chr12.5611_chr12_64348939_64351789_-_0.R 

fitVsDatCorrelation=0.941102678447769
cont.fitVsDatCorrelation=0.315573748150978

fstatistic=7554.90220759202,41,439
cont.fstatistic=949.900505599276,41,439

residuals=-0.591009897018869,-0.0878900206543407,0.00469240917823434,0.0891238032132277,1.03638328503333
cont.residuals=-0.935646451748855,-0.336826509231805,-0.0686601326630256,0.221586338479593,1.86884144250817

predictedValues:
Include	Exclude	Both
chr12.5611_chr12_64348939_64351789_-_0.R.tl.Lung	51.3948813699699	74.1546968204748	117.738390177809
chr12.5611_chr12_64348939_64351789_-_0.R.tl.cerebhem	48.8982276663389	71.731287414724	94.4121021148532
chr12.5611_chr12_64348939_64351789_-_0.R.tl.cortex	52.6124148855512	84.6839965047878	91.0723638092692
chr12.5611_chr12_64348939_64351789_-_0.R.tl.heart	53.9148548164466	98.0018518988833	97.984428082231
chr12.5611_chr12_64348939_64351789_-_0.R.tl.kidney	53.9558867671768	87.4338629782076	122.464080460263
chr12.5611_chr12_64348939_64351789_-_0.R.tl.liver	55.8702741447306	91.0955859441877	114.784810655964
chr12.5611_chr12_64348939_64351789_-_0.R.tl.stomach	62.6282186006831	122.706566470108	97.2513921052068
chr12.5611_chr12_64348939_64351789_-_0.R.tl.testicle	50.7727219890023	89.2154284510338	110.363064902405


diffExp=-22.7598154505049,-22.8330597483851,-32.0715816192367,-44.0869970824367,-33.4779762110308,-35.2253117994572,-60.0783478694249,-38.4427064620315
diffExpScore=0.996551436316555
diffExp1.5=0,0,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.857142857142857
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	114.971612102233	70.7056182041425	88.274688840789
cerebhem	68.5338491435221	75.018909029718	64.694123889994
cortex	92.1719579864037	66.2685667243315	76.3823437051511
heart	79.7604104207126	64.9242686082292	94.8865322208587
kidney	73.3791118866186	84.0922215164668	77.0319440225826
liver	84.0026008457615	80.6796520821588	80.775509351111
stomach	69.9537255105481	84.0651544359636	89.9197976354781
testicle	86.0112989835069	71.464798898098	82.4009140888428
cont.diffExp=44.265993898091,-6.4850598861958,25.9033912620722,14.8361418124833,-10.7131096298483,3.32294876360271,-14.1114289254155,14.5465000854088
cont.diffExpScore=1.84915422626512

cont.diffExp1.5=1,0,0,0,0,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=1,0,0,0,0,0,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=1,0,1,0,0,0,0,0
cont.diffExp1.3Score=0.666666666666667
cont.diffExp1.2=1,0,1,1,0,0,-1,1
cont.diffExp1.2Score=1.25

tran.correlation=0.922186904398555
cont.tran.correlation=-0.490210710778675

tran.covariance=0.0113825871479222
cont.tran.covariance=-0.008768389744952

tran.mean=71.8169222951442
cont.tran.mean=79.125234773651

weightedLogRatios:
wLogRatio
Lung	-1.51149646525367
cerebhem	-1.56390953682654
cortex	-1.99954012183757
heart	-2.56134656944082
kidney	-2.04165864508744
liver	-2.08626786383259
stomach	-3.00879021940799
testicle	-2.37270766105898

cont.weightedLogRatios:
wLogRatio
Lung	2.18850130717654
cerebhem	-0.386290183662124
cortex	1.43810594207081
heart	0.880051109631387
kidney	-0.594672603742979
liver	0.178020522130890
stomach	-0.79745780231293
testicle	0.808134426957242

varWeightedLogRatios=0.249369088322220
cont.varWeightedLogRatios=1.10445065513756

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.51319130799049	0.0880643830143754	39.8934414542711	4.3233325037619e-148	***
df.mm.trans1	0.343933056743937	0.0710547359153092	4.84039596113445	1.7979004021495e-06	***
df.mm.trans2	0.946056649002918	0.0710547359153091	13.3144770269857	3.26603169243662e-34	***
df.mm.exp2	0.137772043351107	0.0957113620082498	1.43945337795142	0.150734763934824	   
df.mm.exp3	0.412997498495114	0.0957113620082498	4.31503104573432	1.97342456002963e-05	***
df.mm.exp4	0.510356984832176	0.0957113620082498	5.332250781137	1.55570038708888e-07	***
df.mm.exp5	0.174004829452904	0.0957113620082498	1.81801643819368	0.0697430319047289	.  
df.mm.exp6	0.314655795578643	0.0957113620082497	3.28754903259575	0.00109184808708775	** 
df.mm.exp7	0.89248566138214	0.0957113620082497	9.32476189509467	5.49409649516346e-19	***
df.mm.exp8	0.237410848979175	0.0957113620082497	2.48048762443388	0.0134940910006117	*  
df.mm.trans1:exp2	-0.187569474829709	0.0763512539173807	-2.45666528322740	0.0144094007844526	*  
df.mm.trans2:exp2	-0.170998434037144	0.0763512539173807	-2.23962836579188	0.0256149607352587	*  
df.mm.trans1:exp3	-0.389583965421147	0.0763512539173807	-5.10252216476647	4.99886338205834e-07	***
df.mm.trans2:exp3	-0.280224266690622	0.0763512539173807	-3.67019861905413	0.000272178503665406	***
df.mm.trans1:exp4	-0.46248952858524	0.0763512539173807	-6.05739270615906	2.97644793021583e-09	***
df.mm.trans2:exp4	-0.231524018141384	0.0763512539173806	-3.03235384178386	0.00257031506556192	** 
df.mm.trans1:exp5	-0.125376611722237	0.0763512539173807	-1.64210285083080	0.101284789084811	   
df.mm.trans2:exp5	-0.00927558229548305	0.0763512539173806	-0.121485657662153	0.903361961091787	   
df.mm.trans1:exp6	-0.231161908547595	0.0763512539173807	-3.02761116140586	0.00261014422226585	** 
df.mm.trans2:exp6	-0.108899854078148	0.0763512539173806	-1.42630079390691	0.154492274934113	   
df.mm.trans1:exp7	-0.69480829173694	0.0763512539173807	-9.10015561091883	3.17372736303041e-18	***
df.mm.trans2:exp7	-0.388843203362046	0.0763512539173807	-5.09282013603616	5.24658469298316e-07	***
df.mm.trans1:exp8	-0.249590190594946	0.0763512539173807	-3.26897303959181	0.00116427135104721	** 
df.mm.trans2:exp8	-0.0525102683808071	0.0763512539173806	-0.68774598564718	0.491975959366956	   
df.mm.trans1:probe2	0.0441518091848185	0.0499836286401701	0.883325408458547	0.377543942021567	   
df.mm.trans1:probe3	0.441796314318685	0.0499836286401701	8.83882035654428	2.35659419788764e-17	***
df.mm.trans1:probe4	0.151096872237235	0.0499836286401701	3.02292723333423	0.00265003494329862	** 
df.mm.trans1:probe5	0.431182462309028	0.0499836286401701	8.6264737883096	1.16722308418551e-16	***
df.mm.trans1:probe6	0.0855716013145147	0.0499836286401701	1.71199257922111	0.0876042652226247	.  
df.mm.trans2:probe2	-0.388873029209288	0.0499836286401701	-7.78000797038502	5.23440244661209e-14	***
df.mm.trans2:probe3	-0.661210100819728	0.0499836286401701	-13.2285333980002	7.40484152800713e-34	***
df.mm.trans2:probe4	-0.0299059462064347	0.0499836286401701	-0.598314828675732	0.54993844120288	   
df.mm.trans2:probe5	-0.375791903061931	0.0499836286401701	-7.51829975705127	3.15236396926726e-13	***
df.mm.trans2:probe6	-0.687542696409725	0.0499836286401701	-13.7553578064393	4.73973255491459e-36	***
df.mm.trans3:probe2	0.0468154562506921	0.0499836286401701	0.936615798499034	0.349471178928403	   
df.mm.trans3:probe3	-0.1764607666721	0.0499836286401701	-3.53037127301087	0.00045884059550458	***
df.mm.trans3:probe4	-0.833318145965791	0.0499836286401701	-16.6718217271661	1.06141028601684e-48	***
df.mm.trans3:probe5	1.16240933241107	0.0499836286401701	23.2558012300229	1.48546652136296e-78	***
df.mm.trans3:probe6	-0.181222578713501	0.0499836286401701	-3.62563870698773	0.000322050572111843	***
df.mm.trans3:probe7	0.00146800694272839	0.0499836286401701	0.0293697553112141	0.976583041014255	   
df.mm.trans3:probe8	-0.297418367596322	0.0499836286401701	-5.95031564709765	5.47631005408401e-09	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.56360082840673	0.247143503337624	18.4653885972166	9.30412008723914e-57	***
df.mm.trans1	0.188268837104279	0.199407703338734	0.9441402410842	0.345617305247749	   
df.mm.trans2	-0.308917015334062	0.199407703338734	-1.54917292643055	0.122060729119143	   
df.mm.exp2	-0.147359267895982	0.268603952088929	-0.548611689254648	0.583550852293978	   
df.mm.exp3	-0.141136811928076	0.268603952088929	-0.52544577557574	0.599538625954443	   
df.mm.exp4	-0.523189881254259	0.268603952088929	-1.94781155372219	0.0520745426505464	.  
df.mm.exp5	-0.139423670359011	0.268603952088929	-0.519067829325352	0.603975010663478	   
df.mm.exp6	-0.0930965207527837	0.268603952088929	-0.346594009614428	0.729062413523448	   
df.mm.exp7	-0.342248894934214	0.268603952088929	-1.27417669126813	0.203274902333278	   
df.mm.exp8	-0.210669718479469	0.268603952088929	-0.784313547291816	0.433279146815027	   
df.mm.trans1:exp2	-0.369998207411711	0.214271828535740	-1.72677019625096	0.084912402663134	.  
df.mm.trans2:exp2	0.206574434901080	0.214271828535739	0.964076501856258	0.335538324771104	   
df.mm.trans1:exp3	-0.079892493690357	0.214271828535740	-0.372855798339497	0.709435725364175	   
df.mm.trans2:exp3	0.076327454823321	0.214271828535739	0.356217872152941	0.721848536968244	   
df.mm.trans1:exp4	0.157531905985068	0.214271828535740	0.735196535454926	0.462612380093723	   
df.mm.trans2:exp4	0.437886338409800	0.214271828535739	2.04360200499602	0.0415892719581202	*  
df.mm.trans1:exp5	-0.309622260327775	0.214271828535740	-1.44499751760942	0.149171982028368	   
df.mm.trans2:exp5	0.312812707023678	0.214271828535739	1.45988723371305	0.145036288200625	   
df.mm.trans1:exp6	-0.220740965039218	0.214271828535739	-1.03019126008158	0.303487468044833	   
df.mm.trans2:exp6	0.225057886360742	0.214271828535739	1.05033819844032	0.294140496319828	   
df.mm.trans1:exp7	-0.154602392356223	0.214271828535740	-0.721524585909042	0.470970918009934	   
df.mm.trans2:exp7	0.515316006014781	0.214271828535740	2.40496387012831	0.0165870636713534	*  
df.mm.trans1:exp8	-0.0795368569734636	0.214271828535740	-0.371196052775539	0.710670582199368	   
df.mm.trans2:exp8	0.221349688694651	0.214271828535739	1.03303215456404	0.302157599501319	   
df.mm.trans1:probe2	0.0135445739619665	0.140273839080232	0.0965580898817452	0.923121404472902	   
df.mm.trans1:probe3	0.0258194682736788	0.140273839080232	0.184064743953510	0.854047655003653	   
df.mm.trans1:probe4	-0.130863469359668	0.140273839080232	-0.932914292627427	0.351377024909959	   
df.mm.trans1:probe5	0.0789372958251582	0.140273839080232	0.562737117218333	0.573901163171804	   
df.mm.trans1:probe6	-0.0880197333778644	0.140273839080232	-0.627485024684609	0.530667581783772	   
df.mm.trans2:probe2	-0.0559492439264952	0.140273839080232	-0.398857294370435	0.690192295591172	   
df.mm.trans2:probe3	-0.113562104975031	0.140273839080232	-0.809574370528757	0.418623421475649	   
df.mm.trans2:probe4	0.0621523521651205	0.140273839080232	0.443078713555215	0.657927057838978	   
df.mm.trans2:probe5	0.131104287959031	0.140273839080232	0.934631067479686	0.350492264886773	   
df.mm.trans2:probe6	0.030031817866234	0.140273839080232	0.2140942178752	0.830572988484433	   
df.mm.trans3:probe2	0.0333954656806051	0.140273839080232	0.238073370626892	0.811935267281718	   
df.mm.trans3:probe3	0.239276062137266	0.140273839080232	1.70577823852392	0.088756700426533	.  
df.mm.trans3:probe4	0.112234945354403	0.140273839080232	0.800113165008682	0.424077983990426	   
df.mm.trans3:probe5	-0.097432937010972	0.140273839080232	-0.694590934773258	0.487679125973108	   
df.mm.trans3:probe6	-0.0394046082527497	0.140273839080232	-0.280912025443401	0.778910221043201	   
df.mm.trans3:probe7	0.0443137010840266	0.140273839080232	0.315908521322216	0.752222079880316	   
df.mm.trans3:probe8	0.00762350497885482	0.140273839080232	0.054347304022202	0.956683185488498