chr11.4653_chr11_69416183_69422208_-_2.R 

fitVsDatCorrelation=0.888771908892766
cont.fitVsDatCorrelation=0.269743061279401

fstatistic=7030.75988234425,53,715
cont.fstatistic=1582.52545582914,53,715

residuals=-0.857422852685931,-0.0960592707630427,-0.000997788421912175,0.0888702594969048,2.84230868852627
cont.residuals=-0.751146356887976,-0.292259935051533,-0.0534742939325213,0.232694839112729,2.3843494623515

predictedValues:
Include	Exclude	Both
chr11.4653_chr11_69416183_69422208_-_2.R.tl.Lung	67.9966558836973	44.7717312563289	95.0148451482004
chr11.4653_chr11_69416183_69422208_-_2.R.tl.cerebhem	62.2363155727044	43.3993531207572	86.5712416847697
chr11.4653_chr11_69416183_69422208_-_2.R.tl.cortex	92.4430501216685	45.3459069539925	145.301953992590
chr11.4653_chr11_69416183_69422208_-_2.R.tl.heart	71.8815604165185	49.6774135625517	105.95705965742
chr11.4653_chr11_69416183_69422208_-_2.R.tl.kidney	75.9689576257084	44.1346818184851	110.622459125885
chr11.4653_chr11_69416183_69422208_-_2.R.tl.liver	58.2139383135334	47.4829055801066	73.1677075791378
chr11.4653_chr11_69416183_69422208_-_2.R.tl.stomach	64.6590258520605	44.8194040148128	100.414661639293
chr11.4653_chr11_69416183_69422208_-_2.R.tl.testicle	65.0026230205145	44.3274856639600	96.6789793661802


diffExp=23.2249246273684,18.8369624519472,47.0971431676760,22.2041468539669,31.8342758072233,10.7310327334267,19.8396218372477,20.6751373565544
diffExpScore=0.994883425104602
diffExp1.5=1,0,1,0,1,0,0,0
diffExp1.5Score=0.75
diffExp1.4=1,1,1,1,1,0,1,1
diffExp1.4Score=0.875
diffExp1.3=1,1,1,1,1,0,1,1
diffExp1.3Score=0.875
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	64.2161338171206	72.5623423866299	79.0884774728108
cerebhem	71.3846523469831	81.9218721962576	66.5833026863079
cortex	68.921718119366	76.2219195738872	65.9325623409883
heart	67.8734406193174	72.4949594452218	57.571497094306
kidney	68.6335502336444	64.1440967614835	64.5734397274877
liver	77.692498337931	70.4748137866454	59.7300707648564
stomach	66.3819408863803	77.7747912739514	60.3977651096341
testicle	66.166308888764	68.118656817791	69.8059252768742
cont.diffExp=-8.3462085695093,-10.5372198492745,-7.30020145452124,-4.62151882590443,4.48945347216085,7.21768455128559,-11.3928503875711,-1.952347929027
cont.diffExpScore=1.67021905858414

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=0.000875126338223952
cont.tran.correlation=0.0384716988002217

tran.covariance=1.23392704695822e-05
cont.tran.covariance=0.000186780443995576

tran.mean=57.6475630485875
cont.tran.mean=70.9364809682109

weightedLogRatios:
wLogRatio
Lung	1.67592150428518
cerebhem	1.42420119386539
cortex	2.97050288246914
heart	1.51123515508781
kidney	2.20424066821329
liver	0.807327903551136
stomach	1.46077297888415
testicle	1.52478902379457

cont.weightedLogRatios:
wLogRatio
Lung	-0.516057940060711
cerebhem	-0.597121298156737
cortex	-0.431233988438005
heart	-0.279995247597681
kidney	0.283786397932133
liver	0.419654940097204
stomach	-0.677067144405645
testicle	-0.122330042650209

varWeightedLogRatios=0.409349986128651
cont.varWeightedLogRatios=0.165183483953652

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.16671839636941	0.0984837912279876	32.154716597359	5.15226708088142e-141	***
df.mm.trans1	0.780516506257649	0.087455512595429	8.92472621901302	3.71738091201592e-18	***
df.mm.trans2	0.61002976375141	0.079552161459207	7.66829904507651	5.70494001821532e-14	***
df.mm.exp2	-0.0265867844803235	0.107248135328677	-0.247899736427534	0.804283158790915	   
df.mm.exp3	-0.104903643220698	0.107248135328677	-0.978139553654766	0.328336137514303	   
df.mm.exp4	0.0505339069802898	0.107248135328677	0.471186812017026	0.637651063897219	   
df.mm.exp5	-0.0555547441798555	0.107248135328677	-0.518001958818214	0.604617143934956	   
df.mm.exp6	0.164738086200415	0.107248135328677	1.5360461577775	0.124969435653690	   
df.mm.exp7	-0.104541674583020	0.107248135328677	-0.974764496022583	0.330006755095550	   
df.mm.exp8	-0.0723657703648145	0.107248135328677	-0.674750848982498	0.500052189584684	   
df.mm.trans1:exp2	-0.0619330602843061	0.101837136067745	-0.608157914447896	0.54327587327819	   
df.mm.trans2:exp2	-0.00454562109086537	0.0857545428445983	-0.0530073502823378	0.957740857427439	   
df.mm.trans1:exp3	0.412037897987553	0.101837136067745	4.04604758045685	5.77631167570257e-05	***
df.mm.trans2:exp3	0.117646619596124	0.0857545428445984	1.37189955999555	0.170524996989117	   
df.mm.trans1:exp4	0.00502733754624384	0.101837136067745	0.0493664466653847	0.960641053840897	   
df.mm.trans2:exp4	0.0534395258294572	0.0857545428445983	0.623168453317961	0.533372550183328	   
df.mm.trans1:exp5	0.166421022947620	0.101837136067745	1.63418797281291	0.102659576254476	   
df.mm.trans2:exp5	0.0412237118325876	0.0857545428445984	0.480717527784993	0.630864327289702	   
df.mm.trans1:exp6	-0.320071795998802	0.101837136067745	-3.14297719238571	0.00174147951733169	** 
df.mm.trans2:exp6	-0.105945263971936	0.0857545428445984	-1.23544783118869	0.217069657421139	   
df.mm.trans1:exp7	0.0542108552843618	0.101837136067745	0.53232894578162	0.594663565292099	   
df.mm.trans2:exp7	0.105605904048112	0.0857545428445984	1.23149049070774	0.218544356365372	   
df.mm.trans1:exp8	0.0273348678221093	0.101837136067745	0.268417483813817	0.788455406674521	   
df.mm.trans2:exp8	0.0623937573871032	0.0857545428445983	0.727585446991084	0.467105569713567	   
df.mm.trans1:probe2	0.127347622167015	0.0557784966160267	2.28309527672756	0.0227173839606466	*  
df.mm.trans1:probe3	-0.0891143644882315	0.0557784966160267	-1.59764729949044	0.110563308884657	   
df.mm.trans1:probe4	-0.0204061395663480	0.0557784966160267	-0.365842408891399	0.714590883761998	   
df.mm.trans1:probe5	0.251596268242847	0.0557784966160267	4.51063193715689	7.55339559864729e-06	***
df.mm.trans1:probe6	0.000527318570093471	0.0557784966160267	0.00945379675116519	0.992459710970292	   
df.mm.trans1:probe7	0.34031816692074	0.0557784966160267	6.10124308769837	1.72384039238649e-09	***
df.mm.trans1:probe8	0.31161617927482	0.0557784966160267	5.58667225149421	3.29146826238495e-08	***
df.mm.trans1:probe9	-0.139681200923163	0.0557784966160267	-2.50421236493184	0.0124940434755692	*  
df.mm.trans1:probe10	0.183165873503499	0.0557784966160267	3.2838080015744	0.00107401375600326	** 
df.mm.trans1:probe11	0.428353951228381	0.0557784966160267	7.67955354152201	5.2605168195401e-14	***
df.mm.trans1:probe12	0.242772395338956	0.0557784966160267	4.35243705132779	1.54266821188320e-05	***
df.mm.trans1:probe13	0.541318488044824	0.0557784966160267	9.70478806144962	5.30766355746176e-21	***
df.mm.trans1:probe14	0.31578181794378	0.0557784966160267	5.66135405401098	2.17521782627410e-08	***
df.mm.trans1:probe15	0.440256849216709	0.0557784966160267	7.89294936088707	1.10975404661604e-14	***
df.mm.trans1:probe16	0.393488539467477	0.0557784966160267	7.05448449384019	4.09849702426107e-12	***
df.mm.trans1:probe17	0.951488792723815	0.0557784966160267	17.0583441729124	5.37205620316692e-55	***
df.mm.trans1:probe18	0.273926563840523	0.0557784966160267	4.91097072275369	1.12391763592755e-06	***
df.mm.trans1:probe19	0.80144741965941	0.0557784966160267	14.3683940636925	2.58829940057419e-41	***
df.mm.trans1:probe20	0.717027579434101	0.0557784966160267	12.8549104571614	3.57490473953045e-34	***
df.mm.trans1:probe21	0.602071172923954	0.0557784966160267	10.7939655862106	2.88131802776887e-25	***
df.mm.trans1:probe22	0.404510908606597	0.0557784966160267	7.25209414285952	1.06896006110209e-12	***
df.mm.trans2:probe2	0.0300360668433944	0.0557784966160267	0.538488282503552	0.59040758944614	   
df.mm.trans2:probe3	0.104171710829369	0.0557784966160267	1.86759624495577	0.0622272841166416	.  
df.mm.trans2:probe4	0.0247364554921735	0.0557784966160267	0.44347655445891	0.657555234062591	   
df.mm.trans2:probe5	0.0705898297831236	0.0557784966160267	1.26553840755258	0.206090625057301	   
df.mm.trans2:probe6	0.0187537509916303	0.0557784966160267	0.336218294313831	0.736804903733183	   
df.mm.trans3:probe2	-0.270308429756818	0.0557784966160267	-4.84610461299438	1.5449812119882e-06	***
df.mm.trans3:probe3	0.468396983412644	0.0557784966160267	8.39744725708618	2.44562701181026e-16	***
df.mm.trans3:probe4	-0.211014642728179	0.0557784966160267	-3.78308229030950	0.000167860264821417	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.10292645676745	0.206901447763292	19.8303419387449	4.52899630927557e-70	***
df.mm.trans1	-0.0232513247600452	0.183732489836692	-0.126549881192553	0.899332244892261	   
df.mm.trans2	0.217871140729937	0.167128592160977	1.30361380965913	0.192784865489738	   
df.mm.exp2	0.399261694150819	0.225314178025985	1.77202206114510	0.0768167142713212	.  
df.mm.exp3	0.301854605115233	0.225314178025985	1.33970532950847	0.180766803678748	   
df.mm.exp4	0.372000856868647	0.225314178025985	1.65103172879669	0.0991712175989214	.  
df.mm.exp5	0.145976995269832	0.225314178025985	0.647881977728881	0.517269269874201	   
df.mm.exp6	0.44204513121537	0.225314178025985	1.96190552715413	0.0501610356754875	.  
df.mm.exp7	0.372156922935101	0.225314178025985	1.65172438856547	0.0990298217358498	.  
df.mm.exp8	0.0915702681633477	0.225314178025985	0.406411478254986	0.684561899195635	   
df.mm.trans1:exp2	-0.293433285721089	0.213946382706842	-1.37152721167136	0.170640906711287	   
df.mm.trans2:exp2	-0.277941766513284	0.180158976879278	-1.54275835335993	0.123331866672862	   
df.mm.trans1:exp3	-0.231137749268752	0.213946382706842	-1.08035362105405	0.280349012826809	   
df.mm.trans2:exp3	-0.252651612689165	0.180158976879278	-1.40238148032148	0.161235377216738	   
df.mm.trans1:exp4	-0.316610537866082	0.213946382706842	-1.47985927062817	0.139351267460980	   
df.mm.trans2:exp4	-0.372929909669214	0.180158976879278	-2.07000459332709	0.0388104407336931	*  
df.mm.trans1:exp5	-0.079449994319272	0.213946382706842	-0.371354697911101	0.710483374299174	   
df.mm.trans2:exp5	-0.26929101821751	0.180158976879278	-1.49474104972276	0.135423230606235	   
df.mm.trans1:exp6	-0.251540909676645	0.213946382706842	-1.17571938583003	0.240098363424908	   
df.mm.trans2:exp6	-0.471235823830574	0.180158976879278	-2.61566662951434	0.00909320061419228	** 
df.mm.trans1:exp7	-0.338986362733806	0.213946382706842	-1.58444540377343	0.113534564178386	   
df.mm.trans2:exp7	-0.30278565122221	0.180158976879278	-1.68065814130984	0.0932661009152442	.  
df.mm.trans1:exp8	-0.0616533486281302	0.213946382706842	-0.28817196088148	0.773298624510659	   
df.mm.trans2:exp8	-0.154765217797277	0.180158976879278	-0.859048050106231	0.390601912295502	   
df.mm.trans1:probe2	0.209081360892782	0.117183259905171	1.78422550338657	0.0748109859962978	.  
df.mm.trans1:probe3	0.135735425839197	0.117183259905171	1.15831754423831	0.247121218397231	   
df.mm.trans1:probe4	0.215751835545790	0.117183259905171	1.84114894670438	0.0660138415301848	.  
df.mm.trans1:probe5	0.147026523885760	0.117183259905171	1.25467173387000	0.210007919666888	   
df.mm.trans1:probe6	0.089224729354018	0.117183259905171	0.761411906668429	0.446662132357044	   
df.mm.trans1:probe7	0.0359577495043559	0.117183259905171	0.306850564948052	0.75904645977549	   
df.mm.trans1:probe8	0.0396977988235682	0.117183259905171	0.338766807270025	0.734884869392387	   
df.mm.trans1:probe9	0.129297055110682	0.117183259905171	1.10337479274185	0.270235653178722	   
df.mm.trans1:probe10	-0.00412494880139116	0.117183259905171	-0.0352008367468974	0.971929419725933	   
df.mm.trans1:probe11	0.103350271959892	0.117183259905171	0.881954231718141	0.378097951586959	   
df.mm.trans1:probe12	0.0681711774709441	0.117183259905171	0.581748429990009	0.560919508998888	   
df.mm.trans1:probe13	-0.056457348279136	0.117183259905171	-0.481786804060781	0.630104834161177	   
df.mm.trans1:probe14	0.147975673490359	0.117183259905171	1.26277143689386	0.207082998084591	   
df.mm.trans1:probe15	-0.116525011335941	0.117183259905171	-0.994382742298157	0.320372963750963	   
df.mm.trans1:probe16	0.129051239969820	0.117183259905171	1.10127709430727	0.271146669215944	   
df.mm.trans1:probe17	0.140597522863231	0.117183259905171	1.199808940091	0.230610960909276	   
df.mm.trans1:probe18	0.167857861064489	0.117183259905171	1.43243890979246	0.152455286349009	   
df.mm.trans1:probe19	0.231277333700157	0.117183259905171	1.97363799135914	0.0488075336124895	*  
df.mm.trans1:probe20	0.108241970141033	0.117183259905171	0.923698233251295	0.355955063587083	   
df.mm.trans1:probe21	0.116213683172567	0.117183259905171	0.99172597917665	0.321666706795502	   
df.mm.trans1:probe22	0.109661265286503	0.117183259905171	0.935809990055281	0.349686981772696	   
df.mm.trans2:probe2	-0.0924397769256467	0.117183259905171	-0.788847971975287	0.430462348652371	   
df.mm.trans2:probe3	-0.023905817413376	0.117183259905171	-0.204003689884729	0.838408665784435	   
df.mm.trans2:probe4	-0.156447358490006	0.117183259905171	-1.33506576465452	0.182279733015388	   
df.mm.trans2:probe5	0.102064185874321	0.117183259905171	0.870979233355647	0.384057829324310	   
df.mm.trans2:probe6	-0.192786334511816	0.117183259905171	-1.64516958026110	0.100374360315389	   
df.mm.trans3:probe2	0.101657543744313	0.117183259905171	0.867509094955867	0.385954181286557	   
df.mm.trans3:probe3	0.0306483294366194	0.117183259905171	0.261541874337865	0.793749983014852	   
df.mm.trans3:probe4	0.159777810993646	0.117183259905171	1.36348665434760	0.173158332242576