chr2.12572_chr2_155373334_155373832_+_1.R 

fitVsDatCorrelation=0.863419771271596
cont.fitVsDatCorrelation=0.32636764823427

fstatistic=9514.0695764576,40,416
cont.fstatistic=2702.61676208529,40,416

residuals=-0.432701704956909,-0.0903256866182925,0.00442527493166765,0.085976056983873,0.489458986434556
cont.residuals=-0.631315478259866,-0.188693244550182,-0.0432042991851693,0.124107765144230,0.821982631828092

predictedValues:
Include	Exclude	Both
chr2.12572_chr2_155373334_155373832_+_1.R.tl.Lung	89.8160491705402	64.8733690298108	65.7434084430593
chr2.12572_chr2_155373334_155373832_+_1.R.tl.cerebhem	58.9859356378886	74.6149260641574	59.5333996643858
chr2.12572_chr2_155373334_155373832_+_1.R.tl.cortex	72.7625798482207	61.14861374519	62.3956278305737
chr2.12572_chr2_155373334_155373832_+_1.R.tl.heart	78.807895412491	61.3094252931701	66.2721666520263
chr2.12572_chr2_155373334_155373832_+_1.R.tl.kidney	95.5631779039466	65.8175333073878	70.3085246512071
chr2.12572_chr2_155373334_155373832_+_1.R.tl.liver	89.3894286404703	68.7903015629863	67.503947401983
chr2.12572_chr2_155373334_155373832_+_1.R.tl.stomach	75.1657680957234	63.7140526374029	64.7081371403079
chr2.12572_chr2_155373334_155373832_+_1.R.tl.testicle	77.2425261853754	66.2765857529452	60.0962763808577


diffExp=24.9426801407294,-15.6289904262688,11.6139661030307,17.4984701193208,29.7456445965588,20.599127077484,11.4517154583205,10.9659404324302
diffExpScore=1.26970648883627
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,1,0,0,0
diffExp1.4Score=0.5
diffExp1.3=1,0,0,0,1,0,0,0
diffExp1.3Score=0.666666666666667
diffExp1.2=1,-1,0,1,1,1,0,0
diffExp1.2Score=1.25

cont.predictedValues:
Include	Exclude	Both
Lung	67.7680129819359	56.2448853752742	67.446544758218
cerebhem	69.381870180613	63.6098716200172	63.9870872094609
cortex	69.0479244839085	66.669039755581	62.2456210241952
heart	65.0568495266394	66.3744607171786	66.0786126224948
kidney	68.2741142444401	67.8191113949217	69.1268625335455
liver	65.2432744344886	68.7324512122394	76.0621812620987
stomach	63.9233382950196	81.671287114825	74.1203013435583
testicle	75.2201644510493	65.5751232878013	72.3827704118887
cont.diffExp=11.5231276066617,5.77199856059571,2.37888472832746,-1.31761119053925,0.455002849518408,-3.48917677775077,-17.7479488198054,9.645041163248
cont.diffExpScore=6.36656118315786

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=1,0,0,0,0,0,-1,0
cont.diffExp1.2Score=2

tran.correlation=-0.330881762200468
cont.tran.correlation=-0.429802471081619

tran.covariance=-0.00362513905741701
cont.tran.covariance=-0.00222304784022196

tran.mean=72.7673855179817
cont.tran.mean=67.5382361922458

weightedLogRatios:
wLogRatio
Lung	1.4103229652916
cerebhem	-0.985956872901233
cortex	0.730401651316785
heart	1.06494743942893
kidney	1.63082307173077
liver	1.14258932686029
stomach	0.700345349013715
testicle	0.653854814418336

cont.weightedLogRatios:
wLogRatio
Lung	0.768406768324889
cerebhem	0.364468777042427
cortex	0.147858135132153
heart	-0.0839185979701729
kidney	0.0282189568464852
liver	-0.219030989175119
stomach	-1.04872432953842
testicle	0.583445548752096

varWeightedLogRatios=0.639393463135962
cont.varWeightedLogRatios=0.314949325683373

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.73391019907356	0.0752158750565048	62.937647079387	1.04077557157644e-214	***
df.mm.trans1	-0.200594716352665	0.0610081307163004	-3.28799971409497	0.00109473835690090	** 
df.mm.trans2	-0.561795725670071	0.0610081307163004	-9.2085385845131	1.63892357572224e-18	***
df.mm.exp2	-0.181339356375511	0.0824980499966637	-2.19810475984395	0.0284918644160195	*  
df.mm.exp3	-0.217427671364929	0.0824980499966637	-2.63554922054184	0.00871410455581278	** 
df.mm.exp4	-0.195264691871778	0.0824980499966637	-2.36690069498219	0.0183947905945832	*  
df.mm.exp5	0.00933932408639915	0.0824980499966637	0.113206604117029	0.90992137022819	   
df.mm.exp6	0.0274376530950298	0.0824980499966637	0.332585474397751	0.739614738797463	   
df.mm.exp7	-0.180227367587323	0.0824980499966637	-2.18462578927153	0.0294737697916521	*  
df.mm.exp8	-0.0396025084966838	0.0824980499966637	-0.480041752481244	0.631450010732943	   
df.mm.trans1:exp2	-0.239125287769315	0.0665120542805123	-3.59521729340688	0.000363006880517535	***
df.mm.trans2:exp2	0.32124272388617	0.0665120542805123	4.82984215960823	1.92382058143031e-06	***
df.mm.trans1:exp3	0.00686580072875847	0.0665120542805123	0.10322641215985	0.917833021366036	   
df.mm.trans2:exp3	0.158297662523292	0.0665120542805123	2.37998456423669	0.0177631406640464	*  
df.mm.trans1:exp4	0.0645141986914427	0.0665120542805123	0.969962503629136	0.332628787665206	   
df.mm.trans2:exp4	0.138761078841836	0.0665120542805123	2.08625459464259	0.037564133955223	*  
df.mm.trans1:exp5	0.0526845727908952	0.0665120542805123	0.792105631991155	0.428750536161493	   
df.mm.trans2:exp5	0.00510974141341647	0.0665120542805123	0.0768242910054516	0.938800260548957	   
df.mm.trans1:exp6	-0.0321989063917641	0.0665120542805123	-0.484106328395245	0.628565163113787	   
df.mm.trans2:exp6	0.0311879152789689	0.0665120542805123	0.468906209804240	0.639382309497772	   
df.mm.trans1:exp7	0.00215960279495911	0.0665120542805123	0.0324693443665273	0.97411333527122	   
df.mm.trans2:exp7	0.162195311413591	0.0665120542805123	2.43858520336085	0.0151623011066894	*  
df.mm.trans1:exp8	-0.111211009430183	0.0665120542805123	-1.67204291963611	0.0952677816652372	.  
df.mm.trans2:exp8	0.0610019862755981	0.0665120542805123	0.917156851272768	0.359591853424161	   
df.mm.trans1:probe2	0.160596647932532	0.0422676728301743	3.7995147870522	0.000166615632890940	***
df.mm.trans1:probe3	0.119225203761345	0.0422676728301743	2.82071843038001	0.00502097324015616	** 
df.mm.trans1:probe4	-0.35476582037018	0.0422676728301743	-8.39331329632413	7.47609545482468e-16	***
df.mm.trans1:probe5	-0.345380923281473	0.0422676728301743	-8.17127842995203	3.70627748105673e-15	***
df.mm.trans1:probe6	-0.0418485354200451	0.0422676728301743	-0.99008373581831	0.322708712648730	   
df.mm.trans2:probe2	0.0547765716740901	0.0422676728301743	1.29594482038732	0.195713042270327	   
df.mm.trans2:probe3	-0.0893842219012568	0.0422676728301743	-2.11471831582473	0.0350481312609182	*  
df.mm.trans2:probe4	0.0615414364966394	0.0422676728301743	1.45599301726178	0.146148816612665	   
df.mm.trans2:probe5	-0.0773968562190787	0.0422676728301743	-1.83111231436963	0.067798841207554	.  
df.mm.trans2:probe6	0.0546585283719081	0.0422676728301743	1.29315206426241	0.196676123146245	   
df.mm.trans3:probe2	0.321836514960381	0.0422676728301743	7.61424732924085	1.79957332761609e-13	***
df.mm.trans3:probe3	0.828788780403937	0.0422676728301743	19.6081005863251	4.21731550681083e-61	***
df.mm.trans3:probe4	0.0289698565427211	0.0422676728301743	0.685390384730146	0.493479351067861	   
df.mm.trans3:probe5	0.0946832737072761	0.0422676728301743	2.24008721955667	0.0256126283127632	*  
df.mm.trans3:probe6	-0.0429158552900022	0.0422676728301743	-1.01533518210080	0.310536231042087	   
df.mm.trans3:probe7	0.268315029830057	0.0422676728301743	6.347996278577	5.71323626712333e-10	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.08339475797364	0.140930071857211	28.9746163055313	7.84345908633299e-102	***
df.mm.trans1	0.148779948979382	0.114309382683686	1.30155500350380	0.193788865460003	   
df.mm.trans2	-0.0849088024459227	0.114309382683686	-0.742798189024256	0.45802311038552	   
df.mm.exp2	0.199242914242523	0.154574497808812	1.28897662335581	0.198122512566937	   
df.mm.exp3	0.268983252590426	0.154574497808812	1.74015284800163	0.082571679265323	.  
df.mm.exp4	0.145258662568276	0.154574497808812	0.939732392001309	0.347900165794527	   
df.mm.exp5	0.169961269870963	0.154574497808812	1.09954275951252	0.272167292936047	   
df.mm.exp6	0.0423231813394154	0.154574497808812	0.273804424011544	0.784370819203422	   
df.mm.exp7	0.220227502049316	0.154574497808812	1.42473373791392	0.154983940688968	   
df.mm.exp8	0.187177397474656	0.154574497808812	1.21092030139518	0.226613435852620	   
df.mm.trans1:exp2	-0.175707616142203	0.124621944264845	-1.40992517151547	0.159308974858197	   
df.mm.trans2:exp2	-0.0761893520783595	0.124621944264845	-0.61136385351558	0.541292657756248	   
df.mm.trans1:exp3	-0.250272730042584	0.124621944264845	-2.00825570102411	0.0452620454107567	*  
df.mm.trans2:exp3	-0.0989576892989752	0.124621944264845	-0.794063115310345	0.427611413993377	   
df.mm.trans1:exp4	-0.186087465510926	0.124621944264845	-1.49321587468941	0.136138719035223	   
df.mm.trans2:exp4	0.0203385818838936	0.124621944264845	0.163202251448350	0.8704384458739	   
df.mm.trans1:exp5	-0.162520874640273	0.124621944264845	-1.30411121090268	0.192916776411234	   
df.mm.trans2:exp5	0.0171676540474597	0.124621944264845	0.137757873613135	0.89049843098456	   
df.mm.trans1:exp6	-0.0802905129436486	0.124621944264845	-0.644272671376529	0.519753706950668	   
df.mm.trans2:exp6	0.158183157240781	0.124621944264845	1.26930419978533	0.205042249022925	   
df.mm.trans1:exp7	-0.2786332745063	0.124621944264845	-2.23582833785799	0.0258927197754509	*  
df.mm.trans2:exp7	0.152759884854456	0.124621944264845	1.22578640347492	0.220972537057729	   
df.mm.trans1:exp8	-0.0828483568608751	0.124621944264845	-0.664797498944542	0.506548378504284	   
df.mm.trans2:exp8	-0.0336961019084259	0.124621944264845	-0.27038658486033	0.786996951340856	   
df.mm.trans1:probe2	-0.0359091977153502	0.0791958634359913	-0.453422643019394	0.65048085853273	   
df.mm.trans1:probe3	0.0466233051664914	0.0791958634359913	0.588708843412938	0.556376114206338	   
df.mm.trans1:probe4	-0.139211622083565	0.0791958634359913	-1.75781431054263	0.079514538046259	.  
df.mm.trans1:probe5	-0.0183159771155116	0.0791958634359913	-0.231274416628025	0.817215329046399	   
df.mm.trans1:probe6	-0.0622838156241444	0.0791958634359913	-0.786452889354306	0.4320499735322	   
df.mm.trans2:probe2	0.0267261485524513	0.0791958634359913	0.337468996395907	0.73593359124048	   
df.mm.trans2:probe3	0.0486924884523164	0.0791958634359913	0.614836259619434	0.538999012052967	   
df.mm.trans2:probe4	0.149824010379646	0.0791958634359913	1.8918161110869	0.0592097479120013	.  
df.mm.trans2:probe5	0.086582413897672	0.0791958634359913	1.09326939743072	0.274908206575565	   
df.mm.trans2:probe6	0.0941539506102093	0.0791958634359913	1.18887460184467	0.235167210544131	   
df.mm.trans3:probe2	0.109217646838823	0.0791958634359913	1.37908272099459	0.168610238852092	   
df.mm.trans3:probe3	0.0445734198579808	0.0791958634359913	0.562825101263105	0.57385717453497	   
df.mm.trans3:probe4	0.113727873881874	0.0791958634359913	1.43603300662026	0.151744478456806	   
df.mm.trans3:probe5	0.0797901490125224	0.0791958634359913	1.00750399769316	0.314278292171276	   
df.mm.trans3:probe6	0.107478383346173	0.0791958634359913	1.35712117632307	0.175478570237893	   
df.mm.trans3:probe7	-0.00630132208558959	0.0791958634359913	-0.0795663032411096	0.93662045682281