chr2.13466_chr2_111536863_111545559_+_2.R 

fitVsDatCorrelation=0.84350284945289
cont.fitVsDatCorrelation=0.23604283563486

fstatistic=10549.7499413551,58,830
cont.fstatistic=3213.28134698716,58,830

residuals=-0.578342296084075,-0.0884756860974938,-0.00881022229234901,0.0843509745163222,0.718566366389718
cont.residuals=-0.502358651935437,-0.180465893114708,-0.0546539493340839,0.107479113093885,1.48583973722274

predictedValues:
Include	Exclude	Both
chr2.13466_chr2_111536863_111545559_+_2.R.tl.Lung	51.8436666302357	40.4492314581808	53.1821901671222
chr2.13466_chr2_111536863_111545559_+_2.R.tl.cerebhem	57.3368894491281	45.3189317662165	55.1430187066866
chr2.13466_chr2_111536863_111545559_+_2.R.tl.cortex	50.7095471420089	41.8187644318195	53.2698682420087
chr2.13466_chr2_111536863_111545559_+_2.R.tl.heart	52.0426060677284	42.6219780185743	57.9855470133076
chr2.13466_chr2_111536863_111545559_+_2.R.tl.kidney	61.471688095179	66.94319803499	104.128341999173
chr2.13466_chr2_111536863_111545559_+_2.R.tl.liver	52.7283872326291	44.0728561161573	52.0675729120281
chr2.13466_chr2_111536863_111545559_+_2.R.tl.stomach	53.6140670209272	42.0058164386051	54.3044582121641
chr2.13466_chr2_111536863_111545559_+_2.R.tl.testicle	54.1750127611048	43.8174921576158	53.1874814283152


diffExp=11.3944351720550,12.0179576829116,8.89078271018937,9.42062804915405,-5.471509939811,8.65553111647186,11.6082505823221,10.357520603489
diffExpScore=1.14649319424631
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=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=1,1,1,1,0,0,1,1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	53.5588490002213	49.8477904449548	56.0548502398016
cerebhem	54.8800487714588	49.1492089891273	53.8247284376921
cortex	57.5904737965431	52.317970093717	51.5259881137703
heart	51.2388103258755	50.3668409899033	56.0430638515904
kidney	54.5065212889486	47.6276345195669	54.8075360927991
liver	54.8408403999821	51.6172792094735	55.7585484761442
stomach	52.6327063642225	50.7963207801428	51.7479057223096
testicle	52.9568103249211	49.741980318956	53.252244617318
cont.diffExp=3.7110585552665,5.73083978233151,5.27250370282611,0.871969335972253,6.87888676938175,3.22356119050853,1.83638558407969,3.21483000596513
cont.diffExpScore=0.968494048531421

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=0.889366152382257
cont.tran.correlation=0.304457756434193

tran.covariance=0.00908788281692356
cont.tran.covariance=0.000288070476712380

tran.mean=50.0606333013188
cont.tran.mean=52.1043803511259

weightedLogRatios:
wLogRatio
Lung	0.94909475755864
cerebhem	0.924725941068028
cortex	0.738253353951212
heart	0.76925946896821
kidney	-0.354817092042814
liver	0.694915274337115
stomach	0.941806644671817
testicle	0.824584271733553

cont.weightedLogRatios:
wLogRatio
Lung	0.28326927095424
cerebhem	0.435642607759225
cortex	0.384582592230643
heart	0.0674195895189288
kidney	0.530302231905043
liver	0.240748565558208
stomach	0.140122545097436
testicle	0.246637028734798

varWeightedLogRatios=0.186270545095409
cont.varWeightedLogRatios=0.0234642755065476

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.68922025484120	0.0710093889821758	51.9539783079565	4.2783483872264e-263	***
df.mm.trans1	0.320531890924261	0.0614762592142346	5.21391338739822	2.3358290903965e-07	***
df.mm.trans2	-0.0151737690952539	0.0544643284921429	-0.278600131780618	0.78062110591636	   
df.mm.exp2	0.178182072332516	0.070393392281923	2.53123292622272	0.0115498286335676	*  
df.mm.exp3	0.00953164673033358	0.070393392281923	0.135405418340399	0.892324171127615	   
df.mm.exp4	-0.0303178771610256	0.070393392281923	-0.430692088819978	0.666804090122813	   
df.mm.exp5	0.00224013211399819	0.070393392281923	0.0318230453367916	0.974620819061548	   
df.mm.exp6	0.123898845188219	0.070393392281923	1.76009197982686	0.0787605227545317	.  
df.mm.exp7	0.0504563926541273	0.070393392281923	0.716777399390716	0.47371310130469	   
df.mm.exp8	0.123872973988466	0.070393392281923	1.75972445669842	0.0788228921817817	.  
df.mm.trans1:exp2	-0.0774706401278758	0.0652564211678411	-1.18717267575277	0.235499170986452	   
df.mm.trans2:exp2	-0.0645048508898941	0.0489917276157506	-1.31664781033678	0.188320139450997	   
df.mm.trans1:exp3	-0.031650226604857	0.0652564211678411	-0.485013214614571	0.627794952570054	   
df.mm.trans2:exp3	0.0237658583963895	0.0489917276157506	0.485099414798936	0.627733834051875	   
df.mm.trans1:exp4	0.0341478284241725	0.0652564211678411	0.523286870671983	0.600914308105152	   
df.mm.trans2:exp4	0.0826402698002118	0.0489917276157506	1.68682089450635	0.09201356285646	.  
df.mm.trans1:exp5	0.168103801233380	0.0652564211678411	2.57604996144383	0.0101654671980950	*  
df.mm.trans2:exp5	0.501556693650554	0.0489917276157506	10.2375792416291	3.02686125416901e-23	***
df.mm.trans1:exp6	-0.106977656791665	0.0652564211678411	-1.63934299302923	0.101520789960851	   
df.mm.trans2:exp6	-0.0381024033343427	0.0489917276157506	-0.777731367899199	0.436949020332734	   
df.mm.trans1:exp7	-0.0168776938823073	0.0652564211678411	-0.258636523123103	0.79597982406863	   
df.mm.trans2:exp7	-0.0126959408519390	0.0489917276157506	-0.259144583581847	0.795587943663084	   
df.mm.trans1:exp8	-0.0798859703053902	0.0652564211678411	-1.22418558780478	0.221229590596497	   
df.mm.trans2:exp8	-0.0438875155278912	0.0489917276157506	-0.895814817393407	0.370611399812069	   
df.mm.trans1:probe2	0.0147753837659984	0.0437753381098947	0.337527576118450	0.735804568638375	   
df.mm.trans1:probe3	-0.259117863746116	0.0437753381098947	-5.9192658454315	4.72929562131535e-09	***
df.mm.trans1:probe4	-0.00254489499646948	0.0437753381098947	-0.0581353590023843	0.953654802510544	   
df.mm.trans1:probe5	0.407113308142010	0.0437753381098947	9.30006084978677	1.21381744549972e-19	***
df.mm.trans1:probe6	0.345994025197813	0.0437753381098947	7.90385728898817	8.58833579915245e-15	***
df.mm.trans1:probe7	0.0565553623019663	0.0437753381098947	1.29194575630663	0.196735539939473	   
df.mm.trans1:probe8	0.309225764326104	0.0437753381098947	7.06392634934802	3.42711175774844e-12	***
df.mm.trans1:probe9	-0.114525182111636	0.0437753381098947	-2.61620325636615	0.00905295439102284	** 
df.mm.trans1:probe10	0.201752814235147	0.0437753381098947	4.60882366524871	4.68630995680908e-06	***
df.mm.trans1:probe11	-0.238889043225235	0.0437753381098947	-5.45716043644305	6.39054969301255e-08	***
df.mm.trans1:probe12	-0.260246562963713	0.0437753381098947	-5.94504975176626	4.06775403738579e-09	***
df.mm.trans1:probe13	-0.23141598106059	0.0437753381098947	-5.28644645712702	1.59564883948467e-07	***
df.mm.trans1:probe14	-0.231939428128304	0.0437753381098947	-5.29840403621869	1.49782522012633e-07	***
df.mm.trans1:probe15	-0.176273455092910	0.0437753381098947	-4.02677541062936	6.17271423590571e-05	***
df.mm.trans1:probe16	-0.30520322940137	0.0437753381098947	-6.97203591289644	6.37481281806946e-12	***
df.mm.trans1:probe17	-0.216855027602052	0.0437753381098947	-4.95381730822167	8.81961309650948e-07	***
df.mm.trans1:probe18	-0.258328635905963	0.0437753381098947	-5.90123679359023	5.25301828860691e-09	***
df.mm.trans1:probe19	-0.230116684448657	0.0437753381098947	-5.25676543881778	1.86596736865208e-07	***
df.mm.trans1:probe20	-0.24641948124191	0.0437753381098947	-5.62918510471107	2.47719751507946e-08	***
df.mm.trans1:probe21	-0.253235181071778	0.0437753381098947	-5.78488235627216	1.02770113606343e-08	***
df.mm.trans1:probe22	-0.217406367627855	0.0437753381098947	-4.96641207161148	8.28140212236725e-07	***
df.mm.trans2:probe2	0.099654419750168	0.0437753381098947	2.27649685994413	0.0230701408359602	*  
df.mm.trans2:probe3	0.117563287660054	0.0437753381098947	2.68560547413523	0.00738441548915809	** 
df.mm.trans2:probe4	0.0471280023382407	0.0437753381098947	1.07658796877661	0.281977200575659	   
df.mm.trans2:probe5	0.0309769420896699	0.0437753381098947	0.707634559255822	0.479370872993788	   
df.mm.trans2:probe6	0.094694714866298	0.0437753381098947	2.16319779480798	0.0308107873165538	*  
df.mm.trans3:probe2	-0.0231674063425464	0.0437753381098947	-0.529234206812666	0.596784499761437	   
df.mm.trans3:probe3	0.200628966259832	0.0437753381098947	4.58315058026892	5.28421377215878e-06	***
df.mm.trans3:probe4	-0.0407090651497187	0.0437753381098947	-0.929954328337148	0.352665117230415	   
df.mm.trans3:probe5	0.0644766909341768	0.0437753381098947	1.47289989565159	0.141157134796573	   
df.mm.trans3:probe6	-0.0832879920390999	0.0437753381098947	-1.90262361492244	0.0574355073678737	.  
df.mm.trans3:probe7	-0.0876569843622425	0.0437753381098947	-2.00242849392017	0.0455635466907057	*  
df.mm.trans3:probe8	-0.186197140444363	0.0437753381098947	-4.25347121196253	2.34429707324917e-05	***
df.mm.trans3:probe9	-0.0317803378475765	0.0437753381098947	-0.725987261772697	0.468051240682433	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.90531168061098	0.128467098870170	30.3993140263696	5.17538145498752e-137	***
df.mm.trans1	0.10615987808575	0.111220175019753	0.954501987313866	0.340107506341889	   
df.mm.trans2	-0.0126138253625148	0.0985344948546714	-0.128014309923839	0.898168658059669	   
df.mm.exp2	0.0508531047117467	0.127352664425242	0.399309311204858	0.689768029352249	   
df.mm.exp3	0.205186250988375	0.127352664425242	1.61116574917695	0.107523787364218	   
df.mm.exp4	-0.0337146138889295	0.127352664425242	-0.264734264030421	0.791279906844645	   
df.mm.exp5	-0.00551872543269206	0.127352664425242	-0.0433341968744726	0.965445554205766	   
df.mm.exp6	0.0638364074147434	0.127352664425242	0.501256944272387	0.61632321598085	   
df.mm.exp7	0.0813531625938334	0.127352664425242	0.638802203008397	0.523127848342914	   
df.mm.exp8	0.0378614545697116	0.127352664425242	0.297296132284197	0.76631482363509	   
df.mm.trans1:exp2	-0.0264842632800916	0.11805907965476	-0.224330592424908	0.82255528347704	   
df.mm.trans2:exp2	-0.0649665234127236	0.088633703312289	-0.732977648286034	0.463779015513774	   
df.mm.trans1:exp3	-0.132610113119240	0.11805907965476	-1.12325213365233	0.261655215137451	   
df.mm.trans2:exp3	-0.156820513847436	0.0886337033122889	-1.76931018322567	0.0772092876851617	.  
df.mm.trans1:exp4	-0.0105691577143425	0.118059079654760	-0.0895243105845808	0.928686831602495	   
df.mm.trans2:exp4	0.0440734842245959	0.0886337033122889	0.497254233745699	0.61914147467871	   
df.mm.trans1:exp5	0.0230580459432163	0.11805907965476	0.195309382477357	0.845198552904584	   
df.mm.trans2:exp5	-0.040042296006654	0.0886337033122889	-0.451772796467393	0.65155069765858	   
df.mm.trans1:exp6	-0.0401822589361202	0.11805907965476	-0.340357209742996	0.733673660617071	   
df.mm.trans2:exp6	-0.0289540939348675	0.0886337033122889	-0.326671377284684	0.743998808942556	   
df.mm.trans1:exp7	-0.0987964727656769	0.118059079654760	-0.836839259247043	0.402923798913426	   
df.mm.trans2:exp7	-0.0625034075723784	0.0886337033122889	-0.705187814979997	0.480891209448633	   
df.mm.trans1:exp8	-0.0491658034368367	0.11805907965476	-0.416450844616206	0.677187797865458	   
df.mm.trans2:exp8	-0.0399863749305215	0.088633703312289	-0.451141873082239	0.652005141683976	   
df.mm.trans1:probe2	-0.0786145245347314	0.0791964382407316	-0.992652274282445	0.321168734912882	   
df.mm.trans1:probe3	-0.0579732840619057	0.0791964382407316	-0.732018830009571	0.464363713651237	   
df.mm.trans1:probe4	-0.0338468154014269	0.0791964382407317	-0.427378000239651	0.66921487775457	   
df.mm.trans1:probe5	-0.0405099718598677	0.0791964382407316	-0.511512547278079	0.609128254603482	   
df.mm.trans1:probe6	-0.0735038986496318	0.0791964382407316	-0.928121267603015	0.353614487360551	   
df.mm.trans1:probe7	0.0382965623860445	0.0791964382407316	0.483564201077266	0.628822729247831	   
df.mm.trans1:probe8	-0.00314349100611998	0.0791964382407316	-0.0396923280383491	0.968347963386324	   
df.mm.trans1:probe9	-0.0591151198720368	0.0791964382407316	-0.746436597215974	0.455615086231291	   
df.mm.trans1:probe10	-0.088801527961624	0.0791964382407316	-1.12128183961627	0.262492214346784	   
df.mm.trans1:probe11	-0.0365564349102453	0.0791964382407317	-0.461591906433034	0.644494948002533	   
df.mm.trans1:probe12	0.0196716071519646	0.0791964382407317	0.248390048706095	0.8038940751517	   
df.mm.trans1:probe13	0.114446776738995	0.0791964382407317	1.44510004845310	0.148807211630114	   
df.mm.trans1:probe14	-0.0553462078294719	0.0791964382407317	-0.698847183774064	0.48484330897819	   
df.mm.trans1:probe15	-0.101489208022455	0.0791964382407316	-1.28148702488312	0.200380539508188	   
df.mm.trans1:probe16	0.0632515259074438	0.0791964382407317	0.798666295006595	0.4247124032343	   
df.mm.trans1:probe17	-0.0572361699741747	0.0791964382407317	-0.72271141538203	0.470060787905588	   
df.mm.trans1:probe18	-0.0476035355552436	0.0791964382407317	-0.6010817735331	0.547949636053065	   
df.mm.trans1:probe19	-0.130994654235046	0.0791964382407317	-1.65404729233989	0.098496006921025	.  
df.mm.trans1:probe20	-0.156250743553506	0.0791964382407316	-1.97295165066078	0.0488325175943559	*  
df.mm.trans1:probe21	-0.117080440060678	0.0791964382407316	-1.47835486874790	0.139692195024626	   
df.mm.trans1:probe22	-0.0490068132661603	0.0791964382407317	-0.618800723300149	0.536217434140333	   
df.mm.trans2:probe2	0.0851272166042702	0.0791964382407317	1.07488693298947	0.282737719436406	   
df.mm.trans2:probe3	0.0431652576054813	0.0791964382407317	0.545040390254329	0.585872159165454	   
df.mm.trans2:probe4	0.0831767961168376	0.0791964382407317	1.05025930413697	0.293904605693017	   
df.mm.trans2:probe5	0.0477008622652722	0.0791964382407317	0.602310701401456	0.547131844844275	   
df.mm.trans2:probe6	-0.0150253910330531	0.0791964382407317	-0.189723065415906	0.849572532487185	   
df.mm.trans3:probe2	0.0591539187727605	0.0791964382407316	0.746926504358083	0.455319454516984	   
df.mm.trans3:probe3	0.0796363727150907	0.0791964382407316	1.00555497802845	0.314922747659509	   
df.mm.trans3:probe4	0.05723672816331	0.0791964382407316	0.722718463541615	0.470056459136971	   
df.mm.trans3:probe5	0.053647531040809	0.0791964382407316	0.677398279929431	0.498342055180462	   
df.mm.trans3:probe6	-0.0520803793974384	0.0791964382407316	-0.657610121797787	0.5109710153811	   
df.mm.trans3:probe7	0.0297829336016945	0.0791964382407316	0.376064053678323	0.706965378032137	   
df.mm.trans3:probe8	0.00428321993937813	0.0791964382407316	0.0540834920676423	0.956881659124777	   
df.mm.trans3:probe9	0.0155961945866916	0.0791964382407317	0.196930505123024	0.843930132948292