chr4.17394_chr4_108148216_108335218_+_2.R 

fitVsDatCorrelation=0.923201277376897
cont.fitVsDatCorrelation=0.219208734494870

fstatistic=6933.38128803398,68,1060
cont.fstatistic=1062.57900204301,68,1060

residuals=-0.815444975049726,-0.112462560658638,-0.00725919499339186,0.101707264656967,1.51400662197488
cont.residuals=-0.968494219741973,-0.350029252413678,-0.123026194211325,0.200477895411302,2.26826593179443

predictedValues:
Include	Exclude	Both
chr4.17394_chr4_108148216_108335218_+_2.R.tl.Lung	67.0093957965912	64.2876346701067	76.7362331833132
chr4.17394_chr4_108148216_108335218_+_2.R.tl.cerebhem	63.074459694092	57.9803065647221	77.0950117654276
chr4.17394_chr4_108148216_108335218_+_2.R.tl.cortex	80.0095499385038	61.7021582418087	84.4686770229466
chr4.17394_chr4_108148216_108335218_+_2.R.tl.heart	69.7470459345449	63.3710562966272	70.0649753076528
chr4.17394_chr4_108148216_108335218_+_2.R.tl.kidney	66.944458385871	70.3416814578251	81.1874472613413
chr4.17394_chr4_108148216_108335218_+_2.R.tl.liver	67.927737314392	71.3366125812345	80.3544274618013
chr4.17394_chr4_108148216_108335218_+_2.R.tl.stomach	90.635806882847	76.2071537519533	73.8465294373232
chr4.17394_chr4_108148216_108335218_+_2.R.tl.testicle	68.8943852971401	67.629848225778	75.8053332856425


diffExp=2.72176112648449,5.09415312936992,18.3073916966950,6.37598963791768,-3.3972230719541,-3.40887526684241,14.4286531308937,1.2645370713621
diffExpScore=1.29755299838427
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=0,0,1,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	83.4900419647373	59.6403210906363	72.2881865353884
cerebhem	77.2297890562873	79.1326005383005	80.137453740835
cortex	83.5932232655192	101.363913243097	75.691606618907
heart	76.1892569007809	61.3596970374587	76.1787072326577
kidney	90.4470767252704	73.1570627052923	75.4034604665761
liver	85.8606496460191	69.2650050897119	69.7354095343334
stomach	71.3067205933297	64.728353378283	73.396245106419
testicle	80.6981419424301	59.2048925490797	69.2068130293866
cont.diffExp=23.849720874101,-1.90281148201318,-17.7706899775782,14.8295598633222,17.2900140199781,16.5956445563073,6.57836721504667,21.4932493933504
cont.diffExpScore=1.46785717260843

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=1,0,0,0,0,0,0,1
cont.diffExp1.3Score=0.666666666666667
cont.diffExp1.2=1,0,-1,1,1,1,0,1
cont.diffExp1.2Score=1.2

tran.correlation=0.519666068162978
cont.tran.correlation=0.237802902577039

tran.covariance=0.00521655727917991
cont.tran.covariance=0.00341160787270144

tran.mean=69.1937056896274
cont.tran.mean=76.0416716078896

weightedLogRatios:
wLogRatio
Lung	0.17349596662234
cerebhem	0.345457403604402
cortex	1.10484519297059
heart	0.402351664578375
kidney	-0.209321611901192
liver	-0.207755953088947
stomach	0.766427961836328
testicle	0.0782379399233387

cont.weightedLogRatios:
wLogRatio
Lung	1.43187738068376
cerebhem	-0.106095580796048
cortex	-0.871702193599719
heart	0.914571273187316
kidney	0.93320875328657
liver	0.933315883103156
stomach	0.408323066619383
testicle	1.31189395345080

varWeightedLogRatios=0.20855976883533
cont.varWeightedLogRatios=0.602585088884498

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.48531965972862	0.0951972189435267	47.1160786996249	3.00604930129726e-262	***
df.mm.trans1	-0.263029637917506	0.0810623135295648	-3.24478325950535	0.00121214700088754	** 
df.mm.trans2	-0.360085533587585	0.0708093658168204	-5.08528115502552	4.33833394033273e-07	***
df.mm.exp2	-0.168445393991489	0.0888894517283139	-1.89499868337960	0.0583644795628091	.  
df.mm.exp3	0.0402579791010181	0.0888894517283139	0.452899397153046	0.650713868854103	   
df.mm.exp4	0.116633116260091	0.0888894517283138	1.31211424969269	0.189765655191972	   
df.mm.exp5	0.0326410298560298	0.0888894517283138	0.367209260732032	0.713536228971636	   
df.mm.exp6	0.0715808037035462	0.0888894517283138	0.805278942684104	0.420839323656427	   
df.mm.exp7	0.510489527791157	0.0888894517283138	5.74297082348356	1.21438104780828e-08	***
df.mm.exp8	0.0906293082848796	0.0888894517283139	1.01957326232457	0.308163532959471	   
df.mm.trans1:exp2	0.107928477066522	0.0804839781044797	1.34099332076274	0.180209895396098	   
df.mm.trans2:exp2	0.0651814989839478	0.054023244894468	1.20654542523828	0.22787645792891	   
df.mm.trans1:exp3	0.137055177350756	0.0804839781044797	1.70288771229522	0.0888822420981162	.  
df.mm.trans2:exp3	-0.0813063751025049	0.0540232448944679	-1.50502575810345	0.132615356758996	   
df.mm.trans1:exp4	-0.0765908939772668	0.0804839781044796	-0.951629079241597	0.341502061781072	   
df.mm.trans2:exp4	-0.130993190255076	0.054023244894468	-2.42475605660055	0.0154849870897726	*  
df.mm.trans1:exp5	-0.0336105789026535	0.0804839781044796	-0.417605835275962	0.676319901624706	   
df.mm.trans2:exp5	0.0573561957125612	0.0540232448944679	1.06169475426002	0.288616110159505	   
df.mm.trans1:exp6	-0.0579691954610701	0.0804839781044796	-0.720257582022323	0.471525207137198	   
df.mm.trans2:exp6	0.0324615864495638	0.0540232448944679	0.600881833606554	0.548047153525197	   
df.mm.trans1:exp7	-0.208473018692255	0.0804839781044796	-2.59024247560959	0.00972242974393539	** 
df.mm.trans2:exp7	-0.340401494154872	0.0540232448944679	-6.301019030231	4.32793491666572e-10	***
df.mm.trans1:exp8	-0.0628874695222186	0.0804839781044797	-0.781366316667172	0.434761553148518	   
df.mm.trans2:exp8	-0.0399471867943843	0.0540232448944679	-0.739444416425177	0.459800897432227	   
df.mm.trans1:probe2	-0.523294787757838	0.0611319697844298	-8.56008385797377	3.91322865609617e-17	***
df.mm.trans1:probe3	-0.269171000222087	0.0611319697844298	-4.40311348008688	1.17516449357142e-05	***
df.mm.trans1:probe4	-0.362619744593323	0.0611319697844298	-5.93175299065337	4.05312914584615e-09	***
df.mm.trans1:probe5	0.0276739869901377	0.0611319697844298	0.452692545123685	0.650862784143553	   
df.mm.trans1:probe6	-0.199552544591875	0.0611319697844298	-3.26429109507773	0.00113246837269585	** 
df.mm.trans1:probe7	-0.487718508452373	0.0611319697844298	-7.97812519655786	3.83342751124791e-15	***
df.mm.trans1:probe8	-0.308888390241725	0.0611319697844298	-5.05281264992704	5.12439011857029e-07	***
df.mm.trans1:probe9	-0.480898754525603	0.0611319697844298	-7.86656730056958	8.94442692972185e-15	***
df.mm.trans1:probe10	0.454399256682225	0.0611319697844298	7.43308711112332	2.18195416258081e-13	***
df.mm.trans1:probe11	0.747176170621875	0.0611319697844298	12.2223473782482	3.11309534798438e-32	***
df.mm.trans1:probe12	0.282195295693838	0.0611319697844298	4.61616559533327	4.38736532892646e-06	***
df.mm.trans1:probe13	0.605769890404926	0.0611319697844298	9.90921595592384	3.38086517048453e-22	***
df.mm.trans1:probe14	0.653921271734057	0.0611319697844298	10.6968788023678	1.97781886817139e-25	***
df.mm.trans1:probe15	0.349284874724078	0.0611319697844298	5.71362048296112	1.43621449263188e-08	***
df.mm.trans1:probe16	-0.361641320214749	0.0611319697844298	-5.91574787283982	4.45372669635467e-09	***
df.mm.trans1:probe17	-0.331102614644102	0.0611319697844298	-5.41619410942707	7.53148573567198e-08	***
df.mm.trans1:probe18	-0.267437800539579	0.0611319697844298	-4.37476170786983	1.33565825862318e-05	***
df.mm.trans1:probe19	0.00377988925171459	0.0611319697844298	0.0618316286068263	0.950708571976375	   
df.mm.trans1:probe20	-0.398275750658059	0.0611319697844298	-6.5150158266207	1.12103495152786e-10	***
df.mm.trans1:probe21	0.150656344566239	0.0611319697844298	2.46444446494199	0.0138803443534636	*  
df.mm.trans2:probe2	0.187839272115935	0.0611319697844298	3.07268476344398	0.00217558646386474	** 
df.mm.trans2:probe3	0.103450157862026	0.0611319697844298	1.69224316224102	0.0908935054568266	.  
df.mm.trans2:probe4	0.151199163768511	0.0611319697844298	2.47332393020684	0.0135421388496285	*  
df.mm.trans2:probe5	0.331347393738268	0.0611319697844298	5.42019821881581	7.36917826660443e-08	***
df.mm.trans2:probe6	0.217626686481679	0.0611319697844298	3.55994886552973	0.000387372490007743	***
df.mm.trans3:probe2	0.95435472247173	0.0611319697844298	15.6113851040148	1.30861079067143e-49	***
df.mm.trans3:probe3	0.106454909008348	0.0611319697844298	1.74139504065942	0.0819044625316846	.  
df.mm.trans3:probe4	-0.0153440357828559	0.0611319697844298	-0.250998550136102	0.801863875870135	   
df.mm.trans3:probe5	0.03200211699063	0.0611319697844298	0.523492324940278	0.600741110566456	   
df.mm.trans3:probe6	0.253664354257711	0.0611319697844298	4.14945494398773	3.5996794444137e-05	***
df.mm.trans3:probe7	0.130176090076656	0.0611319697844298	2.12942737712685	0.0334488524729822	*  
df.mm.trans3:probe8	2.00557974950484	0.0611319697844298	32.8073797814324	1.68330210843705e-163	***
df.mm.trans3:probe9	0.0712177555820299	0.0611319697844298	1.16498381833868	0.244287644008145	   
df.mm.trans3:probe10	0.233406781943865	0.0611319697844298	3.81808050299915	0.000142289650122745	***
df.mm.trans3:probe11	0.470956785460523	0.0611319697844298	7.70393604395969	3.01984854924774e-14	***
df.mm.trans3:probe12	0.815464443486678	0.0611319697844298	13.3394105631187	1.22840352076808e-37	***
df.mm.trans3:probe13	0.118974848681356	0.0611319697844298	1.94619687703338	0.0518950596699195	.  
df.mm.trans3:probe14	0.345576412434542	0.0611319697844298	5.65295726038522	2.02661031209596e-08	***
df.mm.trans3:probe15	0.198324382602491	0.0611319697844298	3.24420075619752	0.00121460406162737	** 
df.mm.trans3:probe16	0.148504900736070	0.0611319697844298	2.42925103280239	0.0152953899450168	*  
df.mm.trans3:probe17	0.611412977853225	0.0611319697844298	10.0015258793272	1.4469082708109e-22	***
df.mm.trans3:probe18	0.671604308924145	0.0611319697844298	10.9861388614244	1.14803444171784e-26	***
df.mm.trans3:probe19	2.2708421163597	0.0611319697844298	37.1465556298511	4.17562279451675e-194	***
df.mm.trans3:probe20	0.140216578413689	0.0611319697844298	2.29367021720608	0.0220044016270906	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.34118892829488	0.241680382393213	17.9625209349089	3.45217789809021e-63	***
df.mm.trans1	0.182591278474313	0.205795622486889	0.887245687093975	0.375147900786098	   
df.mm.trans2	-0.26976389911182	0.179766119194953	-1.50063816429872	0.133746965118892	   
df.mm.exp2	0.101768332545315	0.225666641555633	0.45096755038217	0.652105171785614	   
df.mm.exp3	0.485613800823445	0.225666641555633	2.15190777633710	0.0316299300504081	*  
df.mm.exp4	-0.115506824019164	0.225666641555633	-0.511847135327215	0.608864613186396	   
df.mm.exp5	0.242121877338956	0.225666641555633	1.07291833507110	0.283551953146769	   
df.mm.exp6	0.213558694380337	0.225666641555633	0.946345870653145	0.344187876796138	   
df.mm.exp7	-0.0910813826526364	0.225666641555633	-0.403610307774188	0.686580708848503	   
df.mm.exp8	0.0022219018760281	0.225666641555633	0.00984594737047274	0.992146050219865	   
df.mm.trans1:exp2	-0.179710448175652	0.204327382886644	-0.87952209653344	0.379317598963123	   
df.mm.trans2:exp2	0.181024726966371	0.137150629284271	1.31989716642978	0.187154322542897	   
df.mm.trans1:exp3	-0.48437871227336	0.204327382886644	-2.37060106888406	0.0179372950171247	*  
df.mm.trans2:exp3	0.0447714681193951	0.137150629284271	0.326440121733584	0.744155826262292	   
df.mm.trans1:exp4	0.0239999243806285	0.204327382886644	0.117458189115764	0.906519226456856	   
df.mm.trans2:exp4	0.143928169910517	0.137150629284271	1.04941676652608	0.294225544523104	   
df.mm.trans1:exp5	-0.162084352091769	0.204327382886644	-0.793258102765842	0.42780498334364	   
df.mm.trans2:exp5	-0.0378450772339901	0.137150629284271	-0.275938050240724	0.782649433878104	   
df.mm.trans1:exp6	-0.185560432109452	0.204327382886644	-0.90815254170997	0.3640040524583	   
df.mm.trans2:exp6	-0.0639507664843002	0.137150629284271	-0.466281247253703	0.641110005053691	   
df.mm.trans1:exp7	-0.0666554032358353	0.204327382886644	-0.326218651137984	0.74432332396521	   
df.mm.trans2:exp7	0.172948842882345	0.137150629284271	1.26101384867783	0.207581325512354	   
df.mm.trans1:exp8	-0.0362337179602402	0.204327382886644	-0.177331679427137	0.859281747184945	   
df.mm.trans2:exp8	-0.00954959268632868	0.137150629284271	-0.0696285006941916	0.944502484517528	   
df.mm.trans1:probe2	-0.214566057898244	0.155197788316861	-1.38253296148894	0.167099319882181	   
df.mm.trans1:probe3	-0.179136697522099	0.155197788316861	-1.15424774711585	0.248658773816013	   
df.mm.trans1:probe4	-0.285175179944332	0.155197788316861	-1.83749512823018	0.0664166068893997	.  
df.mm.trans1:probe5	-0.280435131221330	0.155197788316861	-1.80695314194024	0.0710530423346948	.  
df.mm.trans1:probe6	-0.155320641899666	0.155197788316861	-1.00079159364407	0.317155975491101	   
df.mm.trans1:probe7	0.0227188882305785	0.155197788316861	0.146386675203091	0.883643979839244	   
df.mm.trans1:probe8	-0.217702863272548	0.155197788316861	-1.40274462435040	0.160985820949713	   
df.mm.trans1:probe9	-0.123092581130770	0.155197788316861	-0.793133603679044	0.427877476197171	   
df.mm.trans1:probe10	-0.174618159584197	0.155197788316861	-1.12513304137869	0.260787358011033	   
df.mm.trans1:probe11	-0.247495034041215	0.155197788316861	-1.59470722312044	0.111075817970069	   
df.mm.trans1:probe12	-0.17974208060654	0.155197788316861	-1.15814846690706	0.247064325127957	   
df.mm.trans1:probe13	-0.211924788742923	0.155197788316861	-1.36551423213741	0.172381175451058	   
df.mm.trans1:probe14	-0.210976185395846	0.155197788316861	-1.35940201006669	0.174308350748595	   
df.mm.trans1:probe15	-0.246618901753631	0.155197788316861	-1.58906196040706	0.112344605216678	   
df.mm.trans1:probe16	-0.218977625825288	0.155197788316861	-1.41095841764323	0.158550289883039	   
df.mm.trans1:probe17	-0.178716153728759	0.155197788316861	-1.15153801911069	0.249770628949638	   
df.mm.trans1:probe18	-0.332345759321925	0.155197788316861	-2.14143360499048	0.0324665619938893	*  
df.mm.trans1:probe19	-0.210139710165673	0.155197788316861	-1.35401227327183	0.176021055572946	   
df.mm.trans1:probe20	-0.351087750328892	0.155197788316861	-2.26219557724682	0.0238871368342862	*  
df.mm.trans1:probe21	-0.0658140230387848	0.155197788316861	-0.424065469956407	0.671604110580116	   
df.mm.trans2:probe2	0.208284462747669	0.155197788316861	1.34205818914392	0.179864514284179	   
df.mm.trans2:probe3	0.0646082431819865	0.155197788316861	0.416296159131330	0.677277577101849	   
df.mm.trans2:probe4	0.144844675221768	0.155197788316861	0.933290846426522	0.350882356102646	   
df.mm.trans2:probe5	-0.038408035206449	0.155197788316861	-0.247477980343591	0.804586257008236	   
df.mm.trans2:probe6	0.06024861137917	0.155197788316861	0.388205347721597	0.69794202604016	   
df.mm.trans3:probe2	-0.0186080614223876	0.155197788316861	-0.119899011604445	0.904585867814843	   
df.mm.trans3:probe3	0.112324582577191	0.155197788316861	0.723751180963111	0.469378193114429	   
df.mm.trans3:probe4	0.0134849311496895	0.155197788316861	0.0868886811850557	0.930776406762825	   
df.mm.trans3:probe5	0.0518647443535564	0.155197788316861	0.33418481613711	0.738306205876792	   
df.mm.trans3:probe6	-0.128908943720540	0.155197788316861	-0.830610700826174	0.406380627674609	   
df.mm.trans3:probe7	0.0931563999575337	0.155197788316861	0.60024308959442	0.548472540588832	   
df.mm.trans3:probe8	0.156215296390302	0.155197788316861	1.00655620215001	0.314377802136697	   
df.mm.trans3:probe9	0.113154382250871	0.155197788316861	0.72909790453874	0.466102836708862	   
df.mm.trans3:probe10	-0.0424943025091579	0.155197788316861	-0.273807397450787	0.784285982019048	   
df.mm.trans3:probe11	0.152665609629515	0.155197788316861	0.983684183165184	0.325495286759891	   
df.mm.trans3:probe12	0.00723453560260025	0.155197788316861	0.0466149400778172	0.96282890500601	   
df.mm.trans3:probe13	-0.00615146448492967	0.155197788316861	-0.039636289612391	0.96839055897326	   
df.mm.trans3:probe14	0.0254542588857098	0.155197788316861	0.164011737291905	0.869753170735591	   
df.mm.trans3:probe15	-0.0673960354491074	0.155197788316861	-0.434258994152079	0.664188755059819	   
df.mm.trans3:probe16	-0.0687577969178716	0.155197788316861	-0.443033355459238	0.657832007006154	   
df.mm.trans3:probe17	0.0675070366470614	0.155197788316861	0.434974218248748	0.663669683257225	   
df.mm.trans3:probe18	0.0395591879711078	0.155197788316861	0.254895307466247	0.79885340449097	   
df.mm.trans3:probe19	0.0390135368489147	0.155197788316861	0.251379464050494	0.801569467029859	   
df.mm.trans3:probe20	-0.0064296363124486	0.155197788316861	-0.0414286594040983	0.966961967321938