chr16.9661_chr16_46502590_46508636_-_2.R 

fitVsDatCorrelation=0.857968811462575
cont.fitVsDatCorrelation=0.220132993501942

fstatistic=7661.53692160408,58,830
cont.fstatistic=2114.42047122115,58,830

residuals=-0.595713975264479,-0.101497800579245,-0.00621689245397549,0.0978557016279129,1.05529793362164
cont.residuals=-0.6223812017052,-0.231213796501393,-0.0923634465490994,0.157626782982357,1.4571475470941

predictedValues:
Include	Exclude	Both
chr16.9661_chr16_46502590_46508636_-_2.R.tl.Lung	66.2255981895191	51.137629679383	76.5284536756193
chr16.9661_chr16_46502590_46508636_-_2.R.tl.cerebhem	59.571193581391	62.5328283883331	56.7795405033217
chr16.9661_chr16_46502590_46508636_-_2.R.tl.cortex	59.2181559637602	48.5379048497196	67.7345567476017
chr16.9661_chr16_46502590_46508636_-_2.R.tl.heart	50.7688851302519	49.6848490027988	57.212017656144
chr16.9661_chr16_46502590_46508636_-_2.R.tl.kidney	64.6338906488944	49.6737387881832	77.086725340401
chr16.9661_chr16_46502590_46508636_-_2.R.tl.liver	57.0957249503514	50.2887857021395	63.5640733354363
chr16.9661_chr16_46502590_46508636_-_2.R.tl.stomach	53.0930706239733	49.9313888522062	55.7330842377149
chr16.9661_chr16_46502590_46508636_-_2.R.tl.testicle	49.0150898532545	54.5306084020257	51.8862384089607


diffExp=15.0879685101361,-2.96163480694205,10.6802511140406,1.08403612745307,14.9601518607112,6.80693924821195,3.16168177176709,-5.5155185487712
diffExpScore=1.36011086190130
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=0,0,0,0,1,0,0,0
diffExp1.3Score=0.5
diffExp1.2=1,0,1,0,1,0,0,0
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	58.6869471143051	62.4549235497282	60.4806181166147
cerebhem	56.8819447631696	57.5023434284826	60.029414836849
cortex	59.819579390398	49.5597626574871	62.3065231512608
heart	62.4141722561257	63.086110193977	59.4883745760914
kidney	61.3663035584835	58.4681009576143	61.2711876859526
liver	59.0536829242995	55.2104464923546	61.2087156094669
stomach	63.4653756150613	65.2657867805499	60.8324656334373
testicle	60.4013705855477	61.6794288417214	59.0129688036189
cont.diffExp=-3.76797643542319,-0.620398665313061,10.2598167329108,-0.671937937851311,2.8982026008692,3.84323643194492,-1.80041116548860,-1.27805825617372
cont.diffExpScore=2.54906020501151

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=0,0,1,0,0,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=-0.0215537945940629
cont.tran.correlation=0.489042959222752

tran.covariance=-0.000253444741318106
cont.tran.covariance=0.00144547157139022

tran.mean=54.7462089128866
cont.tran.mean=59.7072674443316

weightedLogRatios:
wLogRatio
Lung	1.05067946628973
cerebhem	-0.199484805110115
cortex	0.79191025344295
heart	0.0845321185330256
kidney	1.06281904165351
liver	0.505409022863398
stomach	0.241985307283800
testicle	-0.420718440975521

cont.weightedLogRatios:
wLogRatio
Lung	-0.255341016055549
cerebhem	-0.0438942612987546
cortex	0.752098750019542
heart	-0.0443230259339972
kidney	0.198001626293534
liver	0.272193680712674
stomach	-0.116494985023356
testicle	-0.0860889577166787

varWeightedLogRatios=0.312001226860964
cont.varWeightedLogRatios=0.101695939447985

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.61575894537382	0.0857492500751867	42.1666538448260	1.48980196528478e-208	***
df.mm.trans1	0.408566543705688	0.0742372691922701	5.50352334011001	4.9626059797374e-08	***
df.mm.trans2	0.351296814448374	0.065769828342308	5.34130654287255	1.1924313912679e-07	***
df.mm.exp2	0.393762670885293	0.0850053871036475	4.63220843174535	4.19864037808748e-06	***
df.mm.exp3	-0.0419483414524425	0.0850053871036475	-0.493478623905268	0.621804985987532	   
df.mm.exp4	-0.00370533991720146	0.0850053871036475	-0.0435894717199926	0.965242128139682	   
df.mm.exp5	-0.0606408678525511	0.0850053871036475	-0.713376762564606	0.4758131763735	   
df.mm.exp6	0.0205378504446901	0.0850053871036475	0.241606457478374	0.80914479475939	   
df.mm.exp7	0.0721972487682662	0.0850053871036475	0.849325568981126	0.395945058069098	   
df.mm.exp8	0.151911702050531	0.0850053871036475	1.78708323350501	0.0742888602123113	.  
df.mm.trans1:exp2	-0.499657610628134	0.0788021029041315	-6.3406634114321	3.75341340672091e-10	***
df.mm.trans2:exp2	-0.192591616975644	0.0591612456205324	-3.25536785028075	0.00117834061725133	** 
df.mm.trans1:exp3	-0.0698905429015539	0.0788021029041315	-0.886912154953286	0.375383107947351	   
df.mm.trans2:exp3	-0.0102272417051888	0.0591612456205324	-0.1728706283635	0.862795265110531	   
df.mm.trans1:exp4	-0.26207805838919	0.0788021029041315	-3.32577493151455	0.000920448821350906	***
df.mm.trans2:exp4	-0.0251152416427107	0.0591612456205324	-0.424521853441068	0.671295286872758	   
df.mm.trans1:exp5	0.0363126963207894	0.0788021029041315	0.460808721881020	0.645056558435703	   
df.mm.trans2:exp5	0.0315966475532222	0.0591612456205324	0.534076779854958	0.593431424300617	   
df.mm.trans1:exp6	-0.168875673908237	0.0788021029041315	-2.14303511815778	0.032400432787271	*  
df.mm.trans2:exp6	-0.0372763656115893	0.0591612456205324	-0.630080810851829	0.528815132194126	   
df.mm.trans1:exp7	-0.293217893561136	0.0788021029041314	-3.72093995915131	0.000211852599778279	***
df.mm.trans2:exp7	-0.096068027804429	0.0591612456205324	-1.62383375800809	0.104790980685393	   
df.mm.trans1:exp8	-0.452850562961467	0.0788021029041315	-5.74668119596241	1.27777895027662e-08	***
df.mm.trans2:exp8	-0.0876701551247843	0.0591612456205324	-1.48188487590528	0.138750472291370	   
df.mm.trans1:probe2	0.725101998473293	0.0528620576590715	13.7168704848715	9.5879401667074e-39	***
df.mm.trans1:probe3	0.516175676373472	0.0528620576590715	9.764577832034	2.14947445178596e-21	***
df.mm.trans1:probe4	0.0740411121943368	0.0528620576590715	1.40064756222426	0.161693222598976	   
df.mm.trans1:probe5	0.107380631061992	0.0528620576590715	2.03133657328538	0.0425390322414101	*  
df.mm.trans1:probe6	0.320407325221638	0.0528620576590715	6.06119662023133	2.04882711131218e-09	***
df.mm.trans1:probe7	0.90291062872552	0.0528620576590715	17.0805047837667	2.78484406964105e-56	***
df.mm.trans1:probe8	0.66829321754536	0.0528620576590715	12.6422096895178	1.24777562000205e-33	***
df.mm.trans1:probe9	0.499443364560916	0.0528620576590715	9.44805001314982	3.41431445313731e-20	***
df.mm.trans1:probe10	1.02108884778149	0.0528620576590715	19.3161010562038	6.10632868875107e-69	***
df.mm.trans1:probe11	-0.0501212196174321	0.0528620576590715	-0.948151128370444	0.343328493481058	   
df.mm.trans1:probe12	-0.079982488115452	0.0528620576590715	-1.51304152084452	0.130649775804538	   
df.mm.trans1:probe13	-0.0590072905764242	0.0528620576590714	-1.11625035402492	0.264638035218075	   
df.mm.trans1:probe14	-0.00975607474999668	0.0528620576590715	-0.184557226525640	0.853621421119512	   
df.mm.trans1:probe15	0.0183102326446046	0.0528620576590715	0.346377599651806	0.729146745511932	   
df.mm.trans1:probe16	-0.0118287213874991	0.0528620576590714	-0.223765814486209	0.822994596316162	   
df.mm.trans1:probe17	0.129358576036498	0.0528620576590714	2.44709687373093	0.0146075623125731	*  
df.mm.trans1:probe18	0.0861879482604607	0.0528620576590715	1.63043120296832	0.103389783112496	   
df.mm.trans1:probe19	0.185766532783017	0.0528620576590715	3.51417521393321	0.000464988232755903	***
df.mm.trans1:probe20	0.0105284580550955	0.0528620576590715	0.199168525050570	0.842179698897925	   
df.mm.trans1:probe21	0.159711844562221	0.0528620576590715	3.02129450942426	0.00259421375699376	** 
df.mm.trans1:probe22	0.0169783405534552	0.0528620576590715	0.321181983927968	0.748153341540896	   
df.mm.trans2:probe2	-0.00572242727937341	0.0528620576590715	-0.108252072143684	0.91382190298728	   
df.mm.trans2:probe3	-0.166209609786333	0.0528620576590715	-3.14421377348353	0.00172459728268062	** 
df.mm.trans2:probe4	-0.138034843132258	0.0528620576590715	-2.6112272061466	0.0091846421094679	** 
df.mm.trans2:probe5	-0.115771855549396	0.0528620576590715	-2.19007470908633	0.0287964233229324	*  
df.mm.trans2:probe6	-0.062288374360662	0.0528620576590715	-1.17831914077928	0.23900710895446	   
df.mm.trans3:probe2	-0.228397535762089	0.0528620576590714	-4.32063271609886	1.74427031257889e-05	***
df.mm.trans3:probe3	-0.163442512361179	0.0528620576590714	-3.09186814889585	0.00205550671651999	** 
df.mm.trans3:probe4	0.233261921446947	0.0528620576590715	4.41265307815573	1.15571758849619e-05	***
df.mm.trans3:probe5	0.0400462684909901	0.0528620576590715	0.757561666427449	0.448928452002413	   
df.mm.trans3:probe6	0.0386146479333941	0.0528620576590715	0.730479471352315	0.465303290822122	   
df.mm.trans3:probe7	0.0320823433726738	0.0528620576590715	0.606906821137869	0.544078726446411	   
df.mm.trans3:probe8	-0.275446213837078	0.0528620576590714	-5.21066008465922	2.37584179577759e-07	***
df.mm.trans3:probe9	-0.0183561146773031	0.0528620576590715	-0.347245557403176	0.728494876770433	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.18004373642515	0.162829511249456	25.6712908142387	1.91818024461767e-107	***
df.mm.trans1	-0.0793410489706655	0.140969375807633	-0.562824716475546	0.573706237482493	   
df.mm.trans2	-0.0315007685917098	0.124890526675727	-0.252227045799080	0.800928018996453	   
df.mm.exp2	-0.106370468989166	0.161416987594893	-0.658979395998418	0.510091770843326	   
df.mm.exp3	-0.241893293522365	0.161416987594893	-1.49856156484250	0.134367629057359	   
df.mm.exp4	0.088172625087	0.161416987594893	0.546241299634995	0.585046875492428	   
df.mm.exp5	-0.0343069631546396	0.161416987594893	-0.212536261925168	0.831740876034731	   
df.mm.exp6	-0.129029954993475	0.161416987594893	-0.799357966692457	0.424311569424066	   
df.mm.exp7	0.116499373114205	0.161416987594893	0.721729322607502	0.470664175559892	   
df.mm.exp8	0.0408655782915737	0.161416987594893	0.253167766915176	0.800201264369187	   
df.mm.trans1:exp2	0.075131108450449	0.149637552399098	0.502087258484869	0.615739309019743	   
df.mm.trans2:exp2	0.0237510979085234	0.112341468885777	0.211418794360542	0.832612391837442	   
df.mm.trans1:exp3	0.261008979364059	0.149637552399098	1.74427458334739	0.0814813943213753	.  
df.mm.trans2:exp3	0.0106274879470062	0.112341468885777	0.0945998663931629	0.924655488417772	   
df.mm.trans1:exp4	-0.026597592091744	0.149637552399098	-0.177746773221776	0.858965219922412	   
df.mm.trans2:exp4	-0.07811707681081	0.112341468885777	-0.695353884772818	0.487028181780051	   
df.mm.trans1:exp5	0.078950509600121	0.149637552399098	0.527611607743706	0.597909942499168	   
df.mm.trans2:exp5	-0.0316567874355267	0.112341468885777	-0.281790755893655	0.778174202248516	   
df.mm.trans1:exp6	0.135259529200521	0.149637552399098	0.903914338559686	0.366303099144751	   
df.mm.trans2:exp6	0.00573706508983894	0.112341468885777	0.051068097531038	0.959283544432814	   
df.mm.trans1:exp7	-0.0382222179132127	0.149637552399098	-0.255431990836567	0.798452748430128	   
df.mm.trans2:exp7	-0.0724764865093903	0.112341468885777	-0.645144551056925	0.519011800100729	   
df.mm.trans1:exp8	-0.0120711178761491	0.149637552399098	-0.0806690411772725	0.93572460486086	   
df.mm.trans2:exp8	-0.0533601824347802	0.112341468885777	-0.474982061068063	0.634924716798578	   
df.mm.trans1:probe2	-0.0340098785355057	0.100379921745321	-0.338811566538116	0.734837382344886	   
df.mm.trans1:probe3	-0.0324781488657253	0.100379921745321	-0.323552243327379	0.746358553361902	   
df.mm.trans1:probe4	0.073217918603233	0.100379921745321	0.72940800640389	0.465957904458445	   
df.mm.trans1:probe5	-0.0709783971918165	0.100379921745321	-0.707097554547807	0.479704327010691	   
df.mm.trans1:probe6	-0.188614745256606	0.100379921745321	-1.87900868995645	0.0605935201532511	.  
df.mm.trans1:probe7	-0.108608339031578	0.100379921745321	-1.08197274059581	0.279578885043614	   
df.mm.trans1:probe8	-0.159322787169323	0.100379921745321	-1.58719776225319	0.112848721164884	   
df.mm.trans1:probe9	0.042928014376153	0.100379921745321	0.427655387947681	0.669012964465477	   
df.mm.trans1:probe10	-0.108512370788282	0.100379921745321	-1.08101669040542	0.280003681455332	   
df.mm.trans1:probe11	-0.0271285449571351	0.100379921745321	-0.270258678084691	0.787028437262834	   
df.mm.trans1:probe12	0.0293329196067412	0.100379921745321	0.292218992570679	0.770192218272898	   
df.mm.trans1:probe13	-0.055936895206192	0.100379921745321	-0.557251831179073	0.577505620782603	   
df.mm.trans1:probe14	0.0170331965263453	0.100379921745321	0.169687286363513	0.865297421627792	   
df.mm.trans1:probe15	-0.0321342709770276	0.100379921745321	-0.320126479661511	0.74895302261499	   
df.mm.trans1:probe16	-0.107159827873142	0.100379921745321	-1.06754245281265	0.286037354303390	   
df.mm.trans1:probe17	0.0191580763337733	0.100379921745321	0.190855661178739	0.848685352068533	   
df.mm.trans1:probe18	-0.00800802697700438	0.100379921745321	-0.0797771789195251	0.936433705436764	   
df.mm.trans1:probe19	-0.03618991034093	0.100379921745321	-0.360529373919511	0.718543025263221	   
df.mm.trans1:probe20	-0.0511785606760962	0.100379921745321	-0.509848581133028	0.610293087261994	   
df.mm.trans1:probe21	-0.0570077093095343	0.100379921745321	-0.567919443633076	0.570243261694528	   
df.mm.trans1:probe22	0.0125523951500100	0.100379921745321	0.125048863674723	0.900515146475954	   
df.mm.trans2:probe2	-0.0587552825455124	0.100379921745321	-0.585329033176411	0.558485595466036	   
df.mm.trans2:probe3	0.0277449665436854	0.100379921745321	0.276399563391558	0.782310002249246	   
df.mm.trans2:probe4	0.0542220668962511	0.100379921745321	0.540168451553696	0.5892257702069	   
df.mm.trans2:probe5	-0.159536172267015	0.100379921745321	-1.58932353694978	0.112368181945453	   
df.mm.trans2:probe6	-0.075143996157484	0.100379921745321	-0.748595883030631	0.454312890164483	   
df.mm.trans3:probe2	0.0576686235497087	0.100379921745321	0.574503571501309	0.565782755043529	   
df.mm.trans3:probe3	0.028481215332808	0.100379921745321	0.283734185458614	0.776684854931263	   
df.mm.trans3:probe4	0.0461147885318103	0.100379921745321	0.459402515264064	0.646065438136526	   
df.mm.trans3:probe5	0.114587001326473	0.100379921745321	1.14153308086051	0.253977383488568	   
df.mm.trans3:probe6	-0.0125888372192668	0.100379921745321	-0.125411905093995	0.900227833057768	   
df.mm.trans3:probe7	0.0774595067777732	0.100379921745321	0.771663350906965	0.440533479929989	   
df.mm.trans3:probe8	-0.0303088342397941	0.100379921745321	-0.301941202113031	0.762772525500523	   
df.mm.trans3:probe9	0.0166758341860856	0.100379921745321	0.166127188546677	0.868097316262