chr11.3789_chr11_97664641_97665310_-_0.R 

fitVsDatCorrelation=0.894064706770402
cont.fitVsDatCorrelation=0.266273471030978

fstatistic=11866.6920423008,51,669
cont.fstatistic=2552.44862738099,51,669

residuals=-0.787019000421036,-0.0800641709406334,-0.00437459771655394,0.0870640207094493,0.538689759208844
cont.residuals=-0.617922111842198,-0.206007196842832,-0.054424248242658,0.119504604438660,1.26911304914589

predictedValues:
Include	Exclude	Both
chr11.3789_chr11_97664641_97665310_-_0.R.tl.Lung	67.1842641887746	58.4564912052617	63.9577838260742
chr11.3789_chr11_97664641_97665310_-_0.R.tl.cerebhem	68.2924255369168	49.5266244503974	59.8539447117591
chr11.3789_chr11_97664641_97665310_-_0.R.tl.cortex	67.4595583261967	55.1936837637169	58.567633878561
chr11.3789_chr11_97664641_97665310_-_0.R.tl.heart	68.0758594269704	57.594719593922	62.3708960476195
chr11.3789_chr11_97664641_97665310_-_0.R.tl.kidney	71.5188923270776	59.4126261951195	64.1547900310524
chr11.3789_chr11_97664641_97665310_-_0.R.tl.liver	77.3712176580285	57.7615855446276	67.7924164740313
chr11.3789_chr11_97664641_97665310_-_0.R.tl.stomach	69.675711937268	52.4616695768865	65.2331008976892
chr11.3789_chr11_97664641_97665310_-_0.R.tl.testicle	68.4441045656615	53.9576902208492	64.184806116687


diffExp=8.7277729835129,18.7658010865194,12.2658745624798,10.4811398330484,12.1062661319581,19.6096321134009,17.2140423603816,14.4864143448123
diffExpScore=0.991278330206564
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=0,1,0,0,0,1,1,0
diffExp1.3Score=0.75
diffExp1.2=0,1,1,0,1,1,1,1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	60.1248799413105	62.4088433091301	55.0665831786879
cerebhem	67.3970192974575	64.5211561267116	61.813477000414
cortex	66.6848744674351	60.8194108979304	59.4512716810956
heart	65.9837159304784	53.3122516068197	64.9579693379398
kidney	66.472967410832	60.6090994083662	61.1246386298427
liver	70.9888035061181	63.6638963204742	64.679400511325
stomach	71.6386101155337	65.4022793276565	60.0769926289955
testicle	63.8297132474746	58.7889349827555	67.4224220934381
cont.diffExp=-2.28396336781957,2.87586317074584,5.86546356950468,12.6714643236586,5.86386800246574,7.32490718564386,6.23633078787715,5.04077826471909
cont.diffExpScore=1.08000784354647

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

tran.correlation=0.307751279700391
cont.tran.correlation=0.384320696359982

tran.covariance=0.000882643957424069
cont.tran.covariance=0.00128274798375106

tran.mean=62.6491952823547
cont.tran.mean=63.9154034935303

weightedLogRatios:
wLogRatio
Lung	0.575809490136636
cerebhem	1.30544472468805
cortex	0.825032302918216
heart	0.691676843383804
kidney	0.77468845627959
liver	1.22834356936433
stomach	1.16401112319061
testicle	0.976741101406084

cont.weightedLogRatios:
wLogRatio
Lung	-0.15342302461826
cerebhem	0.182663470759854
cortex	0.382450101595718
heart	0.870620935076437
kidney	0.383311115396442
liver	0.458277926312167
stomach	0.384900392171881
testicle	0.338528186879471

varWeightedLogRatios=0.0718583183232286
cont.varWeightedLogRatios=0.0810626852810253

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.86758619248558	0.0698406790565585	55.3772707357774	4.79325673302711e-252	***
df.mm.trans1	0.349705599712505	0.0550528527050423	6.35217945173758	3.92256677930764e-10	***
df.mm.trans2	0.194238152712875	0.0550528527050423	3.52821231178607	0.00044700759320181	***
df.mm.exp2	-0.0830966423181896	0.0728280786111057	-1.14099731728358	0.254279310186229	   
df.mm.exp3	0.0346960277734231	0.0728280786111057	0.476410039027616	0.633937838979498	   
df.mm.exp4	0.0234562401874014	0.0728280786111057	0.322076877967017	0.747495069772093	   
df.mm.exp5	0.075671095929269	0.0728280786111057	1.039037379159	0.299162728378749	   
df.mm.exp6	0.0709898983471903	0.0728280786111057	0.974760006044769	0.330031640223065	   
df.mm.exp7	-0.0915309873554836	0.0728280786111057	-1.25680903713318	0.209261422362547	   
df.mm.exp8	-0.0650474280899222	0.0728280786111057	-0.893164138481103	0.372090450160106	   
df.mm.trans1:exp2	0.0994564465954094	0.0550528527050423	1.80656299734855	0.0712796631580649	.  
df.mm.trans2:exp2	-0.0826757024662948	0.0550528527050423	-1.50175146979663	0.133633136072447	   
df.mm.trans1:exp3	-0.0306068016077217	0.0550528527050423	-0.5559530542714	0.57842882979536	   
df.mm.trans2:exp3	-0.0921302430526608	0.0550528527050423	-1.67348717688198	0.0946988914688598	.  
df.mm.trans1:exp4	-0.0102726332506076	0.0550528527050423	-0.186595839195572	0.852034097954703	   
df.mm.trans2:exp4	-0.0383080878494303	0.0550528527050423	-0.695842013031991	0.486769427722871	   
df.mm.trans1:exp5	-0.0131485090316803	0.0550528527050423	-0.238834290788278	0.811307222136244	   
df.mm.trans2:exp5	-0.0594470673863656	0.0550528527050423	-1.07981811051402	0.280612319012468	   
df.mm.trans1:exp6	0.070185891955301	0.0550528527050423	1.27488201803705	0.202793592746068	   
df.mm.trans2:exp6	-0.0829486910194474	0.0550528527050423	-1.50671013296737	0.132356998535762	   
df.mm.trans1:exp7	0.127943722393336	0.0550528527050423	2.32401621545067	0.0204232482932998	*  
df.mm.trans2:exp7	-0.0166689504444998	0.0550528527050423	-0.302780866484927	0.762150985692686	   
df.mm.trans1:exp8	0.0836257922625073	0.0550528527050423	1.51900924572521	0.129232594959699	   
df.mm.trans2:exp8	-0.0150350843273287	0.0550528527050423	-0.273102729260597	0.784858531586391	   
df.mm.trans1:probe2	-0.131186143390762	0.0412896395287817	-3.17721696987245	0.00155538036607552	** 
df.mm.trans1:probe3	0.101414930773434	0.0412896395287817	2.45618348648311	0.0142952195391962	*  
df.mm.trans1:probe4	-0.0596490597151849	0.0412896395287817	-1.44464956332703	0.149024531038782	   
df.mm.trans1:probe5	-0.0583189937452885	0.0412896395287817	-1.41243649522869	0.158286483293249	   
df.mm.trans1:probe6	-0.088726396653521	0.0412896395287817	-2.14887796711503	0.0320022386531888	*  
df.mm.trans2:probe2	0.0255982145053744	0.0412896395287817	0.619967013456987	0.535490608028095	   
df.mm.trans2:probe3	-0.0947222241703587	0.0412896395287817	-2.29409181701213	0.0220942139218430	*  
df.mm.trans2:probe4	0.00920319932283285	0.0412896395287817	0.222893670854588	0.823686298096712	   
df.mm.trans2:probe5	0.136583020245895	0.0412896395287817	3.30792474346226	0.000990230973483458	***
df.mm.trans2:probe6	0.0783392040121742	0.0412896395287817	1.89730898371168	0.0582175097254282	.  
df.mm.trans3:probe2	0.614707915366776	0.0412896395287817	14.8877036075426	1.65273070646946e-43	***
df.mm.trans3:probe3	0.225767289059782	0.0412896395287817	5.4678919854073	6.43672894000367e-08	***
df.mm.trans3:probe4	-0.460033056250161	0.0412896395287817	-11.1416098929487	1.45114102370077e-26	***
df.mm.trans3:probe5	-0.407307008394086	0.0412896395287817	-9.8646297967839	1.60104640211384e-21	***
df.mm.trans3:probe6	-0.078479168179519	0.0412896395287817	-1.90069879696609	0.0577710215914692	.  
df.mm.trans3:probe7	-0.140306791246016	0.0412896395287817	-3.39811131429745	0.000718760178760816	***
df.mm.trans3:probe8	-0.320641881621810	0.0412896395287817	-7.76567403545144	3.05638722396198e-14	***
df.mm.trans3:probe9	0.321463221789709	0.0412896395287817	7.78556619671208	2.64616536610992e-14	***
df.mm.trans3:probe10	-0.226196219882550	0.0412896395287817	-5.47828032562203	6.085406142786e-08	***
df.mm.trans3:probe11	-0.556699438326192	0.0412896395287817	-13.4827875631642	7.98094457676369e-37	***
df.mm.trans3:probe12	-0.566306459727623	0.0412896395287817	-13.7154614617759	6.60312637507325e-38	***
df.mm.trans3:probe13	-0.553960926999767	0.0412896395287817	-13.4164631447949	1.61684310730297e-36	***
df.mm.trans3:probe14	-0.474083243778251	0.0412896395287817	-11.4818935013415	5.59356676612185e-28	***
df.mm.trans3:probe15	-0.47551955028488	0.0412896395287817	-11.516679625004	3.9953747827115e-28	***
df.mm.trans3:probe16	-0.435345054542543	0.0412896395287817	-10.5436874603635	3.76886435788266e-24	***
df.mm.trans3:probe17	-0.48016679852172	0.0412896395287817	-11.6292320301564	1.33895215520708e-28	***
df.mm.trans3:probe18	-0.546413553002354	0.0412896395287817	-13.2336721569455	1.12008485556638e-35	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.19435290631444	0.150287055660892	27.908943241117	2.88541890467229e-114	***
df.mm.trans1	-0.090387411598718	0.118465788857427	-0.762983241579547	0.445742340833876	   
df.mm.trans2	-0.0717183644611236	0.118465788857427	-0.605393043450174	0.54512317983761	   
df.mm.exp2	0.0318848893777457	0.156715508092920	0.203457141962240	0.838839609338676	   
df.mm.exp3	0.00114247979113113	0.156715508092920	0.0072901514663994	0.994185525526374	   
df.mm.exp4	-0.22975394621159	0.156715508092920	-1.46605750131228	0.143102475739098	   
df.mm.exp5	-0.0332622991641463	0.156715508092920	-0.212246379244258	0.83197947488447	   
df.mm.exp6	0.0251093661707316	0.156715508092920	0.160222600024011	0.87275409184993	   
df.mm.exp7	0.13497667556944	0.156715508092920	0.861284739538411	0.389389823218173	   
df.mm.exp8	-0.202392831502439	0.156715508092920	-1.29146651767505	0.196987980000508	   
df.mm.trans1:exp2	0.08229217188346	0.118465788857427	0.694649254245865	0.487516305854837	   
df.mm.trans2:exp2	0.00140129757592632	0.118465788857427	0.0118287109674572	0.990565800701931	   
df.mm.trans1:exp3	0.10241194620485	0.118465788857427	0.864485411295425	0.387631147527100	   
df.mm.trans2:exp3	-0.0269404686131085	0.118465788857427	-0.227411380728078	0.820173350024426	   
df.mm.trans1:exp4	0.322738197863678	0.118465788857427	2.72431561023994	0.00661177111145803	** 
df.mm.trans2:exp4	0.0722131272288157	0.118465788857427	0.609569462418586	0.542354011396234	   
df.mm.trans1:exp5	0.133633927474277	0.118465788857427	1.12803813457997	0.259708194388813	   
df.mm.trans2:exp5	0.00400035118912027	0.118465788857427	0.0337679867555237	0.973072236465273	   
df.mm.trans1:exp6	0.140989069732350	0.118465788857427	1.19012477013114	0.234419512277580	   
df.mm.trans2:exp6	-0.00519872606161461	0.118465788857427	-0.0438837753224371	0.965010142908313	   
df.mm.trans1:exp7	0.0402337688733588	0.118465788857427	0.339623525588301	0.734246651353794	   
df.mm.trans2:exp7	-0.0881265506404605	0.118465788857427	-0.74389873642356	0.457198927075459	   
df.mm.trans1:exp8	0.262187906713246	0.118465788857427	2.21319512782536	0.0272209204452857	*  
df.mm.trans2:exp8	0.142639503101762	0.118465788857427	1.20405650000295	0.228993573766300	   
df.mm.trans1:probe2	-0.073742775987778	0.0888493416430705	-0.829975491366281	0.406848706338675	   
df.mm.trans1:probe3	-0.0481559960654122	0.0888493416430705	-0.541996093329162	0.588001669235066	   
df.mm.trans1:probe4	0.00582073167020085	0.0888493416430705	0.0655123781736521	0.947785622635313	   
df.mm.trans1:probe5	-0.110081925585377	0.0888493416430705	-1.23897288994670	0.215790044270878	   
df.mm.trans1:probe6	0.0451576513304535	0.0888493416430705	0.508249701071087	0.611445782946368	   
df.mm.trans2:probe2	-0.0313650518456092	0.0888493416430705	-0.353013891443453	0.724189225241232	   
df.mm.trans2:probe3	-0.00915071716061041	0.0888493416430705	-0.102991389597135	0.918000668707239	   
df.mm.trans2:probe4	0.150940260611495	0.0888493416430705	1.69883375408519	0.0898154456342425	.  
df.mm.trans2:probe5	0.105131990394640	0.0888493416430705	1.18326133261607	0.237125894123913	   
df.mm.trans2:probe6	0.0501821542810239	0.0888493416430705	0.564800519092396	0.572398782804667	   
df.mm.trans3:probe2	-0.010798175976663	0.0888493416430705	-0.121533550806059	0.903304936537588	   
df.mm.trans3:probe3	-0.0860543751852055	0.0888493416430705	-0.96854263176093	0.333123451409911	   
df.mm.trans3:probe4	0.00520958982844549	0.0888493416430705	0.0586339722062735	0.953261160490864	   
df.mm.trans3:probe5	-0.0876475567793584	0.0888493416430705	-0.986473902434304	0.324257248891598	   
df.mm.trans3:probe6	-0.00949450622865663	0.0888493416430705	-0.106860738111019	0.91493149748375	   
df.mm.trans3:probe7	-0.113604088661244	0.0888493416430705	-1.27861486152164	0.201476091635964	   
df.mm.trans3:probe8	-0.0137185025027227	0.0888493416430705	-0.154401847543601	0.877339464086041	   
df.mm.trans3:probe9	-0.0398809792067037	0.0888493416430705	-0.448860717133002	0.653677491904119	   
df.mm.trans3:probe10	0.077737997084548	0.0888493416430705	0.874941734479481	0.381919608419306	   
df.mm.trans3:probe11	-0.0128436829595786	0.0888493416430705	-0.144555747088986	0.885105175082898	   
df.mm.trans3:probe12	0.0377874003683357	0.0888493416430705	0.425297471759971	0.670756603023385	   
df.mm.trans3:probe13	-0.0113155179545811	0.0888493416430705	-0.127356238609379	0.898696720574969	   
df.mm.trans3:probe14	-0.083632788863972	0.0888493416430705	-0.94128765973242	0.346897223406700	   
df.mm.trans3:probe15	0.00722487080546632	0.0888493416430705	0.0813159745683923	0.93521499080657	   
df.mm.trans3:probe16	0.0305263357798144	0.0888493416430705	0.343574135894514	0.731274525542418	   
df.mm.trans3:probe17	-0.093483301127693	0.0888493416430705	-1.05215524841184	0.293108209433952	   
df.mm.trans3:probe18	-0.0226860497453104	0.0888493416430705	-0.255331658353145	0.798545427784165