score=0.75
diffExp1.3=0,1,1,1,0,0,0,1
diffExp1.3Score=0.8
diffExp1.2=1,1,1,1,0,0,1,1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	77.6651160925769	69.6960091333694	67.773543649695
cerebhem	69.7590902078655	83.62427623352	67.8830419730057
cortex	68.3487718656595	68.8212419110807	72.7742266750405
heart	71.7543109151502	74.0826973200975	61.6401433314576
kidney	75.2041173086225	87.8652769367065	90.4389522984255
liver	80.0247367246243	85.2577615523377	83.8792781457816
stomach	76.1367008421548	64.4271725849831	61.0673449795736
testicle	72.8250910969267	76.104295968221	72.3903948833472
cont.diffExp=7.96910695920751,-13.8651860256545,-0.472470045421204,-2.32838640494737,-12.6611596280840,-5.23302482771334,11.7095282571717,-3.27920487129434
cont.diffExpScore=3.00186199248689

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=0.46882405910978
cont.tran.correlation=0.144762479724525

tran.covariance=0.00632044053483861
cont.tran.covariance=0.000774489184539497

tran.mean=64.4017595066078
cont.tran.mean=75.0997916683685

weightedLogRatios:
wLogRatio
Lung	0.925594876784291
cerebhem	1.92493236644433
cortex	4.449516014995
heart	1.59281887991308
kidney	0.599362088067565
liver	0.492151159274408
stomach	0.865198054798184
testicle	1.13665206153695

cont.weightedLogRatios:
wLogRatio
Lung	0.465344715981675
cerebhem	-0.786000587631307
cortex	-0.0291265318801908
heart	-0.136972070903932
kidney	-0.684323986306502
liver	-0.279598067636676
stomach	0.709567007486668
testicle	-0.189833974102652

varWeightedLogRatios=1.65437832569828
cont.varWeightedLogRatios=0.261659575879282

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.39035934663554	0.110165197389866	30.7752305352599	1.90079520370737e-134	***
df.mm.trans1	0.839580684593747	0.0970457297923185	8.65139235276484	3.16013380571079e-17	***
df.mm.trans2	0.532136508086721	0.0875673254845503	6.07688433033857	1.96307509670307e-09	***
df.mm.exp2	0.144155890447671	0.116613612599972	1.23618407177023	0.216783444723957	   
df.mm.exp3	-0.231584143948705	0.116613612599972	-1.98591003902026	0.0474128972871186	*  
df.mm.exp4	0.166918120073886	0.116613612599972	1.43137766125535	0.152745335144662	   
df.mm.exp5	0.0229556849596496	0.116613612599972	0.196852532460306	0.843997138673898	   
df.mm.exp6	0.184093151944543	0.116613612599972	1.57865919629855	0.114842750027243	   
df.mm.exp7	0.0614940875640106	0.116613612599972	0.527331982887435	0.598121552832863	   
df.mm.exp8	0.0364671635367568	0.116613612599972	0.312717895652994	0.75458334321646	   
df.mm.trans1:exp2	0.0361709712250345	0.109994882630885	0.328842309386473	0.74236817334319	   
df.mm.trans2:exp2	-0.204716842416081	0.0899958130616336	-2.27473740668225	0.0232077929006643	*  
df.mm.trans1:exp3	1.07928338775072	0.109994882630885	9.81212363644693	1.91173937948172e-21	***
df.mm.trans2:exp3	0.320013929375196	0.0899958130616335	3.55587575119784	0.00040075347640799	***
df.mm.trans1:exp4	0.0589985672322204	0.109994882630886	0.536375564217877	0.591860652588678	   
df.mm.trans2:exp4	-0.0923034542233885	0.0899958130616335	-1.02564165024182	0.305396581101713	   
df.mm.trans1:exp5	-0.0914853364588333	0.109994882630885	-0.831723569957655	0.405834022971583	   
df.mm.trans2:exp5	-0.0116286864655936	0.0899958130616335	-0.129213638612606	0.897223811155365	   
df.mm.trans1:exp6	-0.220358454601437	0.109994882630885	-2.00335187720417	0.0455047027027373	*  
df.mm.trans2:exp6	-0.112311623879174	0.0899958130616336	-1.24796498924075	0.212439683814837	   
df.mm.trans1:exp7	-0.0437810668197998	0.109994882630885	-0.39802821524632	0.690724499533587	   
df.mm.trans2:exp7	-0.0274309837682959	0.0899958130616335	-0.304802888435597	0.760602216863085	   
df.mm.trans1:exp8	0.0175144801173435	0.109994882630885	0.159229954143572	0.873531270334861	   
df.mm.trans2:exp8	-0.0328360190420478	0.0899958130616336	-0.364861629946718	0.715319227272197	   
df.mm.trans1:probe2	-0.161645025718464	0.0642231749934862	-2.51692672831667	0.0120491913683534	*  
df.mm.trans1:probe3	-0.329276943141017	0.0642231749934862	-5.12707357078521	3.76319647458903e-07	***
df.mm.trans1:probe4	-0.372559511523017	0.0642231749934862	-5.80101359923118	9.77812360084063e-09	***
df.mm.trans1:probe5	-0.20178484702637	0.0642231749934862	-3.14193197466235	0.00174544005043052	** 
df.mm.trans1:probe6	-0.221368207769830	0.0642231749934862	-3.44685867355953	0.000599269877433521	***
df.mm.trans1:probe7	-0.119085399447843	0.0642231749934862	-1.85424341695845	0.0641030957811028	.  
df.mm.trans1:probe8	-0.379326441015764	0.0642231749934862	-5.90637945031894	5.33589490000125e-09	***
df.mm.trans1:probe9	0.270881994101323	0.0642231749934862	4.21782314762228	2.77343407040345e-05	***
df.mm.trans1:probe10	0.183773274337513	0.0642231749934862	2.86147912114516	0.00433599090350004	** 
df.mm.trans1:probe11	-0.422999027495046	0.0642231749934862	-6.58639233482226	8.56203451640087e-11	***
df.mm.trans1:probe12	-0.286265653509934	0.0642231749934862	-4.45735754326952	9.58670677363803e-06	***
df.mm.trans1:probe13	-0.412675165378184	0.0642231749934862	-6.4256425413418	2.35414322879001e-10	***
df.mm.trans1:probe14	-0.408912778909655	0.0642231749934862	-6.36705953810488	3.38545748324216e-10	***
df.mm.trans1:probe15	-0.425582728474821	0.0642231749934862	-6.6266223760813	6.62533020356507e-11	***
df.mm.trans1:probe16	-0.427864042889486	0.0642231749934862	-6.66214404586634	5.27709839641983e-11	***
df.mm.trans1:probe17	-0.0559180169538934	0.0642231749934862	-0.870682848668955	0.384210468738853	   
df.mm.trans1:probe18	0.068586066113883	0.0642231749934862	1.06793328297518	0.285899807480973	   
df.mm.trans1:probe19	0.519364238542891	0.0642231749934862	8.08686644027747	2.50917827325867e-15	***
df.mm.trans1:probe20	0.393250839974734	0.0642231749934862	6.12319213453118	1.4899257170552e-09	***
df.mm.trans1:probe21	0.295122481083623	0.0642231749934862	4.59526457721151	5.0825425001948e-06	***
df.mm.trans1:probe22	0.238598509806562	0.0642231749934862	3.71514659358965	0.000218420742468107	***
df.mm.trans2:probe2	0.0153844317307657	0.0642231749934862	0.239546421246319	0.810748418307991	   
df.mm.trans2:probe3	0.0101061306116765	0.0642231749934862	0.157359560823666	0.875004523677217	   
df.mm.trans2:probe4	-0.0220888483179858	0.0642231749934862	-0.343938902432434	0.730990204631737	   
df.mm.trans2:probe5	-0.0362657686896809	0.0642231749934862	-0.564683522628072	0.572460633649793	   
df.mm.trans2:probe6	-0.0296660046485937	0.0642231749934862	-0.461920555182807	0.644274425909646	   
df.mm.trans3:probe2	-0.289697719473092	0.0642231749934862	-4.51079722393784	7.51174565023846e-06	***
df.mm.trans3:probe3	-0.0796428563544703	0.0642231749934862	-1.24009528277834	0.215334290912727	   
df.mm.trans3:probe4	-0.415775421112556	0.0642231749934862	-6.4739157034003	1.74137786843435e-10	***
df.mm.trans3:probe5	-0.00435318103839557	0.0642231749934862	-0.0677820901697415	0.945977460315697	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.55521052739715	0.241644566841652	18.8508708759098	5.25377209202633e-65	***
df.mm.trans1	-0.124469883214894	0.212867347357506	-0.584729808305684	0.558908121620694	   
df.mm.trans2	-0.290643839304397	0.192076707867295	-1.51316545629886	0.130665744948501	   
df.mm.exp2	0.0732179964896425	0.255789002082365	0.286243723903603	0.774771789617514	   
df.mm.exp3	-0.211603174087129	0.255789002082365	-0.827256732558784	0.408358963856334	   
df.mm.exp4	0.0767392486670336	0.255789002082365	0.300009961500703	0.764254039354024	   
df.mm.exp5	-0.0890417359066324	0.255789002082365	-0.348106193705547	0.727859702403189	   
df.mm.exp6	0.0182590009140523	0.255789002082365	0.0713830569938767	0.94311223329136	   
df.mm.exp7	0.00571127583488403	0.255789002082365	0.0223280742658552	0.982192289883043	   
df.mm.exp8	-0.0422857060372216	0.255789002082365	-0.165314793415573	0.868741488158825	   
df.mm.trans1:exp2	-0.180576458944050	0.241270985736769	-0.74843835197433	0.45443424501709	   
df.mm.trans2:exp2	0.108972808659400	0.197403533784629	0.55203068845916	0.581094452813989	   
df.mm.trans1:exp3	0.0838205685554664	0.241270985736769	0.34741255066167	0.728380458659141	   
df.mm.trans2:exp3	0.198972561724616	0.197403533784629	1.00794832751930	0.313809625918630	   
df.mm.trans1:exp4	-0.155897513616103	0.241270985736769	-0.64615110325031	0.518382373625579	   
df.mm.trans2:exp4	-0.0157003064398326	0.197403533784629	-0.0795340698255277	0.936629394580302	   
df.mm.trans1:exp5	0.0568415165830298	0.241270985736769	0.235592010408765	0.813814634156553	   
df.mm.trans2:exp5	0.320703375035412	0.197403533784629	1.62460807507785	0.104673070087265	   
df.mm.trans1:exp6	0.0116705947973255	0.241270985736769	0.0483713147757364	0.961433407166158	   
df.mm.trans2:exp6	0.183277097351161	0.197403533784629	0.928438786466304	0.353483561061284	   
df.mm.trans1:exp7	-0.0255870561972942	0.241270985736769	-0.106051111446986	0.915570618776296	   
df.mm.trans2:exp7	-0.0843188555208052	0.197403533784629	-0.427139544587883	0.66940227835157	   
df.mm.trans1:exp8	-0.0220599404412592	0.241270985736769	-0.0914322141715251	0.927173977009857	   
df.mm.trans2:exp8	0.130247362574421	0.197403533784629	0.659802588521661	0.509586372820054	   
df.mm.trans1:probe2	-0.0489195301583598	0.140871905739663	-0.347262499939235	0.72849312658709	   
df.mm.trans1:probe3	-0.0236828903255328	0.140871905739663	-0.168116489950095	0.866537697083468	   
df.mm.trans1:probe4	-0.0922055268624275	0.140871905739663	-0.654534531766943	0.512971414382817	   
df.mm.trans1:probe5	-0.217430232773771	0.140871905739663	-1.54346057599015	0.123147734653199	   
df.mm.trans1:probe6	-0.102436764111880	0.140871905739663	-0.727162478380802	0.467357029630653	   
df.mm.trans1:probe7	-0.121256340449229	0.140871905739663	-0.86075601669871	0.389651985480289	   
df.mm.trans1:probe8	-0.248184595664711	0.140871905739663	-1.76177495691274	0.0785213223333335	.  
df.mm.trans1:probe9	0.226424841665927	0.140871905739663	1.60731013382021	0.108414073981512	   
df.mm.trans1:probe10	-0.114501682005746	0.140871905739663	-0.812807077497407	0.41659080044167	   
df.mm.trans1:probe11	-0.12739065733757	0.140871905739663	-0.904301369877063	0.366130716001742	   
df.mm.trans1:probe12	-0.211219796398404	0.140871905739663	-1.49937487740633	0.134204044065655	   
df.mm.trans1:probe13	-0.127861081608947	0.140871905739663	-0.90764074595001	0.364364332415491	   
df.mm.trans1:probe14	-0.110426306357079	0.140871905739663	-0.783877422380807	0.433363545330000	   
df.mm.trans1:probe15	-0.172222260849023	0.140871905739663	-1.22254511958755	0.221891837680854	   
df.mm.trans1:probe16	-0.0614529160975723	0.140871905739663	-0.436232588569786	0.662795567642658	   
df.mm.trans1:probe17	-0.178312183872614	0.140871905739663	-1.26577533636935	0.205992967462684	   
df.mm.trans1:probe18	-0.0658965325948372	0.140871905739663	-0.467776255661768	0.640082703110006	   
df.mm.trans1:probe19	-0.113215364226629	0.140871905739663	-0.803675961024159	0.421842919256934	   
df.mm.trans1:probe20	-0.0492197715202779	0.140871905739663	-0.349393807529216	0.726893353258889	   
df.mm.trans1:probe21	-0.0120808544610687	0.140871905739663	-0.0857577271893702	0.931682271362258	   
df.mm.trans1:probe22	-0.143539540835025	0.140871905739663	-1.01893660117222	0.308566973538433	   
df.mm.trans2:probe2	-0.00417124033844675	0.140871905739663	-0.0296101647560257	0.976385963928923	   
df.mm.trans2:probe3	0.102240479026637	0.140871905739663	0.725769119753241	0.46821040784745	   
df.mm.trans2:probe4	-0.0627189245152353	0.140871905739663	-0.445219536045336	0.656291668321792	   
df.mm.trans2:probe5	-0.283550269892630	0.140871905739663	-2.01282341148022	0.0444959367048931	*  
df.mm.trans2:probe6	0.0235400286188016	0.140871905739663	0.167102365054282	0.867335280139583	   
df.mm.trans3:probe2	0.144476995809408	0.140871905739663	1.02559126357250	0.305420324731828	   
df.mm.trans3:probe3	0.164663583350626	0.140871905739663	1.16888873254069	0.242825879750952	   
df.mm.trans3:probe4	0.122689096345171	0.140871905739663	0.870926645742302	0.384077417166021	   
df.mm.trans3:probe5	-0.0514541642067122	0.140871905739663	-0.365254973563015	0.715025739665491