chr9.24204_chr9_44654347_44655561_+_1.R 

fitVsDatCorrelation=0.83687754185881
cont.fitVsDatCorrelation=0.263145942668257

fstatistic=5639.5977624497,50,646
cont.fstatistic=1806.78457446261,50,646

residuals=-0.82152065823507,-0.113848055855274,-0.0114301990472974,0.106756845878311,1.25019989726366
cont.residuals=-0.728672817566033,-0.269468507727448,-0.0669231147324382,0.226501819109242,1.5490884360528

predictedValues:
Include	Exclude	Both
chr9.24204_chr9_44654347_44655561_+_1.R.tl.Lung	87.8913022548183	103.642163593068	67.8419480448156
chr9.24204_chr9_44654347_44655561_+_1.R.tl.cerebhem	160.274995968732	118.412494555701	62.4985985919601
chr9.24204_chr9_44654347_44655561_+_1.R.tl.cortex	84.4717822757724	96.5345405468563	71.2296226794593
chr9.24204_chr9_44654347_44655561_+_1.R.tl.heart	83.4633439108493	89.5704866586465	72.6664249365162
chr9.24204_chr9_44654347_44655561_+_1.R.tl.kidney	91.0522280726669	173.311502218112	115.082285763353
chr9.24204_chr9_44654347_44655561_+_1.R.tl.liver	85.1684557666955	132.132336067427	92.7187094990243
chr9.24204_chr9_44654347_44655561_+_1.R.tl.stomach	89.018654716871	95.8050376414194	70.0046456425411
chr9.24204_chr9_44654347_44655561_+_1.R.tl.testicle	93.0926508157096	100.418383480690	79.29968857887


diffExp=-15.7508613382499,41.8625014130312,-12.0627582710839,-6.10714274779717,-82.259274145445,-46.963880300731,-6.78638292454833,-7.3257326649799
diffExpScore=1.60651705569754
diffExp1.5=0,0,0,0,-1,-1,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=0,0,0,0,-1,-1,0,0
diffExp1.4Score=0.666666666666667
diffExp1.3=0,1,0,0,-1,-1,0,0
diffExp1.3Score=1.5
diffExp1.2=0,1,0,0,-1,-1,0,0
diffExp1.2Score=1.5

cont.predictedValues:
Include	Exclude	Both
Lung	76.758769305916	96.2011132717843	84.3268375076479
cerebhem	84.0355583610971	87.2155118768213	86.4219701408928
cortex	80.1346740882158	84.8681709059116	90.9366983881324
heart	92.0555529820205	82.3725300120627	81.8135417706174
kidney	89.7095193457114	106.116665676611	81.6675198923169
liver	86.3007653714638	86.0266690291062	88.8382273367478
stomach	98.4938217940832	80.0590332844507	88.273358287486
testicle	95.880927716739	72.6904477782508	81.638610076472
cont.diffExp=-19.4423439658682,-3.17995351572421,-4.73349681769581,9.6830229699578,-16.4071463308999,0.27409634235768,18.4347885096325,23.1904799384881
cont.diffExpScore=10.8108055961489

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=0,0,0,0,0,0,0,1
cont.diffExp1.3Score=0.5
cont.diffExp1.2=-1,0,0,0,0,0,1,1
cont.diffExp1.2Score=1.5

tran.correlation=0.110214239592552
cont.tran.correlation=-0.477679231939553

tran.covariance=0.00814880378070373
cont.tran.covariance=-0.00499246229657589

tran.mean=105.266272409002
cont.tran.mean=87.4324831750154

weightedLogRatios:
wLogRatio
Lung	-0.751442273310956
cerebhem	1.49104157964134
cortex	-0.601096715594932
heart	-0.314937770096713
kidney	-3.11096426777958
liver	-2.04839765970421
stomach	-0.332491317568771
testicle	-0.346289102877521

cont.weightedLogRatios:
wLogRatio
Lung	-1.00549361215774
cerebhem	-0.165275687546771
cortex	-0.253229961974329
heart	0.4964436104083
kidney	-0.769360693748741
liver	0.0141758308773239
stomach	0.929710288102917
testicle	1.22517512440086

varWeightedLogRatios=1.83299699365845
cont.varWeightedLogRatios=0.611226023547338

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.60027808148521	0.108199514099908	42.516624217346	2.27841170633067e-189	***
df.mm.trans1	-0.0596447741559815	0.0853931304314526	-0.698472744290127	0.485132956394669	   
df.mm.trans2	0.0216061690182049	0.0853931304314526	0.253019990121440	0.800333259519401	   
df.mm.exp2	0.816056801480856	0.113074972146016	7.21695337167151	1.49673337413081e-12	***
df.mm.exp3	-0.159454736805659	0.113074972146016	-1.41016826075138	0.15897129802754	   
df.mm.exp4	-0.266310405915698	0.113074972146016	-2.35516667270813	0.0188124953053138	*  
df.mm.exp5	0.0210120676031481	0.113074972146016	0.185824212063609	0.852640948978077	   
df.mm.exp6	-0.100999561039316	0.113074972146016	-0.89320880759442	0.37207798182548	   
df.mm.exp7	-0.0972647607649173	0.113074972146016	-0.860179391769534	0.390009275343997	   
df.mm.exp8	-0.130158040554631	0.113074972146016	-1.15107736119143	0.250126279178257	   
df.mm.trans1:exp2	-0.215266586097810	0.0857433429622841	-2.51059241056765	0.0122960459514148	*  
df.mm.trans2:exp2	-0.682826787775338	0.0857433429622841	-7.96361284952107	7.54895921524886e-15	***
df.mm.trans1:exp3	0.119771428496316	0.0857433429622841	1.39685979527297	0.162935401157849	   
df.mm.trans2:exp3	0.0884113827171286	0.0857433429622841	1.03111658191375	0.302872034442794	   
df.mm.trans1:exp4	0.214617096968227	0.0857433429622841	2.50301760525748	0.0125597229799148	*  
df.mm.trans2:exp4	0.120392050146594	0.0857433429622841	1.40409792745718	0.160770258245027	   
df.mm.trans1:exp5	0.0143203598024685	0.0857433429622841	0.167014246327759	0.867411103868233	   
df.mm.trans2:exp5	0.493134267111611	0.0857433429622841	5.75128342416653	1.36719003782644e-08	***
df.mm.trans1:exp6	0.0695298395015856	0.0857433429622841	0.810906562532437	0.417717977943934	   
df.mm.trans2:exp6	0.343859295858732	0.0857433429622841	4.01033227745721	6.77180637007222e-05	***
df.mm.trans1:exp7	0.110009862755567	0.0857433429622841	1.28301345567967	0.199947469780234	   
df.mm.trans2:exp7	0.0186357978239573	0.0857433429622841	0.217343961409980	0.828008926697688	   
df.mm.trans1:exp8	0.187652433776984	0.0857433429622841	2.18853647751437	0.0289878795744632	*  
df.mm.trans2:exp8	0.0985591019296348	0.0857433429622841	1.14946651861927	0.250789047247609	   
df.mm.trans1:probe2	-0.196646958760682	0.0638398100530217	-3.08031866945341	0.00215560885674953	** 
df.mm.trans1:probe3	-0.267920761088888	0.0638398100530217	-4.19676626334522	3.08680280058745e-05	***
df.mm.trans1:probe4	-0.417522479995461	0.0638398100530217	-6.540158556999	1.24995549062671e-10	***
df.mm.trans1:probe5	-0.374801658205035	0.0638398100530217	-5.87097076093657	6.93009415722674e-09	***
df.mm.trans1:probe6	-0.227354675746262	0.0638398100530217	-3.56133070504805	0.000396105510485288	***
df.mm.trans2:probe2	0.0542747230047156	0.0638398100530217	0.850170496429079	0.395545283998929	   
df.mm.trans2:probe3	0.177967651781735	0.0638398100530217	2.78772213817562	0.00546411295905094	** 
df.mm.trans2:probe4	0.0405490978710277	0.0638398100530217	0.6351694630255	0.525542805748555	   
df.mm.trans2:probe5	0.0710261449620946	0.0638398100530217	1.11256823764207	0.266307747988891	   
df.mm.trans2:probe6	0.0945619457328124	0.0638398100530217	1.48123789300555	0.139030765942993	   
df.mm.trans3:probe2	-0.22681058432009	0.0638398100530217	-3.55280794431741	0.000408905438678059	***
df.mm.trans3:probe3	-0.610701485706063	0.0638398100530217	-9.56615449198312	2.29620857537139e-20	***
df.mm.trans3:probe4	-0.465976101350868	0.0638398100530217	-7.29914611218071	8.5353318110812e-13	***
df.mm.trans3:probe5	-0.318832142572487	0.0638398100530217	-4.99425268195008	7.60972137422117e-07	***
df.mm.trans3:probe6	0.0728337075358171	0.0638398100530217	1.14088227197615	0.254341683102689	   
df.mm.trans3:probe7	-0.675086656618494	0.0638398100530217	-10.5746971373788	3.25736712991245e-24	***
df.mm.trans3:probe8	-0.519103195428938	0.0638398100530217	-8.13133991153483	2.17337454244669e-15	***
df.mm.trans3:probe9	-0.27827046782413	0.0638398100530217	-4.35888621211458	1.5207156946889e-05	***
df.mm.trans3:probe10	0.147369235862846	0.0638398100530217	2.30842221711576	0.0212905416247692	*  
df.mm.trans3:probe11	-0.551250840983382	0.0638398100530217	-8.6349072863084	4.58076020099072e-17	***
df.mm.trans3:probe12	-0.712480776814164	0.0638398100530217	-11.1604463769929	1.43347787943872e-26	***
df.mm.trans3:probe13	-0.294272648605922	0.0638398100530217	-4.60954768445452	4.86468420770337e-06	***
df.mm.trans3:probe14	-0.214498691989037	0.0638398100530217	-3.35995191418782	0.000825448080907182	***
df.mm.trans3:probe15	-0.614281580463317	0.0638398100530217	-9.62223383736778	1.42665275802043e-20	***
df.mm.trans3:probe16	-0.231762849569324	0.0638398100530217	-3.63038125233824	0.000305405685914895	***
df.mm.trans3:probe17	-0.372874011030218	0.0638398100530217	-5.84077569655252	8.23515104567424e-09	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.44486499715551	0.190697866789878	23.308414886744	1.132572810366e-87	***
df.mm.trans1	-0.096560834010249	0.150502411653637	-0.641589944966942	0.521367037239746	   
df.mm.trans2	0.141187574252286	0.150502411653637	0.938108384450423	0.348539310958909	   
df.mm.exp2	-0.0320280974218131	0.199290691413452	-0.160710453632614	0.872371698240228	   
df.mm.exp3	-0.157764271496681	0.199290691413452	-0.791628903376024	0.428867657460841	   
df.mm.exp4	0.0567930654602334	0.199290691413452	0.284976006944597	0.775753859794456	   
df.mm.exp5	0.286051230088789	0.199290691413452	1.43534666902902	0.151672320413639	   
df.mm.exp6	-0.0467296220224572	0.199290691413452	-0.234479702443859	0.814686886021798	   
df.mm.exp7	0.0199113613935893	0.199290691413452	0.0999111461371813	0.920445864519948	   
df.mm.exp8	-0.0253936404325957	0.199290691413452	-0.127420103028865	0.898647558391812	   
df.mm.trans1:exp2	0.122600482517803	0.151119649014712	0.811280884498796	0.41750318814273	   
df.mm.trans2:exp2	-0.0660306290643473	0.151119649014712	-0.436942710592975	0.662298911359191	   
df.mm.trans1:exp3	0.200805278901877	0.151119649014712	1.32878338595352	0.184388602145787	   
df.mm.trans2:exp3	0.0324224634541259	0.151119649014712	0.214548297759541	0.830187214691092	   
df.mm.trans1:exp4	0.124931528115949	0.151119649014712	0.826706050010653	0.408708933177841	   
df.mm.trans2:exp4	-0.211981987842639	0.151119649014712	-1.40274272223860	0.161173974256917	   
df.mm.trans1:exp5	-0.130141980397287	0.151119649014712	-0.861185036133967	0.389455666903013	   
df.mm.trans2:exp5	-0.187953051700211	0.151119649014712	-1.24373668762236	0.214047620554085	   
df.mm.trans1:exp6	0.163900450805374	0.151119649014712	1.08457405687475	0.278514944070143	   
df.mm.trans2:exp6	-0.0650539548835128	0.151119649014712	-0.4304797907331	0.66699024470992	   
df.mm.trans1:exp7	0.229414823916691	0.151119649014712	1.51810056079707	0.129478264797085	   
df.mm.trans2:exp7	-0.203588012866735	0.151119649014712	-1.34719749677896	0.178388987795203	   
df.mm.trans1:exp8	0.247833087764873	0.151119649014712	1.63997924413354	0.101496300068779	   
df.mm.trans2:exp8	-0.254837306058299	0.151119649014712	-1.68632806997513	0.0922154654044728	.  
df.mm.trans1:probe2	0.0600383715888241	0.112515436826648	0.533601195374859	0.593801025156044	   
df.mm.trans1:probe3	-0.0610830250434671	0.112515436826648	-0.54288572987169	0.587395733708893	   
df.mm.trans1:probe4	0.0538268538764115	0.112515436826648	0.478395279745854	0.632530752285321	   
df.mm.trans1:probe5	-0.0217519975781879	0.112515436826648	-0.193324562314956	0.846765558231734	   
df.mm.trans1:probe6	-0.206670281233177	0.112515436826648	-1.83681712538336	0.0666961466069698	.  
df.mm.trans2:probe2	-0.118380573097829	0.112515436826648	-1.05212739190816	0.29313449803675	   
df.mm.trans2:probe3	-0.108958469149298	0.112515436826648	-0.968386847372501	0.333213615599686	   
df.mm.trans2:probe4	0.0069944868484307	0.112515436826648	0.0621646864261572	0.95045091261036	   
df.mm.trans2:probe5	-0.103988339940637	0.112515436826648	-0.92421398230761	0.355720005399028	   
df.mm.trans2:probe6	-0.126734855281226	0.112515436826648	-1.1263774896638	0.260424019143093	   
df.mm.trans3:probe2	-0.167069472049290	0.112515436826648	-1.48485822711325	0.138069167897769	   
df.mm.trans3:probe3	-0.0243305784807594	0.112515436826648	-0.216242136785598	0.828867274432185	   
df.mm.trans3:probe4	0.0639276548491029	0.112515436826648	0.568167859025385	0.570118423859317	   
df.mm.trans3:probe5	0.00312677996088399	0.112515436826648	0.0277897864423829	0.977838394601065	   
df.mm.trans3:probe6	-0.0299878509976328	0.112515436826648	-0.266522104374307	0.789922187259384	   
df.mm.trans3:probe7	-0.229339798933681	0.112515436826648	-2.03829630317325	0.0419270562103002	*  
df.mm.trans3:probe8	-0.038404457266619	0.112515436826648	-0.341326117995599	0.732969078576936	   
df.mm.trans3:probe9	-0.171293577278143	0.112515436826648	-1.5224006777137	0.128398049378916	   
df.mm.trans3:probe10	-0.0437915983285223	0.112515436826648	-0.389205246529786	0.697252583511892	   
df.mm.trans3:probe11	0.0127234393685393	0.112515436826648	0.113081722183083	0.910000897110675	   
df.mm.trans3:probe12	-0.0529722161238567	0.112515436826648	-0.470799541981698	0.637942818959064	   
df.mm.trans3:probe13	-0.0153468621530901	0.112515436826648	-0.136397836474073	0.891549278699294	   
df.mm.trans3:probe14	-0.0921305034651995	0.112515436826648	-0.81882545243231	0.413187962520676	   
df.mm.trans3:probe15	0.000704173917157402	0.112515436826648	0.00625846494505742	0.995008432190148	   
df.mm.trans3:probe16	-0.102374062145687	0.112515436826648	-0.909866815016807	0.363232099455172	   
df.mm.trans3:probe17	-0.0448976912714471	0.112515436826648	-0.399035834883889	0.689998673338379