chr6.19592_chr6_130327203_130331494_+_2.R 

fitVsDatCorrelation=0.900703222528557
cont.fitVsDatCorrelation=0.241371564552234

fstatistic=8606.85663931392,61,899
cont.fstatistic=1713.11270403174,61,899

residuals=-0.765960006072456,-0.0988449003393226,-0.00997530381277926,0.0797468966397253,1.88225186061648
cont.residuals=-0.741709953236818,-0.273099728505490,-0.0487796054325114,0.170940578752502,2.21769985700043

predictedValues:
Include	Exclude	Both
chr6.19592_chr6_130327203_130331494_+_2.R.tl.Lung	80.7750375956982	84.722927146438	53.7009690881007
chr6.19592_chr6_130327203_130331494_+_2.R.tl.cerebhem	79.8778910183826	59.098372163251	51.1307844509298
chr6.19592_chr6_130327203_130331494_+_2.R.tl.cortex	69.2439153596045	67.588589259462	50.1643335381897
chr6.19592_chr6_130327203_130331494_+_2.R.tl.heart	74.4536531840072	76.4110914298928	50.1937527026533
chr6.19592_chr6_130327203_130331494_+_2.R.tl.kidney	75.8312184840244	78.1939116637562	50.4712748696896
chr6.19592_chr6_130327203_130331494_+_2.R.tl.liver	79.5430744126414	86.1336217366222	56.9497226580381
chr6.19592_chr6_130327203_130331494_+_2.R.tl.stomach	76.8754416330634	88.2214510200742	52.9619123434651
chr6.19592_chr6_130327203_130331494_+_2.R.tl.testicle	71.5419142473009	73.4837991480225	50.2388785565812


diffExp=-3.94788955073973,20.7795188551316,1.65532610014250,-1.95743824588561,-2.36269317973181,-6.59054732398084,-11.3460093870107,-1.94188490072169
diffExpScore=7.53638099050504
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,1,0,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	65.3191987655538	79.5053879255675	71.0552242687222
cerebhem	64.810945056249	62.200697578319	69.7442884974145
cortex	62.906268022837	57.990410016845	71.0633528419903
heart	58.5195720703596	68.7166723258537	69.9395494278471
kidney	65.4606304552327	76.1094888223703	67.2555984189763
liver	68.2895528808704	74.1188596225055	61.2210789727266
stomach	65.0472805096492	68.1700818430625	69.6509486640325
testicle	68.6337849208745	82.8106221829908	68.3854662736378
cont.diffExp=-14.1861891600137,2.61024747793,4.91585800599199,-10.1971002554941,-10.6488583671376,-5.82930674163514,-3.12280133341326,-14.1768372621163
cont.diffExpScore=1.27214514055731

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=-1,0,0,0,0,0,0,-1
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.312371953152636
cont.tran.correlation=0.538978591087518

tran.covariance=0.00204436905873962
cont.tran.covariance=0.00312389360958544

tran.mean=76.3747443438901
cont.tran.mean=68.0380908124463

weightedLogRatios:
wLogRatio
Lung	-0.210701334374067
cerebhem	1.27443610148428
cortex	0.102241544456146
heart	-0.112190275779370
kidney	-0.133276849712790
liver	-0.351526536135174
stomach	-0.607236974506835
testicle	-0.114723096967911

cont.weightedLogRatios:
wLogRatio
Lung	-0.840705563062468
cerebhem	0.170637194185092
cortex	0.333687697985711
heart	-0.666564990749374
kidney	-0.641603764433588
liver	-0.349336408070235
stomach	-0.196876310383298
testicle	-0.81167406733869

varWeightedLogRatios=0.315989845070131
cont.varWeightedLogRatios=0.199428250201589

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.89143194854247	0.0826474612082483	59.184297702956	0	***
df.mm.trans1	-0.622177751439954	0.0702180477983509	-8.86065293678766	4.19222284691651e-18	***
df.mm.trans2	-0.438744576455341	0.0621816549826341	-7.0558523503093	3.42536798430909e-12	***
df.mm.exp2	-0.322307445657599	0.078943611728805	-4.08275525529312	4.84689706840839e-05	***
df.mm.exp3	-0.311853020657209	0.078943611728805	-3.95032623701735	8.41542094667981e-05	***
df.mm.exp4	-0.11720906348445	0.078943611728805	-1.48471878746944	0.137968868902676	   
df.mm.exp5	-0.0813256912041392	0.078943611728805	-1.03017444253143	0.303205195841863	   
df.mm.exp6	-0.0575934779390891	0.078943611728805	-0.72955210279636	0.46585404425919	   
df.mm.exp7	0.00484041204580281	0.078943611728805	0.0613148035642336	0.951122129642137	   
df.mm.exp8	-0.197063927815790	0.078943611728805	-2.49626186970978	0.0127290965587121	*  
df.mm.trans1:exp2	0.311138574835892	0.0708242580190684	4.39310743999779	1.25052742265328e-05	***
df.mm.trans2:exp2	-0.0378754256064093	0.0508334427938743	-0.745088735382163	0.456412818699574	   
df.mm.trans1:exp3	0.157820319873302	0.0708242580190684	2.22833707387109	0.026104687521986	*  
df.mm.trans2:exp3	0.0859059399934942	0.0508334427938743	1.68994927889965	0.0913843494757611	.  
df.mm.trans1:exp4	0.0357179132219982	0.0708242580190684	0.504317506755689	0.61416185327911	   
df.mm.trans2:exp4	0.013950673376173	0.0508334427938743	0.274438885297262	0.78381041331567	   
df.mm.trans1:exp5	0.0181677752676413	0.0708242580190684	0.256519104834813	0.797608720354199	   
df.mm.trans2:exp5	0.00113122823457004	0.0508334427938743	0.022253622269046	0.982250581971225	   
df.mm.trans1:exp6	0.0422241922332621	0.0708242580190684	0.596182627453631	0.551203307039177	   
df.mm.trans2:exp6	0.0741070579815127	0.0508334427938743	1.45784062437028	0.145233709113978	   
df.mm.trans1:exp7	-0.0543219182630423	0.0708242580190684	-0.76699593871378	0.443285302151763	   
df.mm.trans2:exp7	0.0356234787131397	0.0508334427938743	0.700788236153712	0.483616515562498	   
df.mm.trans1:exp8	0.0756794418610913	0.0708242580190684	1.06855255498357	0.285558171093880	   
df.mm.trans2:exp8	0.0547426384560756	0.0508334427938743	1.07690204415335	0.281812923368294	   
df.mm.trans1:probe2	-0.375781605435585	0.0523071811024326	-7.18413031472095	1.41938100662094e-12	***
df.mm.trans1:probe3	-0.127040977839539	0.0523071811024326	-2.42874831260274	0.0153461890504944	*  
df.mm.trans1:probe4	0.176963586696614	0.0523071811024326	3.38316045649772	0.00074752155834968	***
df.mm.trans1:probe5	-0.0220358556166405	0.0523071811024326	-0.421277827483915	0.673652919729034	   
df.mm.trans1:probe6	0.35563808691891	0.0523071811024326	6.7990298735936	1.91814027948074e-11	***
df.mm.trans1:probe7	0.0819923943556148	0.0523071811024326	1.56751697620734	0.117345797963997	   
df.mm.trans1:probe8	0.0606261820410687	0.0523071811024326	1.15904127814392	0.246747126328117	   
df.mm.trans1:probe9	0.0735236220056086	0.0523071811024326	1.40561239309815	0.160184746354464	   
df.mm.trans1:probe10	-0.0739519966552032	0.0523071811024326	-1.41380198849530	0.15776623258428	   
df.mm.trans1:probe11	-0.0169510942969710	0.0523071811024326	-0.324068205162421	0.745961777745688	   
df.mm.trans1:probe12	0.111555867198329	0.0523071811024326	2.13270653946865	0.0332191689654146	*  
df.mm.trans1:probe13	0.226028257653357	0.0523071811024326	4.32117068611914	1.72510762838681e-05	***
df.mm.trans1:probe14	1.1758318538785	0.0523071811024326	22.4793580746758	3.75663918305187e-89	***
df.mm.trans1:probe15	0.534350511269283	0.0523071811024326	10.2156243178708	2.96961892353677e-23	***
df.mm.trans1:probe16	0.41244082207497	0.0523071811024326	7.88497512927129	9.08954556048911e-15	***
df.mm.trans1:probe17	0.936988972717551	0.0523071811024326	17.9131995448705	1.34459117549257e-61	***
df.mm.trans1:probe18	0.63188989457229	0.0523071811024326	12.0803660463917	3.04642150263678e-31	***
df.mm.trans2:probe2	-0.0465342436719356	0.0523071811024326	-0.889633941098987	0.373900468305953	   
df.mm.trans2:probe3	0.00733315130160526	0.0523071811024326	0.140193968534547	0.888538140425893	   
df.mm.trans2:probe4	-0.14882669578328	0.0523071811024326	-2.84524404960447	0.00453856549098869	** 
df.mm.trans2:probe5	-0.123073696119662	0.0523071811024326	-2.35290247965471	0.0188421514297618	*  
df.mm.trans2:probe6	0.0184768319658899	0.0523071811024326	0.353237004489056	0.723993579730218	   
df.mm.trans3:probe2	-0.0829203543054605	0.0523071811024326	-1.58525756039268	0.113259495898762	   
df.mm.trans3:probe3	0.0861164587639631	0.0523071811024326	1.64636015455167	0.100039137713958	   
df.mm.trans3:probe4	0.230095294243966	0.0523071811024326	4.39892361611635	1.21817136190621e-05	***
df.mm.trans3:probe5	0.0460766041238715	0.0523071811024326	0.880884864233845	0.378615572346393	   
df.mm.trans3:probe6	-0.00272666121170002	0.0523071811024326	-0.0521278561419785	0.958438397397743	   
df.mm.trans3:probe7	0.122549524727683	0.0523071811024326	2.34288145804868	0.0193526822337512	*  
df.mm.trans3:probe8	0.00925179962140925	0.0523071811024326	0.176874368421643	0.859646911221173	   
df.mm.trans3:probe9	0.234097788796697	0.0523071811024326	4.47544264215396	8.60400892942958e-06	***
df.mm.trans3:probe10	0.175951135553186	0.0523071811024326	3.36380458370759	0.00080125702208047	***
df.mm.trans3:probe11	0.0808112025958429	0.0523071811024326	1.54493514834208	0.122713873502791	   
df.mm.trans3:probe12	0.133165844443740	0.0523071811024326	2.54584249499057	0.0110673326355967	*  
df.mm.trans3:probe13	0.301426692218421	0.0523071811024326	5.76262543431924	1.13731686905326e-08	***
df.mm.trans3:probe14	0.420851437150421	0.0523071811024326	8.04576787126556	2.69803647704145e-15	***
df.mm.trans3:probe15	0.614406425348045	0.0523071811024326	11.7461199857981	9.72006414336572e-30	***
df.mm.trans3:probe16	0.0775896405404176	0.0523071811024326	1.48334586007368	0.138333023479454	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.3142881984656	0.184616383722862	23.3689346062699	9.44878167775506e-95	***
df.mm.trans1	-0.184268198190586	0.156851787908482	-1.17479182512156	0.240389083212937	   
df.mm.trans2	0.0725994616659689	0.138900240962888	0.522673403319483	0.601330328736425	   
df.mm.exp2	-0.234648235390210	0.176342792656034	-1.33063694782187	0.183645901704562	   
df.mm.exp3	-0.353301723487136	0.176342792656034	-2.00349397991145	0.0454240007439183	*  
df.mm.exp4	-0.239931585354102	0.176342792656034	-1.36059762772444	0.173981895179423	   
df.mm.exp5	0.0134681708170181	0.176342792656034	0.0763749434505581	0.93913779659064	   
df.mm.exp6	0.123281841023462	0.176342792656034	0.699103372282019	0.484668257232543	   
df.mm.exp7	-0.138029549136907	0.176342792656034	-0.782734281667759	0.433989296345611	   
df.mm.exp8	0.128527512345945	0.176342792656034	0.728850385150951	0.466283010137929	   
df.mm.trans1:exp2	0.226836727943429	0.158205929186248	1.43380674232749	0.151975127666169	   
df.mm.trans2:exp2	-0.0108103418545009	0.113550812615300	-0.0952026815618258	0.92417505587027	   
df.mm.trans1:exp3	0.315661531099118	0.158205929186248	1.99525727463415	0.0463162589596232	*  
df.mm.trans2:exp3	0.0377545838130139	0.113550812615300	0.332490652805129	0.739596308159141	   
df.mm.trans1:exp4	0.130006847211549	0.158205929186248	0.821757110370356	0.411433025763835	   
df.mm.trans2:exp4	0.0940986461818026	0.113550812615300	0.828691966305873	0.407498687401229	   
df.mm.trans1:exp5	-0.0113052723691791	0.158205929186248	-0.0714592204434383	0.943048172481542	   
df.mm.trans2:exp5	-0.0571200168732264	0.113550812615300	-0.503034857766664	0.615062979394562	   
df.mm.trans1:exp6	-0.0788110471618206	0.158205929186248	-0.498154826226772	0.618496760465985	   
df.mm.trans2:exp6	-0.193436617294264	0.113550812615300	-1.70352472905333	0.0888155181544194	.  
df.mm.trans1:exp7	0.133857945335847	0.158205929186248	0.846099422596624	0.397722432374859	   
df.mm.trans2:exp7	-0.0157894569285763	0.113550812615300	-0.139051906057860	0.889440274892577	   
df.mm.trans1:exp8	-0.0790286090214966	0.158205929186248	-0.499530007680432	0.617528279890517	   
df.mm.trans2:exp8	-0.087795963961118	0.113550812615300	-0.773186575586764	0.439615214135963	   
df.mm.trans1:probe2	0.0807666991475852	0.116842822231836	0.691242282622463	0.48959174930059	   
df.mm.trans1:probe3	0.209993882062835	0.116842822231836	1.79723390835400	0.0726340117203366	.  
df.mm.trans1:probe4	-0.00471532454097264	0.116842822231836	-0.0403561335724724	0.967818162373325	   
df.mm.trans1:probe5	0.0372462565143273	0.116842822231836	0.318772311408435	0.749973221801236	   
df.mm.trans1:probe6	0.129792142850607	0.116842822231836	1.11082683875161	0.266939896665169	   
df.mm.trans1:probe7	0.0189034619649311	0.116842822231836	0.161785393435836	0.871511208461402	   
df.mm.trans1:probe8	0.0773375832692215	0.116842822231836	0.661894173659811	0.508208666459495	   
df.mm.trans1:probe9	0.133431450295623	0.116842822231836	1.14197387350737	0.253768945100274	   
df.mm.trans1:probe10	0.13524597841022	0.116842822231836	1.15750352333897	0.247374138686823	   
df.mm.trans1:probe11	0.0658844722730076	0.116842822231836	0.563872654002498	0.572981432218918	   
df.mm.trans1:probe12	0.155283368115609	0.116842822231836	1.32899364419236	0.184187257176056	   
df.mm.trans1:probe13	0.0293215886002357	0.116842822231836	0.250948993187246	0.801910889342455	   
df.mm.trans1:probe14	0.18618701651835	0.116842822231836	1.59348270575768	0.111403446328756	   
df.mm.trans1:probe15	0.185567593749427	0.116842822231836	1.58818137224749	0.112596945678596	   
df.mm.trans1:probe16	0.053546432873151	0.116842822231836	0.45827746925614	0.646863864093475	   
df.mm.trans1:probe17	0.211538296148882	0.116842822231836	1.81045178564031	0.0705595050105079	.  
df.mm.trans1:probe18	-0.0302868487440027	0.116842822231836	-0.259210177959484	0.79553242030793	   
df.mm.trans2:probe2	-0.109399132370989	0.116842822231836	-0.936293135353427	0.349373723721902	   
df.mm.trans2:probe3	0.0867043120931543	0.116842822231836	0.74205937889037	0.458245182780112	   
df.mm.trans2:probe4	-0.0172002249823156	0.116842822231836	-0.147208229429681	0.88300067147053	   
df.mm.trans2:probe5	-0.0868000276104886	0.116842822231836	-0.742878560723759	0.457749277713289	   
df.mm.trans2:probe6	-0.116688025749568	0.116842822231836	-0.99867517337127	0.318220794984902	   
df.mm.trans3:probe2	-0.0210883017642658	0.116842822231836	-0.180484358058580	0.856813009942818	   
df.mm.trans3:probe3	-0.0578939570991467	0.116842822231836	-0.495485781610745	0.620378347136028	   
df.mm.trans3:probe4	0.0931181225953667	0.116842822231836	0.796952014823848	0.425689320255036	   
df.mm.trans3:probe5	0.149631273866301	0.116842822231836	1.28062016141143	0.200657405102370	   
df.mm.trans3:probe6	0.205781001463033	0.116842822231836	1.76117794428765	0.0785482078977295	.  
df.mm.trans3:probe7	-0.0679645802957755	0.116842822231836	-0.581675271082737	0.560931251542582	   
df.mm.trans3:probe8	0.116564815671862	0.116842822231836	0.99762067917683	0.318731769355577	   
df.mm.trans3:probe9	0.0368093215623666	0.116842822231836	0.315032800982251	0.752809855621087	   
df.mm.trans3:probe10	-0.00449087435507803	0.116842822231836	-0.0384351753004336	0.969349249001377	   
df.mm.trans3:probe11	0.149254561822094	0.116842822231836	1.27739606910510	0.201792238310881	   
df.mm.trans3:probe12	0.0816530122570507	0.116842822231836	0.698827798724657	0.484840396424887	   
df.mm.trans3:probe13	0.0729195322775928	0.116842822231836	0.624082257555435	0.532731892416611	   
df.mm.trans3:probe14	0.112540609422737	0.116842822231836	0.963179485680661	0.335716459451460	   
df.mm.trans3:probe15	0.0956170156044287	0.116842822231836	0.818338805739458	0.413380605814517	   
df.mm.trans3:probe16	0.0109551568475446	0.116842822231836	0.0937597760674391	0.925320876360651