chr6.19917_chr6_124297784_124302876_+_2.R 

fitVsDatCorrelation=0.773774675259558
cont.fitVsDatCorrelation=0.247941131036719

fstatistic=12535.7522478844,62,922
cont.fstatistic=5351.23229732159,62,922

residuals=-0.385292025721877,-0.088370421767752,-0.00476481899764354,0.0846182553549809,0.661659164977315
cont.residuals=-0.575420189548152,-0.156270985761006,-0.0233961773844364,0.147731961359565,0.896871842890543

predictedValues:
Include	Exclude	Both
chr6.19917_chr6_124297784_124302876_+_2.R.tl.Lung	56.3214417255259	67.9548374727919	61.8937024083385
chr6.19917_chr6_124297784_124302876_+_2.R.tl.cerebhem	58.2702935795526	65.8942262719761	52.7479437244431
chr6.19917_chr6_124297784_124302876_+_2.R.tl.cortex	55.7334739296402	60.6952958515842	56.9139890350071
chr6.19917_chr6_124297784_124302876_+_2.R.tl.heart	58.7147581393016	63.8047595084829	62.0144716583902
chr6.19917_chr6_124297784_124302876_+_2.R.tl.kidney	57.1877204000318	67.0399276612122	57.2990769710168
chr6.19917_chr6_124297784_124302876_+_2.R.tl.liver	61.444098064779	67.5762180629236	61.5841748697362
chr6.19917_chr6_124297784_124302876_+_2.R.tl.stomach	60.6527771456668	68.0314643659679	74.6577823477175
chr6.19917_chr6_124297784_124302876_+_2.R.tl.testicle	57.9586299109672	58.2236976804738	59.5617811079596


diffExp=-11.6333957472660,-7.62393269242345,-4.96182192194398,-5.09000136918129,-9.85220726118037,-6.13211999814455,-7.37868722030115,-0.265067769506572
diffExpScore=0.98145993173525
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=-1,0,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	59.2798422744597	61.0182179911607	59.8930438956614
cerebhem	62.038771032971	59.9473373618137	66.845979760345
cortex	57.9970957886877	58.2661878641193	58.3381652958783
heart	62.0337175470198	58.6380235875442	54.8038024848447
kidney	59.6241825439089	57.062174948734	65.786080614472
liver	61.1666422749295	62.8985883866669	65.4056085649988
stomach	60.3178976391254	56.7864439858041	61.1986318808287
testicle	58.4354876974485	64.710887901941	60.5647619051396
cont.diffExp=-1.73837571670091,2.09143367115730,-0.269092075431629,3.39569395947568,2.56200759517497,-1.73194611173742,3.53145365332126,-6.2754002044925
cont.diffExpScore=8.41671811319516

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=0.389925831339803
cont.tran.correlation=-0.130200036215232

tran.covariance=0.000755706975106404
cont.tran.covariance=-0.000148108960178676

tran.mean=61.5939762356799
cont.tran.mean=60.0138436766459

weightedLogRatios:
wLogRatio
Lung	-0.774535441519564
cerebhem	-0.507396663868667
cortex	-0.346533086752438
heart	-0.34204585665967
kidney	-0.655794718767459
liver	-0.396275320617296
stomach	-0.477883126805296
testicle	-0.0185348335895394

cont.weightedLogRatios:
wLogRatio
Lung	-0.118408158608924
cerebhem	0.140965509141021
cortex	-0.0188063556534082
heart	0.230781916209723
kidney	0.178582265501941
liver	-0.115248741784495
stomach	0.245515742206876
testicle	-0.420155615801128

varWeightedLogRatios=0.051762064399129
cont.varWeightedLogRatios=0.0525128942395379

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.04404578540784	0.0771996897720134	52.3842232702066	1.33228221434991e-278	***
df.mm.trans1	-0.190168437029157	0.0698477883240121	-2.72261214839041	0.00659906608459825	** 
df.mm.trans2	0.164501524184286	0.0635442731345899	2.58877025528112	0.00978362792185346	** 
df.mm.exp2	0.163118249834815	0.0868321945289524	1.87854574814905	0.0606218798152582	.  
df.mm.exp3	-0.0395942362225921	0.0868321945289524	-0.455985667958562	0.648507663406753	   
df.mm.exp4	-0.0233490757574503	0.0868321945289524	-0.26889883279024	0.788067693230425	   
df.mm.exp5	0.0788428555737574	0.0868321945289524	0.907991051031987	0.364120210447758	   
df.mm.exp6	0.0864787644718252	0.0868321945289524	0.995929734828833	0.319545586695508	   
df.mm.exp7	-0.112279239918328	0.0868321945289524	-1.29306002833881	0.196314197425573	   
df.mm.exp8	-0.0874923883461735	0.0868321945289524	-1.00760309952780	0.313909397122009	   
df.mm.trans1:exp2	-0.129101140771930	0.0842396022934237	-1.53254689311381	0.125730571669485	   
df.mm.trans2:exp2	-0.193910755355677	0.0719332547703942	-2.69570389904678	0.00715192949904605	** 
df.mm.trans1:exp3	0.0290998605210599	0.0842396022934237	0.345441570577448	0.729841225673655	   
df.mm.trans2:exp3	-0.0733828967572754	0.0719332547703942	-1.02015259828724	0.307923696264980	   
df.mm.trans1:exp4	0.0649648769923046	0.0842396022934237	0.771191639367179	0.440790936244246	   
df.mm.trans2:exp4	-0.039666465943554	0.0719332547703942	-0.551434327143496	0.581469584955602	   
df.mm.trans1:exp5	-0.0635789688976665	0.0842396022934237	-0.754739661236861	0.450597936970766	   
df.mm.trans2:exp5	-0.0923978081554238	0.0719332547703942	-1.28449363858692	0.199291924415438	   
df.mm.trans1:exp6	0.000573712074473546	0.0842396022934237	0.00681047938088774	0.994567538912625	   
df.mm.trans2:exp6	-0.0920659768390013	0.0719332547703942	-1.27988059393210	0.200909074650099	   
df.mm.trans1:exp7	0.186369353624186	0.0842396022934237	2.21237219253509	0.0271853769043331	*  
df.mm.trans2:exp7	0.113406219625109	0.0719332547703941	1.57654787048207	0.115242624385879	   
df.mm.trans1:exp8	0.116146556650276	0.0842396022934237	1.37876430429614	0.168301841928025	   
df.mm.trans2:exp8	-0.0670584928656181	0.0719332547703942	-0.932232151591973	0.351460608240166	   
df.mm.trans1:probe2	0.139906695379205	0.0421198011467118	3.32163712957433	0.000930074624659027	***
df.mm.trans1:probe3	0.460493843892454	0.0421198011467119	10.9329538923619	3.022485557326e-26	***
df.mm.trans1:probe4	0.345328338005353	0.0421198011467118	8.1987171972276	8.09610137212812e-16	***
df.mm.trans1:probe5	-0.112321375522427	0.0421198011467119	-2.66671191374311	0.00779390209553413	** 
df.mm.trans1:probe6	0.0697310433923853	0.0421198011467118	1.65554066006860	0.0981551704242898	.  
df.mm.trans1:probe7	0.275001423566104	0.0421198011467119	6.52902948445122	1.09186084040808e-10	***
df.mm.trans1:probe8	0.0878724680850966	0.0421198011467118	2.08625078212072	0.0372302438195631	*  
df.mm.trans1:probe9	-0.0804814336911073	0.0421198011467119	-1.91077430329678	0.0563434938357694	.  
df.mm.trans1:probe10	0.06699617477868	0.0421198011467118	1.59060994958924	0.112040179409130	   
df.mm.trans1:probe11	0.472736483432681	0.0421198011467118	11.2236162223569	1.72322541999078e-27	***
df.mm.trans1:probe12	0.436405400044365	0.0421198011467118	10.3610508160824	7.1696878053952e-24	***
df.mm.trans1:probe13	0.366821209488689	0.0421198011467118	8.7089967070589	1.39968337398719e-17	***
df.mm.trans1:probe14	0.383970795715286	0.0421198011467118	9.1161587961405	4.75659978486823e-19	***
df.mm.trans1:probe15	0.466732343186187	0.0421198011467118	11.0810671104658	7.07135090338755e-27	***
df.mm.trans1:probe16	0.200817933018393	0.0421198011467118	4.76777970339659	2.16374626373308e-06	***
df.mm.trans1:probe17	0.221337244756278	0.0421198011467119	5.25494515003323	1.84002750744626e-07	***
df.mm.trans1:probe18	0.237976636719362	0.0421198011467118	5.64999430767587	2.13769925290257e-08	***
df.mm.trans1:probe19	0.165674092396050	0.0421198011467119	3.93340158038671	9.00346276630512e-05	***
df.mm.trans1:probe20	-0.0156923361517767	0.0421198011467118	-0.372564345617804	0.709558336771586	   
df.mm.trans1:probe21	-0.0334441440581266	0.0421198011467119	-0.794024262878969	0.427385617990837	   
df.mm.trans1:probe22	0.417409565083706	0.0421198011467119	9.91005545419798	4.5565545659861e-22	***
df.mm.trans1:probe23	0.0288591089178972	0.0421198011467118	0.68516726414199	0.493410594412348	   
df.mm.trans1:probe24	0.212124974609777	0.0421198011467119	5.03622925167435	5.71085832695783e-07	***
df.mm.trans1:probe25	0.132638246838348	0.0421198011467118	3.14907105986426	0.00169062173373558	** 
df.mm.trans1:probe26	0.457707480032621	0.0421198011467119	10.8668005919195	5.75524460074463e-26	***
df.mm.trans1:probe27	0.0648722146283622	0.0421198011467118	1.54018330719082	0.123858791739534	   
df.mm.trans1:probe28	0.342285014600679	0.0421198011467118	8.12646321402209	1.41458588994766e-15	***
df.mm.trans1:probe29	0.283168517776852	0.0421198011467118	6.72293102216979	3.11850885175124e-11	***
df.mm.trans1:probe30	0.138522289393049	0.0421198011467118	3.28876883607659	0.00104435699571701	** 
df.mm.trans1:probe31	-0.0653930016769026	0.0421198011467118	-1.55254773043979	0.120874390504959	   
df.mm.trans1:probe32	0.0338714220733255	0.0421198011467119	0.804168613126744	0.421506894392736	   
df.mm.trans2:probe2	0.0339580669976323	0.0421198011467118	0.806225719806925	0.420320606373242	   
df.mm.trans2:probe3	0.00833988592283859	0.0421198011467118	0.198003924419991	0.843085639875188	   
df.mm.trans2:probe4	0.0096188070945435	0.0421198011467118	0.228367818286682	0.819410943753032	   
df.mm.trans2:probe5	-0.0784269965817376	0.0421198011467119	-1.86199826320548	0.0629213006237053	.  
df.mm.trans2:probe6	0.119174417679025	0.0421198011467119	2.82941548712247	0.00476452535963993	** 
df.mm.trans3:probe2	0.298242288437276	0.0421198011467118	7.08080950806101	2.84052398840865e-12	***
df.mm.trans3:probe3	0.0228764029598871	0.0421198011467119	0.543127040894706	0.587173611407278	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.05050415885186	0.118064324867306	34.3076044639588	6.86765729530622e-167	***
df.mm.trans1	0.0303265669389397	0.106820791590001	0.283901349985675	0.776549722606686	   
df.mm.trans2	0.0622686886977687	0.0971805939761533	0.640752295803507	0.521842850360907	   
df.mm.exp2	-0.0820465942257487	0.132795668662438	-0.617840890837397	0.53683279803354	   
df.mm.exp3	-0.0417230474165685	0.132795668662438	-0.314189821376079	0.753447949580383	   
df.mm.exp4	0.0944204157947907	0.132795668662438	0.711020297166497	0.477251486074471	   
df.mm.exp5	-0.155086999766013	0.132795668662438	-1.16786188381067	0.243164390202072	   
df.mm.exp6	-0.0263637370546082	0.132795668662438	-0.198528591483084	0.842675283606666	   
df.mm.exp7	-0.0760797554459728	0.132795668662438	-0.572908410434415	0.566846396214322	   
df.mm.exp8	0.0332581786059685	0.132795668662438	0.250446260340837	0.802298054460848	   
df.mm.trans1:exp2	0.127536802772159	0.128830722004649	0.98995643886523	0.322455133575749	   
df.mm.trans2:exp2	0.0643405852204887	0.110010172127056	0.584860326790316	0.558784729176666	   
df.mm.trans1:exp3	0.0198466638034392	0.128830722004649	0.154052259388277	0.87760224275831	   
df.mm.trans2:exp3	-0.00442747067629773	0.110010172127056	-0.0402460117159371	0.96790570820759	   
df.mm.trans1:exp4	-0.0490116674659004	0.128830722004649	-0.38043462540039	0.703710443074879	   
df.mm.trans2:exp4	-0.134209538130554	0.110010172127056	-1.21997389455540	0.222786727712919	   
df.mm.trans1:exp5	0.16087891862809	0.128830722004649	1.24876206641366	0.212069084346346	   
df.mm.trans2:exp5	0.0880559865198423	0.110010172127056	0.800434949034918	0.423665034186224	   
df.mm.trans1:exp6	0.0576963968090084	0.128830722004649	0.447846568824836	0.654369138425427	   
df.mm.trans2:exp6	0.0567149831484126	0.110010172127056	0.515543081624397	0.606297163271979	   
df.mm.trans1:exp7	0.0934393047784615	0.128830722004649	0.72528744172597	0.468459745517409	   
df.mm.trans2:exp7	0.00420491528955454	0.110010172127056	0.0382229680060686	0.96951818275523	   
df.mm.trans1:exp8	-0.0476041275708811	0.128830722004649	-0.369509126628687	0.711833120062916	   
df.mm.trans2:exp8	0.0254988164394030	0.110010172127056	0.23178598802621	0.816755672959485	   
df.mm.trans1:probe2	0.0200150288053286	0.0644153610023245	0.310718258717922	0.756085044101035	   
df.mm.trans1:probe3	-0.038219149451995	0.0644153610023245	-0.593323531177848	0.553110167861099	   
df.mm.trans1:probe4	0.0707619849221664	0.0644153610023245	1.09852655983117	0.272261404639486	   
df.mm.trans1:probe5	0.0272003763927406	0.0644153610023245	0.422265372257388	0.672929778105412	   
df.mm.trans1:probe6	-0.0716450678477715	0.0644153610023245	-1.11223575763529	0.266326714846477	   
df.mm.trans1:probe7	0.0138661334851115	0.0644153610023245	0.215261286583663	0.829611217143583	   
df.mm.trans1:probe8	0.0136812521101265	0.0644153610023245	0.212391142380352	0.83184884070156	   
df.mm.trans1:probe9	-0.00532170251242059	0.0644153610023245	-0.0826154263457213	0.934175266525607	   
df.mm.trans1:probe10	-0.000103995508809006	0.0644153610023245	-0.00161445200633516	0.998712203462188	   
df.mm.trans1:probe11	0.0120568910997561	0.0644153610023245	0.187174160202580	0.851565263517316	   
df.mm.trans1:probe12	0.00725073716932978	0.0644153610023245	0.112562237585971	0.910402126624352	   
df.mm.trans1:probe13	-0.00734122107115835	0.0644153610023245	-0.113966932062888	0.909288818476989	   
df.mm.trans1:probe14	0.0680573332103806	0.0644153610023245	1.05653887755010	0.290998839457842	   
df.mm.trans1:probe15	-0.00426153736736383	0.0644153610023245	-0.0661571603582264	0.947267045209621	   
df.mm.trans1:probe16	-0.103381807864306	0.0644153610023245	-1.60492476104536	0.108852807887318	   
df.mm.trans1:probe17	0.0753377565290751	0.0644153610023245	1.16956197026291	0.242479544650901	   
df.mm.trans1:probe18	0.0644976373412931	0.0644153610023245	1.00127727824060	0.316955479544627	   
df.mm.trans1:probe19	0.0146348773147048	0.0644153610023245	0.227195455974804	0.820322126850572	   
df.mm.trans1:probe20	-0.0287876678096768	0.0644153610023245	-0.446906876895992	0.655047254803003	   
df.mm.trans1:probe21	-0.00751293750272362	0.0644153610023246	-0.116632700427659	0.907176522803158	   
df.mm.trans1:probe22	-0.032539761105103	0.0644153610023245	-0.505155301449428	0.613570486644972	   
df.mm.trans1:probe23	0.0151411296245859	0.0644153610023245	0.235054642075816	0.814218516099005	   
df.mm.trans1:probe24	-0.0166075966433198	0.0644153610023245	-0.257820438865824	0.796603023035547	   
df.mm.trans1:probe25	-0.092502041523853	0.0644153610023245	-1.43602457681662	0.151334534452841	   
df.mm.trans1:probe26	-0.0828362754525053	0.0644153610023245	-1.28597083309858	0.198776097874534	   
df.mm.trans1:probe27	0.0232158261609568	0.0644153610023245	0.360408228716114	0.718624422572566	   
df.mm.trans1:probe28	0.0245649384162972	0.0644153610023245	0.381352181126652	0.70302980008366	   
df.mm.trans1:probe29	-0.0149452344727709	0.0644153610023245	-0.232013517276285	0.816579000205875	   
df.mm.trans1:probe30	0.087106700560314	0.0644153610023245	1.35226596893823	0.176621825384947	   
df.mm.trans1:probe31	0.00619241895117613	0.0644153610023245	0.0961326437486342	0.923436115908016	   
df.mm.trans1:probe32	0.0127757817588742	0.0644153610023245	0.198334396642025	0.842827163650728	   
df.mm.trans2:probe2	0.0197166300464488	0.0644153610023245	0.306085842563814	0.759608387018912	   
df.mm.trans2:probe3	-0.0653617628462187	0.0644153610023245	-1.01469217635619	0.310518779868997	   
df.mm.trans2:probe4	-0.000384236389477547	0.0644153610023245	-0.00596498076698944	0.99524195251211	   
df.mm.trans2:probe5	0.0217716474424821	0.0644153610023246	0.337988441013262	0.735448839446778	   
df.mm.trans2:probe6	0.00985437039674933	0.0644153610023245	0.152981683924642	0.87844619228481	   
df.mm.trans3:probe2	-0.134376789451143	0.0644153610023245	-2.08609852308821	0.0372440652943791	*  
df.mm.trans3:probe3	-0.0172403447407325	0.0644153610023245	-0.267643376866433	0.789033698406395