chr16.9192_chr16_20472899_20473770_+_2.R 

fitVsDatCorrelation=0.898584142793342
cont.fitVsDatCorrelation=0.255970973513735

fstatistic=11283.2502941026,61,899
cont.fstatistic=2313.17849590847,61,899

residuals=-0.663314627346451,-0.0956629132276208,-0.00406626342911356,0.0933859981193395,0.762982521044211
cont.residuals=-0.768396007606804,-0.260611573249050,-0.0434368972492259,0.239119915301129,1.02231633687757

predictedValues:
Include	Exclude	Both
chr16.9192_chr16_20472899_20473770_+_2.R.tl.Lung	72.6845536605231	52.9224632547495	77.439726039028
chr16.9192_chr16_20472899_20473770_+_2.R.tl.cerebhem	53.6515441781044	44.4069429273676	74.1501193612514
chr16.9192_chr16_20472899_20473770_+_2.R.tl.cortex	68.5729682264977	47.727021824931	77.4705753108787
chr16.9192_chr16_20472899_20473770_+_2.R.tl.heart	67.674109676427	51.9148081077394	74.2538309647621
chr16.9192_chr16_20472899_20473770_+_2.R.tl.kidney	76.5161267386393	55.0108129392723	79.6245366257661
chr16.9192_chr16_20472899_20473770_+_2.R.tl.liver	73.3165045893336	54.4652887222814	80.1608906180627
chr16.9192_chr16_20472899_20473770_+_2.R.tl.stomach	67.4612566277005	47.1587787748405	74.932065453705
chr16.9192_chr16_20472899_20473770_+_2.R.tl.testicle	67.8528215901137	55.0726511468116	75.6626223375178


diffExp=19.7620904057736,9.24460125073685,20.8459464015666,15.7593015686877,21.5053137993670,18.8512158670522,20.3024778528601,12.7801704433021
diffExpScore=0.9928597499455
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,1,0,0,0,1,0
diffExp1.4Score=0.666666666666667
diffExp1.3=1,0,1,1,1,1,1,0
diffExp1.3Score=0.857142857142857
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	71.0158365763304	75.3993634999315	71.0077093277884
cerebhem	74.6330009164252	74.8729321121752	70.4066757374363
cortex	73.2675719020288	75.1803451790867	74.9305981137734
heart	73.2435112440957	65.7129665670734	79.7823808109067
kidney	74.1819285270569	67.2579893949344	72.7931680489939
liver	73.8810474249224	70.034151293478	75.9023771953675
stomach	70.2696997607507	65.5786978508025	70.9644141422063
testicle	76.318377798604	68.6497349388046	75.5000495560842
cont.diffExp=-4.38352692360107,-0.239931195750017,-1.91277327705794,7.5305446770223,6.92393913212244,3.84689613144434,4.69100190994817,7.66864285979945
cont.diffExpScore=1.48049998429741

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

tran.correlation=0.788861038346976
cont.tran.correlation=0.0177283808734524

tran.covariance=0.00699840255371889
cont.tran.covariance=5.17418420892644e-05

tran.mean=59.7755408115833
cont.tran.mean=71.8435721866563

weightedLogRatios:
wLogRatio
Lung	1.30965306271236
cerebhem	0.735267990633634
cortex	1.46652611269582
heart	1.08217740038553
kidney	1.37681233463752
liver	1.23233496629691
stomach	1.44378237271472
testicle	0.858332019982753

cont.weightedLogRatios:
wLogRatio
Lung	-0.257124298489209
cerebhem	-0.0138470635848862
cortex	-0.110998904283695
heart	0.459962405211853
kidney	0.417172864492765
liver	0.228636985403679
stomach	0.291406572422461
testicle	0.453445163977882

varWeightedLogRatios=0.0743231637172493
cont.varWeightedLogRatios=0.0767730319433611

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.29553227772916	0.0733671524048401	44.918361551562	5.67033772022855e-232	***
df.mm.trans1	0.831524524330264	0.0627234236831391	13.2570015395028	9.0853932329549e-37	***
df.mm.trans2	0.644410144666173	0.0552988972119785	11.6532187286835	2.51349289260110e-29	***
df.mm.exp2	-0.435642472558929	0.070326996778421	-6.1945268888917	8.88712183764536e-10	***
df.mm.exp3	-0.161958924988338	0.070326996778421	-2.30294100995982	0.0215096943622293	*  
df.mm.exp4	-0.0486384976301101	0.070326996778421	-0.691604929233011	0.489364027705635	   
df.mm.exp5	0.0622521212364928	0.070326996778421	0.885180998594754	0.376295709792041	   
df.mm.exp6	0.00285672047106333	0.070326996778421	0.0406205383696958	0.967607429517453	   
df.mm.exp7	-0.156965146733751	0.070326996778421	-2.23193302606537	0.0258651187501855	*  
df.mm.exp8	-0.00574693827209619	0.070326996778421	-0.0817173850065437	0.934889642597788	   
df.mm.trans1:exp2	0.132023828542805	0.0639336334349282	2.06501369388273	0.0392079338547149	*  
df.mm.trans2:exp2	0.260210417082791	0.0456577467352234	5.69915152825638	1.63184137145161e-08	***
df.mm.trans1:exp3	0.103728437763658	0.0639336334349282	1.62243927320716	0.105059930462455	   
df.mm.trans2:exp3	0.058628772838866	0.0456577467352234	1.28409255890054	0.199440398103338	   
df.mm.trans1:exp4	-0.0227867179494310	0.0639336334349282	-0.356412059274301	0.721615628601975	   
df.mm.trans2:exp4	0.0294146821734603	0.0456577467352234	0.644242965909833	0.519582227720928	   
df.mm.trans1:exp5	-0.0108794907019706	0.0639336334349282	-0.170168503140741	0.864915907905674	   
df.mm.trans2:exp5	-0.0235502413586549	0.0456577467352234	-0.515799465427554	0.606121300732697	   
df.mm.trans1:exp6	0.00580013288291861	0.0639336334349282	0.0907211520962906	0.927734371801923	   
df.mm.trans2:exp6	0.0258789891827238	0.0456577467352234	0.566803905869474	0.570988898815886	   
df.mm.trans1:exp7	0.0823897088167767	0.0639336334349282	1.28867552789148	0.197842438967706	   
df.mm.trans2:exp7	0.041657441780552	0.0456577467352234	0.912384967706142	0.361810698195	   
df.mm.trans1:exp8	-0.0630409857285763	0.0639336334349282	-0.986037901204841	0.324379813062981	   
df.mm.trans2:exp8	0.0455722968586952	0.0456577467352234	0.998128469260129	0.318485643284337	   
df.mm.trans1:probe2	0.0961998268205065	0.0463243184429159	2.07665930237162	0.0381165846656392	*  
df.mm.trans1:probe3	0.146337205450929	0.0463243184429159	3.15897158058042	0.00163615912448658	** 
df.mm.trans1:probe4	0.171775198747475	0.0463243184429159	3.70809986031739	0.000221613849252266	***
df.mm.trans1:probe5	0.165724756227101	0.0463243184429159	3.57748935758911	0.000365435302722679	***
df.mm.trans1:probe6	-0.195221267038259	0.0463243184429159	-4.21422858662939	2.75932054903823e-05	***
df.mm.trans1:probe7	0.134959179016161	0.0463243184429159	2.91335487606726	0.00366425663270891	** 
df.mm.trans1:probe8	-0.166280306180428	0.0463243184429159	-3.58948197770745	0.000349256612979604	***
df.mm.trans1:probe9	0.371080081831602	0.0463243184429159	8.01048119658518	3.52836332837789e-15	***
df.mm.trans1:probe10	0.196250105835272	0.0463243184429159	4.23643806173003	2.50498903958760e-05	***
df.mm.trans1:probe11	0.230001010198235	0.0463243184429159	4.96501660314029	8.21839179296367e-07	***
df.mm.trans1:probe12	0.37575282010764	0.0463243184429159	8.11135128886287	1.63431995849027e-15	***
df.mm.trans1:probe13	0.25123233782448	0.0463243184429159	5.4233358691303	7.52114634777993e-08	***
df.mm.trans1:probe14	0.113891670793849	0.0463243184429159	2.45857196872081	0.0141366494472191	*  
df.mm.trans1:probe15	0.872705898409518	0.0463243184429159	18.8390445395312	5.52221774210854e-67	***
df.mm.trans1:probe16	0.623840975834676	0.0463243184429159	13.4668139068990	8.64833211771948e-38	***
df.mm.trans1:probe17	0.7170562724778	0.0463243184429159	15.4790463536211	4.34087139426291e-48	***
df.mm.trans1:probe18	0.394138955804075	0.0463243184429159	8.50825158474293	7.31946220670596e-17	***
df.mm.trans1:probe19	0.470634822686511	0.0463243184429159	10.1595628064439	4.97928423402022e-23	***
df.mm.trans1:probe20	0.438371619291402	0.0463243184429159	9.46309916748358	2.53944069989140e-20	***
df.mm.trans2:probe2	0.0254833782320457	0.0463243184429159	0.550108001339471	0.582381944196381	   
df.mm.trans2:probe3	0.204074357914567	0.0463243184429159	4.40533967415067	1.18340674440062e-05	***
df.mm.trans2:probe4	0.123538741741786	0.0463243184429159	2.66682265156301	0.00779480007827596	** 
df.mm.trans2:probe5	0.130353929235029	0.0463243184429159	2.81394165346782	0.00500060623839849	** 
df.mm.trans2:probe6	0.0942588435191495	0.0463243184429159	2.03475942415217	0.0421680699299914	*  
df.mm.trans3:probe2	-0.181504140605945	0.0463243184429159	-3.91811788509327	9.60097860118637e-05	***
df.mm.trans3:probe3	-0.700657063553761	0.0463243184429159	-15.1250377146328	3.25003599687683e-46	***
df.mm.trans3:probe4	-0.483463305797512	0.0463243184429159	-10.4364904233458	3.79409724963472e-24	***
df.mm.trans3:probe5	-0.82574836302061	0.0463243184429159	-17.8253753271763	4.29616807978082e-61	***
df.mm.trans3:probe6	-0.745797899553999	0.0463243184429159	-16.0994899573757	1.96659704199401e-51	***
df.mm.trans3:probe7	-0.0126385362466952	0.0463243184429159	-0.272827246498387	0.785048669886518	   
df.mm.trans3:probe8	-0.106390273795566	0.0463243184429159	-2.29663980759193	0.0218684821799211	*  
df.mm.trans3:probe9	0.243827053374323	0.0463243184429159	5.26347848322439	1.76865100569281e-07	***
df.mm.trans3:probe10	-0.88110983571222	0.0463243184429159	-19.0204597785499	4.70745235693983e-68	***
df.mm.trans3:probe11	-0.904844603623933	0.0463243184429159	-19.5328206444947	4.26443533260251e-71	***
df.mm.trans3:probe12	-0.51068738657738	0.0463243184429159	-11.0241748555175	1.35157912296986e-26	***
df.mm.trans3:probe13	-0.241602204289032	0.0463243184429159	-5.21545081309185	2.27669509238584e-07	***
df.mm.trans3:probe14	-0.556922021355442	0.0463243184429159	-12.0222388601728	5.59087594425078e-31	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.23280637138527	0.161628724735880	26.1884536817460	8.47868051020558e-113	***
df.mm.trans1	0.0562372739231469	0.138180461537243	0.40698426751158	0.684116420970599	   
df.mm.trans2	0.0807651637821023	0.121824139859665	0.662965187976206	0.507522791755377	   
df.mm.exp2	0.0511738519840405	0.154931225094824	0.330300441068095	0.741249915846024	   
df.mm.exp3	-0.025467671219699	0.154931225094824	-0.164380493371248	0.869468569264667	   
df.mm.exp4	-0.223130044357004	0.154931225094824	-1.44018769760866	0.150162447530634	   
df.mm.exp5	-0.0954790054637248	0.154931225094824	-0.616267026903635	0.537874305486396	   
df.mm.exp6	-0.100921955343304	0.154931225094824	-0.651398420696254	0.514955804352899	   
df.mm.exp7	-0.149500216900477	0.154931225094824	-0.964945683537822	0.33483151043904	   
df.mm.exp8	-0.08311555246181	0.154931225094824	-0.536467406172902	0.591768277310752	   
df.mm.trans1:exp2	-0.00149397359804665	0.140846568268022	-0.0106070997427762	0.991539270897803	   
df.mm.trans2:exp2	-0.0581802471300588	0.100584568669195	-0.578421202176682	0.563124651547277	   
df.mm.trans1:exp3	0.056682877255364	0.140846568268022	0.402444148639108	0.687452855106023	   
df.mm.trans2:exp3	0.0225586673809202	0.100584568669195	0.224275628750885	0.822593798776242	   
df.mm.trans1:exp4	0.25401680209193	0.140846568268022	1.80350011516470	0.0716443975589104	.  
df.mm.trans2:exp4	0.0856274772712192	0.100584568669195	0.851298349280921	0.394830336952488	   
df.mm.trans1:exp5	0.139096672585314	0.140846568268022	0.98757587277968	0.323626125041859	   
df.mm.trans2:exp5	-0.0187840150318003	0.100584568669195	-0.186748477229918	0.851899979088957	   
df.mm.trans1:exp6	0.140475385414904	0.140846568268022	0.997364629769248	0.318855923911747	   
df.mm.trans2:exp6	0.0271061207083527	0.100584568669195	0.269485877078222	0.787617648850235	   
df.mm.trans1:exp7	0.138938006903420	0.140846568268022	0.986449358418378	0.324178065026782	   
df.mm.trans2:exp7	0.0099522988980878	0.100584568669195	0.09894458990841	0.921204322480754	   
df.mm.trans1:exp8	0.155126421576432	0.140846568268022	1.10138588028100	0.271023538325006	   
df.mm.trans2:exp8	-0.010666009716117	0.100584568669195	-0.106040219262615	0.91557409787953	   
df.mm.trans1:probe2	-0.151061410559638	0.102053034208990	-1.48022458842611	0.13916366796901	   
df.mm.trans1:probe3	-0.0800911076092501	0.102053034208990	-0.784798886481272	0.432778246467296	   
df.mm.trans1:probe4	0.157080835554465	0.102053034208990	1.53920789099506	0.124105434115207	   
df.mm.trans1:probe5	-0.0446509500567077	0.102053034208990	-0.437526923161042	0.661834343438527	   
df.mm.trans1:probe6	0.0767031933878837	0.102053034208990	0.751601302032891	0.452487572403554	   
df.mm.trans1:probe7	-0.044253307146303	0.102053034208990	-0.433630489179565	0.664660822848207	   
df.mm.trans1:probe8	-0.038691687113378	0.102053034208990	-0.379133138110751	0.70467852741498	   
df.mm.trans1:probe9	-0.0697078955621206	0.102053034208990	-0.683055590678167	0.494747700379329	   
df.mm.trans1:probe10	-0.0600214279961217	0.102053034208990	-0.588139573324265	0.556586326758451	   
df.mm.trans1:probe11	0.0720937217337547	0.102053034208990	0.706433887953957	0.480101393861327	   
df.mm.trans1:probe12	0.00599763544470538	0.102053034208990	0.0587697905426615	0.953148531056624	   
df.mm.trans1:probe13	-0.0255431378049423	0.102053034208990	-0.250292781620131	0.802418124410772	   
df.mm.trans1:probe14	-0.0229376957222141	0.102053034208990	-0.22476250608327	0.822215111390932	   
df.mm.trans1:probe15	-0.0575389533464181	0.102053034208990	-0.563814234357666	0.573021176834565	   
df.mm.trans1:probe16	-0.0987988069887074	0.102053034208990	-0.968112391311973	0.333248612896922	   
df.mm.trans1:probe17	-0.0432716402191108	0.102053034208990	-0.42401130504848	0.671659004304961	   
df.mm.trans1:probe18	-0.172706771064971	0.102053034208990	-1.69232372563557	0.0909307742956542	.  
df.mm.trans1:probe19	-0.109231659615362	0.102053034208990	-1.07034210655287	0.284752625435655	   
df.mm.trans1:probe20	-0.182154189437231	0.102053034208990	-1.78489734135887	0.0746150640981002	.  
df.mm.trans2:probe2	0.0799018423050672	0.102053034208990	0.782944308558627	0.433866009820491	   
df.mm.trans2:probe3	-0.0130253585169505	0.102053034208990	-0.127633231269504	0.898467774694728	   
df.mm.trans2:probe4	-0.00655751800066615	0.102053034208990	-0.0642559827004979	0.948780686239228	   
df.mm.trans2:probe5	0.0446824990236547	0.102053034208990	0.437836066021825	0.661610296587533	   
df.mm.trans2:probe6	0.0795444984976405	0.102053034208990	0.77944275850481	0.435924079836619	   
df.mm.trans3:probe2	-0.271211530447423	0.102053034208990	-2.65755479540198	0.0080106544195897	** 
df.mm.trans3:probe3	-0.0996511736887042	0.102053034208990	-0.976464584919967	0.329096966349446	   
df.mm.trans3:probe4	0.0550633882505645	0.102053034208990	0.539556600912059	0.589636460439785	   
df.mm.trans3:probe5	-0.162626948652043	0.102053034208990	-1.59355329229121	0.111387622774856	   
df.mm.trans3:probe6	-0.263585372172055	0.102053034208990	-2.58282739180759	0.00995643295694065	** 
df.mm.trans3:probe7	-0.0366147626636722	0.102053034208990	-0.358781715286295	0.719842632510675	   
df.mm.trans3:probe8	-0.203731591358523	0.102053034208990	-1.99633056417814	0.0461991615434946	*  
df.mm.trans3:probe9	-0.152437830206805	0.102053034208990	-1.49371188606342	0.135601818699021	   
df.mm.trans3:probe10	-0.00682421598146862	0.102053034208990	-0.0668693100049689	0.946700613425118	   
df.mm.trans3:probe11	-0.140283167842250	0.102053034208990	-1.37461045553012	0.169594776107894	   
df.mm.trans3:probe12	-0.109315294844192	0.102053034208990	-1.07116163366913	0.28438423945618	   
df.mm.trans3:probe13	-0.0183509082668665	0.102053034208990	-0.179817370537818	0.857336468025184	   
df.mm.trans3:probe14	-0.0887155741985228	0.102053034208990	-0.86930854027178	0.384910419422642