chr15.8368_chr15_89920559_89921324_+_0.R 

fitVsDatCorrelation=0.859071600200437
cont.fitVsDatCorrelation=0.29142791985307

fstatistic=4700.52178739463,36,324
cont.fstatistic=1339.39533200985,36,324

residuals=-0.606290597008907,-0.103793328672839,-0.0117449771597231,0.0867652714223,1.02088214230102
cont.residuals=-0.70806008684207,-0.236176989038344,-0.087824120471245,0.178673708922338,1.53237261180986

predictedValues:
Include	Exclude	Both
chr15.8368_chr15_89920559_89921324_+_0.R.tl.Lung	60.3746620145315	51.1931890766677	92.2346423392652
chr15.8368_chr15_89920559_89921324_+_0.R.tl.cerebhem	91.0071873257774	63.7777085780669	83.0012113364273
chr15.8368_chr15_89920559_89921324_+_0.R.tl.cortex	52.8789591295905	46.3157049548112	83.3586615617147
chr15.8368_chr15_89920559_89921324_+_0.R.tl.heart	56.4021843722308	46.1659140021161	99.7988694379526
chr15.8368_chr15_89920559_89921324_+_0.R.tl.kidney	55.4711693605966	48.4858872739487	93.7332429953781
chr15.8368_chr15_89920559_89921324_+_0.R.tl.liver	53.4707803801157	46.942191842256	107.202339794104
chr15.8368_chr15_89920559_89921324_+_0.R.tl.stomach	60.9794252287193	48.3310029906159	112.575697968439
chr15.8368_chr15_89920559_89921324_+_0.R.tl.testicle	64.4329613908145	52.6445545113383	112.045336686745


diffExp=9.18147293786385,27.2294787477105,6.5632541747793,10.2362703701147,6.98528208664786,6.5285885378597,12.6484222381034,11.7884068794762
diffExpScore=0.98914944400994
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,1,0,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,1,0,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,1,0,1,0,0,1,1
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	66.669663856073	54.6234329107151	61.3090255068319
cerebhem	57.5083422753652	59.2898464136651	63.9247077098586
cortex	84.2967963292902	64.4388280810441	65.9560975688747
heart	65.6533618335377	65.9113003655939	57.0836303740557
kidney	59.6957155012085	55.5928818192676	74.1718915613918
liver	67.4330064156314	61.032228994899	60.2560937325481
stomach	61.6355174682119	64.8831626629823	68.8038099530117
testicle	67.980376413743	65.3236597163603	61.2235102655694
cont.diffExp=12.0462309453579,-1.78150413829992,19.8579682482461,-0.257938532056173,4.10283368194093,6.40077742073232,-3.24764519477046,2.65671669738278
cont.diffExpScore=1.23479100048619

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=0,0,1,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=1,0,1,0,0,0,0,0
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.978404444459922
cont.tran.correlation=0.372404267771337

tran.covariance=0.0183424797376753
cont.tran.covariance=0.00328125815941681

tran.mean=56.1795926520123
cont.tran.mean=63.8730075660993

weightedLogRatios:
wLogRatio
Lung	0.66283591798134
cerebhem	1.54059291158130
cortex	0.517076222996902
heart	0.787521579954341
kidney	0.531440319550817
liver	0.509678451747766
stomach	0.928529202476067
testicle	0.821302119023208

cont.weightedLogRatios:
wLogRatio
Lung	0.817098210373452
cerebhem	-0.124081841806351
cortex	1.15510629340020
heart	-0.0164150794453598
kidney	0.28864103141293
liver	0.415013855380945
stomach	-0.21294344778154
testicle	0.167403670800706

varWeightedLogRatios=0.117086021056284
cont.varWeightedLogRatios=0.224514672709019

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.38216784354038	0.108541941778503	31.1600086392616	1.70581833114491e-99	***
df.mm.trans1	0.603343127730574	0.0919338908420636	6.56279335296575	2.09429047644321e-10	***
df.mm.trans2	0.538359084895311	0.0919338908420636	5.85593713008597	1.16398069035029e-08	***
df.mm.exp2	0.735646796014792	0.128029089765387	5.74593475094496	2.10878919792942e-08	***
df.mm.exp3	-0.131506127421293	0.128029089765387	-1.02715818461474	0.305112202475808	   
df.mm.exp4	-0.250247454445093	0.128029089765387	-1.95461402485693	0.0514883846733122	.  
df.mm.exp5	-0.155156941984427	0.128029089765387	-1.21188819094747	0.226438226531059	   
df.mm.exp6	-0.358506068219436	0.128029089765387	-2.8001922756492	0.00541372723520223	** 
df.mm.exp7	-0.246856332500868	0.128029089765387	-1.92812690423115	0.0547129866654528	.  
df.mm.exp8	-0.101555671926425	0.128029089765387	-0.793223415963706	0.428228158310453	   
df.mm.trans1:exp2	-0.325277824868944	0.110876444160224	-2.93369639811768	0.00358839395424105	** 
df.mm.trans2:exp2	-0.515849559395327	0.110876444160224	-4.65247206746539	4.78619995721364e-06	***
df.mm.trans1:exp3	-0.00105787471411431	0.110876444160224	-0.00954102309220537	0.992393352416158	   
df.mm.trans2:exp3	0.0313807335357308	0.110876444160224	0.283024349972692	0.777338909920503	   
df.mm.trans1:exp4	0.182185828349141	0.110876444160224	1.64314277689020	0.101323443461016	   
df.mm.trans2:exp4	0.146882690717811	0.110876444160224	1.32474207511161	0.186190290929255	   
df.mm.trans1:exp5	0.0704508429307083	0.110876444160224	0.635399551855236	0.525616356939289	   
df.mm.trans2:exp5	0.100823216191094	0.110876444160224	0.9093294518482	0.363852174024481	   
df.mm.trans1:exp6	0.237071897947682	0.110876444160224	2.13816288701591	0.0332512841558026	*  
df.mm.trans2:exp6	0.271816454753435	0.110876444160224	2.45152572137543	0.0147528193464209	*  
df.mm.trans1:exp7	0.256823334592124	0.110876444160224	2.31630204717783	0.0211653893457095	*  
df.mm.trans2:exp7	0.189323073753340	0.110876444160224	1.70751393758403	0.0886845165438555	.  
df.mm.trans1:exp8	0.166611483084763	0.110876444160224	1.50267700544219	0.133896367710427	   
df.mm.trans2:exp8	0.129511979722208	0.110876444160224	1.16807479445368	0.243635394240537	   
df.mm.trans1:probe2	0.266341378729979	0.0554382220801119	4.80429149306229	2.3787123097304e-06	***
df.mm.trans1:probe3	0.125035869448258	0.0554382220801119	2.25540907981451	0.0247745280518754	*  
df.mm.trans1:probe4	0.0929951845255384	0.0554382220801119	1.67745611306139	0.0944176959366635	.  
df.mm.trans1:probe5	0.0223227843672480	0.0554382220801119	0.402660538698194	0.687463508553995	   
df.mm.trans1:probe6	0.528831666177013	0.0554382220801119	9.53911662990952	3.60259173252153e-19	***
df.mm.trans2:probe2	-0.0257434496370416	0.0554382220801119	-0.464362828949323	0.642699683710353	   
df.mm.trans2:probe3	-0.0267282745317802	0.0554382220801119	-0.482127195442092	0.630041117286545	   
df.mm.trans2:probe4	0.0913597344809013	0.0554382220801119	1.64795570732554	0.100331120207569	   
df.mm.trans2:probe5	0.0262309922246804	0.0554382220801119	0.473157169195919	0.636419663634999	   
df.mm.trans2:probe6	0.0705971176956481	0.0554382220801119	1.27343762203684	0.203775633736231	   
df.mm.trans3:probe2	-0.189665575694916	0.0554382220801119	-3.42120595824369	0.000703297544600134	***
df.mm.trans3:probe3	0.191062778259217	0.0554382220801119	3.44640883293693	0.000642971077337583	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.02919426490935	0.202851102152314	19.8628167269407	5.48906635649628e-58	***
df.mm.trans1	0.199360438943825	0.171812764511982	1.16033543555445	0.246766531529687	   
df.mm.trans2	-0.0548714984752629	0.171812764511982	-0.319367997081709	0.749653290404411	   
df.mm.exp2	-0.107623793610602	0.239270106476113	-0.449800416757648	0.653155132998375	   
df.mm.exp3	0.326784968218709	0.239270106476113	1.36575760771575	0.172962380158837	   
df.mm.exp4	0.243895387602871	0.239270106476113	1.01933079395031	0.308806471225482	   
df.mm.exp5	-0.283355772029476	0.239270106476113	-1.18425062036642	0.237181898340641	   
df.mm.exp6	0.139647035806797	0.239270106476113	0.583637621362191	0.559870208013155	   
df.mm.exp7	-0.0217186114636208	0.239270106476113	-0.0907702670571136	0.927731225757004	   
df.mm.exp8	0.199756172539750	0.239270106476113	0.83485636998992	0.404413737154352	   
df.mm.trans1:exp2	-0.0401962207702394	0.207213990574521	-0.193984106279655	0.846309889378946	   
df.mm.trans2:exp2	0.189598896030026	0.207213990574521	0.91499080493718	0.36087691054796	   
df.mm.trans1:exp3	-0.0921911418547562	0.207213990574521	-0.444907902208471	0.656683382716089	   
df.mm.trans2:exp3	-0.161531561149724	0.207213990574521	-0.77953984044157	0.436230815253885	   
df.mm.trans1:exp4	-0.259256614443973	0.207213990574521	-1.25115400618056	0.211780947059454	   
df.mm.trans2:exp4	-0.056048448191002	0.207213990574521	-0.270485829820671	0.786958735663556	   
df.mm.trans1:exp5	0.172865987993263	0.207213990574521	0.834238979298527	0.40476097301566	   
df.mm.trans2:exp5	0.300947975385937	0.207213990574521	1.45235355272841	0.147371025291420	   
df.mm.trans1:exp6	-0.128262463036783	0.207213990574521	-0.618985536069078	0.536360848612427	   
df.mm.trans2:exp6	-0.0287079318503363	0.207213990574521	-0.138542439971069	0.889897797681174	   
df.mm.trans1:exp7	-0.0567931365908809	0.207213990574521	-0.274079643142899	0.784198071502802	   
df.mm.trans2:exp7	0.193843801558663	0.207213990574521	0.935476417500634	0.350239533338621	   
df.mm.trans1:exp8	-0.180287125872771	0.207213990574521	-0.870052863577921	0.384915639636601	   
df.mm.trans2:exp8	-0.0208648433769250	0.207213990574521	-0.100692252096855	0.91985704098291	   
df.mm.trans1:probe2	0.00564644783930384	0.103606995287261	0.0544987124049732	0.95657142331859	   
df.mm.trans1:probe3	-0.0778238522152391	0.103606995287261	-0.751144765847757	0.453110753628648	   
df.mm.trans1:probe4	-0.112452019957628	0.103606995287261	-1.08537092158539	0.278564305655109	   
df.mm.trans1:probe5	-0.0354626090037084	0.103606995287261	-0.342280064250342	0.732362061766113	   
df.mm.trans1:probe6	-0.0391499889472947	0.103606995287261	-0.37787013163298	0.705774499402193	   
df.mm.trans2:probe2	0.102385032832071	0.103606995287261	0.98820579197571	0.323789270880728	   
df.mm.trans2:probe3	0.069104163630119	0.103606995287261	0.666983570351798	0.505257340466881	   
df.mm.trans2:probe4	-0.0162503898205108	0.103606995287261	-0.156846454001055	0.875463551184079	   
df.mm.trans2:probe5	-0.0349207021113334	0.103606995287261	-0.337049655908969	0.736297693979996	   
df.mm.trans2:probe6	0.114943681400761	0.103606995287261	1.10942008386662	0.268071759497712	   
df.mm.trans3:probe2	-0.0907504409103453	0.103606995287261	-0.875910363568895	0.381727671080716	   
df.mm.trans3:probe3	-0.0825179738457565	0.103606995287261	-0.79645176097393	0.42635269320364