chr1.955_chr1_91732587_91735269_+_2.R 

fitVsDatCorrelation=0.958945015656734
cont.fitVsDatCorrelation=0.263098792366442

fstatistic=6700.23976765979,51,669
cont.fstatistic=566.953572430098,51,669

residuals=-0.826454126899696,-0.106653624534548,-0.00412424869800457,0.104085959702442,0.943034798901567
cont.residuals=-1.46410162083361,-0.585372043432267,-0.207687329237702,0.61462822240816,1.72151631830240

predictedValues:
Include	Exclude	Both
chr1.955_chr1_91732587_91735269_+_2.R.tl.Lung	131.491293945201	151.808741988148	67.7504586076184
chr1.955_chr1_91732587_91735269_+_2.R.tl.cerebhem	107.155575871682	91.4816358463016	58.6749844477692
chr1.955_chr1_91732587_91735269_+_2.R.tl.cortex	121.595129237059	126.561595360426	67.2276852161675
chr1.955_chr1_91732587_91735269_+_2.R.tl.heart	135.530885039340	137.244869372277	71.4417568371168
chr1.955_chr1_91732587_91735269_+_2.R.tl.kidney	131.908696800678	147.182861362036	86.1257690397306
chr1.955_chr1_91732587_91735269_+_2.R.tl.liver	134.490460526364	128.549071017958	81.317816485844
chr1.955_chr1_91732587_91735269_+_2.R.tl.stomach	135.636121317657	145.947764383695	72.1534740834562
chr1.955_chr1_91732587_91735269_+_2.R.tl.testicle	120.875525699249	117.191047153966	65.0835867539207


diffExp=-20.3174480429471,15.6739400253806,-4.96646612336656,-1.71398433293726,-15.2741645613582,5.94138950840556,-10.3116430660384,3.68447854528324
diffExpScore=2.75363438500253
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=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	115.466990873035	66.3872953695478	112.682473552656
cerebhem	90.7635869290824	63.1888864108718	98.0910556465678
cortex	97.2638045855395	109.805516329107	84.2561304812238
heart	111.070516799849	87.7254023754071	101.964706665592
kidney	123.880296733437	92.945799474677	86.6837959235413
liver	116.699015291491	82.413744539196	98.1868770695185
stomach	98.7150701036374	86.5768256640376	109.592694670279
testicle	90.770623878186	128.755828878210	95.4531352767412
cont.diffExp=49.0796955034875,27.5747005182106,-12.5417117435671,23.3451144244421,30.9344972587599,34.2852707522952,12.1382444395997,-37.9852050000244
cont.diffExpScore=1.78270639949301

cont.diffExp1.5=1,0,0,0,0,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=1,1,0,0,0,1,0,-1
cont.diffExp1.4Score=1.33333333333333
cont.diffExp1.3=1,1,0,0,1,1,0,-1
cont.diffExp1.3Score=1.25
cont.diffExp1.2=1,1,0,1,1,1,0,-1
cont.diffExp1.2Score=1.2

tran.correlation=0.884593886956496
cont.tran.correlation=-0.308393385857213

tran.covariance=0.0123683476984836
cont.tran.covariance=-0.00685450571176277

tran.mean=129.040704682627
cont.tran.mean=97.651825264707

weightedLogRatios:
wLogRatio
Lung	-0.711332223532713
cerebhem	0.726702628133832
cortex	-0.192983730019703
heart	-0.0617736130021882
kidney	-0.540914500452408
liver	0.220441301402790
stomach	-0.362453406652612
testicle	0.147946627506688

cont.weightedLogRatios:
wLogRatio
Lung	2.47529376696449
cerebhem	1.56700539830961
cortex	-0.56252282617992
heart	1.08354420090145
kidney	1.34331527374289
liver	1.59510819266013
stomach	0.593919137312725
testicle	-1.63713730434159

varWeightedLogRatios=0.213519566691866
cont.varWeightedLogRatios=1.74869145429356

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	6.11661933375126	0.0998730852685745	61.2439208952312	1.74527059729553e-276	***
df.mm.trans1	-0.864631222677614	0.083746127918687	-10.3244322354476	2.7439656730883e-23	***
df.mm.trans2	-1.34178141429134	0.0769573806686644	-17.4353830994886	2.10219810843202e-56	***
df.mm.exp2	-0.567324334100632	0.0998730852685745	-5.68045267225906	2.00462842535680e-08	***
df.mm.exp3	-0.252389989442995	0.0998730852685745	-2.52710716570214	0.0117299495185050	*  
df.mm.exp4	-0.123647148757455	0.0998730852685745	-1.23804274620082	0.216134496738692	   
df.mm.exp5	-0.267753764723331	0.0998730852685745	-2.68094015523100	0.00752249037233845	** 
df.mm.exp6	-0.32629202636611	0.0998730852685745	-3.26706665252865	0.00114220604162872	** 
df.mm.exp7	-0.071301800968479	0.0998730852685745	-0.71392408451924	0.475523118712476	   
df.mm.exp8	-0.302836473189	0.0998730852685745	-3.03221305694748	0.00252154499987807	** 
df.mm.trans1:exp2	0.362665448979915	0.086492628996915	4.19302145380331	3.12301871490968e-05	***
df.mm.trans2:exp2	0.0608411329475367	0.0706209358514313	0.861516945563156	0.389262069338256	   
df.mm.trans1:exp3	0.174146258870319	0.086492628996915	2.01342311928720	0.0444701295776953	*  
df.mm.trans2:exp3	0.0704976467907468	0.0706209358514314	0.998254213722911	0.318517027060808	   
df.mm.trans1:exp4	0.153906053287693	0.086492628996915	1.77941236233185	0.0756260877627822	.  
df.mm.trans2:exp4	0.0227923946675452	0.0706209358514313	0.322742744665613	0.74699091830733	   
df.mm.trans1:exp5	0.270923113391019	0.086492628996915	3.13232603209093	0.00180994040603647	** 
df.mm.trans2:exp5	0.236808081116981	0.0706209358514314	3.35322773993204	0.00084377995102599	***
df.mm.trans1:exp6	0.348844653751924	0.086492628996915	4.03322985782252	6.13556653079631e-05	***
df.mm.trans2:exp6	0.159981281273493	0.0706209358514313	2.26535204248855	0.0238099911717582	*  
df.mm.trans1:exp7	0.102336878713990	0.086492628996915	1.18318612696626	0.237155671183783	   
df.mm.trans2:exp7	0.0319291283069708	0.0706209358514313	0.45211986958289	0.651329184623465	   
df.mm.trans1:exp8	0.218657132381577	0.086492628996915	2.52804354448951	0.0116990129093188	*  
df.mm.trans2:exp8	0.0440205057847234	0.0706209358514313	0.62333506705903	0.533276805333616	   
df.mm.trans1:probe2	0.0156301104584301	0.0611595244863707	0.255562982048908	0.798366858062795	   
df.mm.trans1:probe3	0.131241727301508	0.0611595244863707	2.14589188525747	0.0322407454647858	*  
df.mm.trans1:probe4	0.113928892248311	0.0611595244863708	1.86281520670913	0.0629263412583214	.  
df.mm.trans1:probe5	-0.00113366980520550	0.0611595244863707	-0.018536275661498	0.985216565486115	   
df.mm.trans1:probe6	-0.895249582202099	0.0611595244863708	-14.6379421638833	2.70089347643334e-42	***
df.mm.trans1:probe7	-1.42197969801890	0.0611595244863708	-23.2503393373469	4.23765220649222e-88	***
df.mm.trans1:probe8	-1.38139595467675	0.0611595244863707	-22.5867674132193	2.15701940639932e-84	***
df.mm.trans1:probe9	-1.41146414713338	0.0611595244863707	-23.0784028977844	3.87920061212612e-87	***
df.mm.trans1:probe10	-1.42807134241524	0.0611595244863707	-23.3499418840884	1.17415292817469e-88	***
df.mm.trans1:probe11	-1.32230998954515	0.0611595244863707	-21.6206715250021	5.05895213107702e-79	***
df.mm.trans1:probe12	-1.35233556351005	0.0611595244863707	-22.1116101681172	9.53999573472975e-82	***
df.mm.trans2:probe2	0.546150777153036	0.0611595244863708	8.92993825147781	4.08019561907961e-18	***
df.mm.trans2:probe3	1.08092432640875	0.0611595244863708	17.6738510556869	1.18572565974725e-57	***
df.mm.trans2:probe4	1.19430530481426	0.0611595244863708	19.5277074968169	1.51121612306136e-67	***
df.mm.trans2:probe5	0.606670104880715	0.0611595244863708	9.91947059719063	9.9269086689883e-22	***
df.mm.trans2:probe6	1.03205307531029	0.0611595244863708	16.8747727190110	1.71003833244051e-53	***
df.mm.trans3:probe2	0.0672092480522044	0.0611595244863707	1.09891711252892	0.272199534381286	   
df.mm.trans3:probe3	0.125863042715734	0.0611595244863708	2.05794671840168	0.0399821213918358	*  
df.mm.trans3:probe4	0.775590798954506	0.0611595244863708	12.6814393255681	3.53061433409769e-33	***
df.mm.trans3:probe5	0.611157038104597	0.0611595244863707	9.99283502017404	5.22161250567433e-22	***
df.mm.trans3:probe6	1.41559859351933	0.0611595244863707	23.1460039202037	1.62461185922778e-87	***
df.mm.trans3:probe7	0.282299337928256	0.0611595244863708	4.61578699800332	4.6955130009826e-06	***
df.mm.trans3:probe8	0.115312404372419	0.0611595244863708	1.88543657493798	0.0598039938298709	.  
df.mm.trans3:probe9	-0.171353378067772	0.0611595244863708	-2.80174477330931	0.00522967710200008	** 
df.mm.trans3:probe10	0.252753141844426	0.0611595244863707	4.13268651067998	4.04073868880777e-05	***
df.mm.trans3:probe11	0.371237209838043	0.0611595244863708	6.06998195221045	2.14294101582868e-09	***
df.mm.trans3:probe12	-0.178173052412941	0.0611595244863708	-2.91325110699065	0.00369617622518636	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.41678540404047	0.339764258869081	12.9995586314521	1.30656475486864e-34	***
df.mm.trans1	0.444938207963448	0.284900992183538	1.56172923285859	0.118824684384302	   
df.mm.trans2	-0.269579386050605	0.261805944385117	-1.02969161637542	0.303526914183456	   
df.mm.exp2	-0.151426073021925	0.339764258869081	-0.445679817900661	0.655972734780087	   
df.mm.exp3	0.622359853145403	0.339764258869081	1.83174020486132	0.0674345986699116	.  
df.mm.exp4	0.339833549594223	0.339764258869081	1.00020393765187	0.317573452729413	   
df.mm.exp5	0.669148799844005	0.339764258869081	1.96945023608809	0.0493136143269992	*  
df.mm.exp6	0.36456125086515	0.339764258869081	1.07298293257392	0.283665654560245	   
df.mm.exp7	0.136582576229466	0.339764258869081	0.401992183298169	0.687818172778907	   
df.mm.exp8	0.587701617688701	0.339764258869081	1.72973349122974	0.084139133693928	.  
df.mm.trans1:exp2	-0.089300442621072	0.294244479478616	-0.303490630578038	0.761610344175788	   
df.mm.trans2:exp2	0.102048807402849	0.240249611451149	0.424761591856305	0.67114705194811	   
df.mm.trans1:exp3	-0.793917627063124	0.294244479478616	-2.69815640541464	0.00714831620833255	** 
df.mm.trans2:exp3	-0.119154788920035	0.240249611451149	-0.495962462541854	0.620083787113715	   
df.mm.trans1:exp4	-0.378652959313901	0.294244479478616	-1.28686512652625	0.198586390742793	   
df.mm.trans2:exp4	-0.0611277447335478	0.240249611451149	-0.254434312564860	0.799238231390906	   
df.mm.trans1:exp5	-0.598817745220327	0.294244479478616	-2.03510273593373	0.0422342306291709	*  
df.mm.trans2:exp5	-0.332637981312611	0.240249611451149	-1.38455158908862	0.166651227566352	   
df.mm.trans1:exp6	-0.353947845364149	0.294244479478616	-1.20290394569619	0.229439026000901	   
df.mm.trans2:exp6	-0.148314728579179	0.240249611451149	-0.617335976875605	0.537223196646453	   
df.mm.trans1:exp7	-0.293329651299676	0.294244479478616	-0.996890924918757	0.319177886547464	   
df.mm.trans2:exp7	0.128943898115628	0.240249611451149	0.53670804017865	0.591647733141684	   
df.mm.trans1:exp8	-0.828350605805885	0.294244479478616	-2.81517806986107	0.00501846639646674	** 
df.mm.trans2:exp8	0.0747104902912451	0.240249611451149	0.310970285612455	0.755920078003956	   
df.mm.trans1:probe2	-0.25959883334646	0.208062266766035	-1.24769780403468	0.212578295593579	   
df.mm.trans1:probe3	-0.380526112037683	0.208062266766035	-1.82890496173236	0.0678588647457218	.  
df.mm.trans1:probe4	-0.41419328686231	0.208062266766035	-1.99071793891426	0.04691830315367	*  
df.mm.trans1:probe5	-0.324721497604616	0.208062266766035	-1.56069383772389	0.119068906716811	   
df.mm.trans1:probe6	-0.0424525772127246	0.208062266766036	-0.204037848248872	0.838385974235153	   
df.mm.trans1:probe7	-0.281592366083980	0.208062266766035	-1.35340429795773	0.176383609622882	   
df.mm.trans1:probe8	-0.201448964106321	0.208062266766035	-0.968214790877236	0.333287000405148	   
df.mm.trans1:probe9	-0.267147273439865	0.208062266766035	-1.28397752073071	0.199594316052575	   
df.mm.trans1:probe10	-0.0933926501875284	0.208062266766035	-0.448868752797679	0.653671697749996	   
df.mm.trans1:probe11	-0.0523811635061778	0.208062266766035	-0.251757150973848	0.801306096519738	   
df.mm.trans1:probe12	-0.388279264311938	0.208062266766035	-1.86616857706619	0.0624551324580995	.  
df.mm.trans2:probe2	0.150037299796721	0.208062266766035	0.721117298820149	0.471089268047742	   
df.mm.trans2:probe3	0.205441500273198	0.208062266766036	0.98740393184419	0.323801631366888	   
df.mm.trans2:probe4	0.0922985400499313	0.208062266766036	0.443610182108226	0.657467874606406	   
df.mm.trans2:probe5	0.343362948977726	0.208062266766036	1.65028937882252	0.0993531292974504	.  
df.mm.trans2:probe6	0.0782540479173032	0.208062266766035	0.376108792495755	0.706955257152308	   
df.mm.trans3:probe2	0.234062419964904	0.208062266766035	1.12496332757974	0.261008018215184	   
df.mm.trans3:probe3	0.263013892728741	0.208062266766035	1.26411144517856	0.206630285068312	   
df.mm.trans3:probe4	0.184777302243749	0.208062266766035	0.888086557528133	0.374813371677883	   
df.mm.trans3:probe5	0.113258642989857	0.208062266766035	0.544349750438965	0.586382199488722	   
df.mm.trans3:probe6	0.401101235593914	0.208062266766035	1.92779422154883	0.0543037107721924	.  
df.mm.trans3:probe7	-0.110597039310674	0.208062266766036	-0.531557408412934	0.595209019758356	   
df.mm.trans3:probe8	0.0677565142971843	0.208062266766035	0.32565498468483	0.744787234719502	   
df.mm.trans3:probe9	0.0481211462391945	0.208062266766035	0.231282428030578	0.817166114650841	   
df.mm.trans3:probe10	0.0987152038220164	0.208062266766035	0.474450294887063	0.635333658924006	   
df.mm.trans3:probe11	0.223017840944641	0.208062266766035	1.07188028089410	0.284160323269383	   
df.mm.trans3:probe12	0.0659288663914217	0.208062266766035	0.316870845522212	0.751440459826743