chrX.25737_chrX_17889634_17897566_+_2.R 

fitVsDatCorrelation=0.904949769872323
cont.fitVsDatCorrelation=0.297256175476314

fstatistic=8985.0203168043,52,692
cont.fstatistic=1773.90292885798,52,692

residuals=-0.668841231883889,-0.0867763706989358,-0.000287716211128017,0.083701458191532,1.08327739360381
cont.residuals=-0.710296657102195,-0.261825546934918,-0.0856545858952,0.220800971834018,1.83699642306157

predictedValues:
Include	Exclude	Both
chrX.25737_chrX_17889634_17897566_+_2.R.tl.Lung	57.638317217075	64.9010512424156	80.0210119290034
chrX.25737_chrX_17889634_17897566_+_2.R.tl.cerebhem	62.7562358203755	75.1085435833498	76.3810516838398
chrX.25737_chrX_17889634_17897566_+_2.R.tl.cortex	54.8121946163628	99.336970471931	111.080510418772
chrX.25737_chrX_17889634_17897566_+_2.R.tl.heart	52.6636332844467	63.2547460383127	65.3629391455412
chrX.25737_chrX_17889634_17897566_+_2.R.tl.kidney	58.7181090320876	61.0097103692425	80.6935283491815
chrX.25737_chrX_17889634_17897566_+_2.R.tl.liver	56.2255191428375	59.2185175056338	76.1852398264712
chrX.25737_chrX_17889634_17897566_+_2.R.tl.stomach	55.7653950924447	62.5953406248289	67.3461706408499
chrX.25737_chrX_17889634_17897566_+_2.R.tl.testicle	53.7314941853466	65.3461793210033	79.2145101738904


diffExp=-7.2627340253406,-12.3523077629743,-44.5247758555682,-10.5911127538661,-2.29160133715494,-2.99299836279636,-6.82994553238414,-11.6146851356567
diffExpScore=0.989945723068402
diffExp1.5=0,0,-1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,-1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,-1,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,0,-1,-1,0,0,0,-1
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	65.2364842031307	63.4636033922979	66.578786661123
cerebhem	59.840369215042	55.1321169998852	59.5157289396556
cortex	64.8186167123967	69.160666834867	81.1500247064438
heart	58.1551594808722	73.7880314595064	55.8958710462328
kidney	62.560272280271	61.4063646972966	60.315380368601
liver	65.950370633466	51.4528785270652	80.5070822202392
stomach	64.4101830613387	50.464079099315	70.4733009522096
testicle	55.736823108262	60.0269945302068	66.4153655504646
cont.diffExp=1.77288081083279,4.70825221515677,-4.34205012247031,-15.6328719786342,1.15390758297435,14.4974921064008,13.9461039620237,-4.29017142194473
cont.diffExpScore=4.70937112971777

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,-1,0,1,1,0
cont.diffExp1.2Score=1.5

tran.correlation=0.0143069573551758
cont.tran.correlation=-0.287102048025884

tran.covariance=0.000382353238846883
cont.tran.covariance=-0.0024284460084442

tran.mean=62.6926223467309
cont.tran.mean=61.3501883897012

weightedLogRatios:
wLogRatio
Lung	-0.488177785532435
cerebhem	-0.759868625974205
cortex	-2.55752458727816
heart	-0.743158887169541
kidney	-0.156657447775983
liver	-0.210322415187513
stomach	-0.471267766015926
testicle	-0.798816489538292

cont.weightedLogRatios:
wLogRatio
Lung	0.114734545866966
cerebhem	0.331947583970741
cortex	-0.272585845152999
heart	-0.995695716210957
kidney	0.0768288761710651
liver	1.00902620075442
stomach	0.98659737852365
testicle	-0.300893337428218

varWeightedLogRatios=0.579272465348039
cont.varWeightedLogRatios=0.452030146981906

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.74089841616291	0.0881542569562556	42.4358226741023	9.44091999241686e-195	***
df.mm.trans1	0.069125999388992	0.0791754143389076	0.873074046611245	0.382925571102312	   
df.mm.trans2	0.371923553515947	0.0728125464919554	5.10795970522798	4.21574401337697e-07	***
df.mm.exp2	0.277695464799573	0.0997351566147675	2.78432875853584	0.00551040998456087	** 
df.mm.exp3	0.0474131057095816	0.0997351566147675	0.47539009631997	0.634658970224169	   
df.mm.exp4	0.0863777415422622	0.0997351566147675	0.866071147568364	0.386751316032159	   
df.mm.exp5	-0.0516393077373368	0.0997351566147675	-0.517764341984206	0.604788178376495	   
df.mm.exp6	-0.067324869226398	0.0997351566147675	-0.675036481733758	0.499878063520278	   
df.mm.exp7	0.103236169998111	0.0997351566147675	1.03510310207729	0.30098234810016	   
df.mm.exp8	-0.0532233524687128	0.0997351566147675	-0.533646853078007	0.593757248900802	   
df.mm.trans1:exp2	-0.19262509209951	0.0954891425393022	-2.01724601328604	0.0440554745162565	*  
df.mm.trans2:exp2	-0.131624971197910	0.0831126305123063	-1.58369396307846	0.113720256934186	   
df.mm.trans1:exp3	-0.097687983013869	0.0954891425393023	-1.02302712555683	0.306652514542738	   
df.mm.trans2:exp3	0.378240885487706	0.0831126305123063	4.55094349867438	6.30766029302271e-06	***
df.mm.trans1:exp4	-0.176640170704960	0.0954891425393022	-1.84984560555937	0.0647619581565966	.  
df.mm.trans2:exp4	-0.112071402029764	0.0831126305123063	-1.34842804684385	0.177961905150275	   
df.mm.trans1:exp5	0.0701999123951278	0.0954891425393023	0.735161197685216	0.462490398851631	   
df.mm.trans2:exp5	-0.0101914758360505	0.0831126305123063	-0.122622467526659	0.902441664744569	   
df.mm.trans1:exp6	0.0425080243409299	0.0954891425393023	0.445160813161916	0.656342758023398	   
df.mm.trans2:exp6	-0.0243046635496606	0.0831126305123063	-0.292430445286675	0.770045188589071	   
df.mm.trans1:exp7	-0.136270228620893	0.0954891425393022	-1.42707563391100	0.154009145405791	   
df.mm.trans2:exp7	-0.139409147034368	0.0831126305123063	-1.67735212055075	0.0939252294532816	.  
df.mm.trans1:exp8	-0.016964910030403	0.0954891425393023	-0.177663235623049	0.85903945118978	   
df.mm.trans2:exp8	0.0600585045048354	0.0831126305123063	0.72261585434891	0.470160062897207	   
df.mm.trans1:probe2	0.0548441198593705	0.0477445712696511	1.14869855149861	0.251077202741598	   
df.mm.trans1:probe3	0.0666265246305914	0.0477445712696511	1.39547854046692	0.163319206642972	   
df.mm.trans1:probe4	0.0979505304246054	0.0477445712696511	2.05155325139275	0.0405889656712884	*  
df.mm.trans1:probe5	0.229873956986054	0.0477445712696511	4.81466166462728	1.81198966708968e-06	***
df.mm.trans1:probe6	0.0669734923914907	0.0477445712696511	1.40274570721850	0.161141161038836	   
df.mm.trans1:probe7	-0.0404989989322093	0.0477445712696511	-0.84824301182808	0.396595953905219	   
df.mm.trans1:probe8	0.187220510899521	0.0477445712696511	3.92129421043787	9.68450577881042e-05	***
df.mm.trans1:probe9	0.078892450705162	0.0477445712696511	1.65238578140317	0.0989095491462437	.  
df.mm.trans1:probe10	0.101849435393938	0.0477445712696511	2.13321499566337	0.033258267613254	*  
df.mm.trans1:probe11	0.197845488833406	0.0477445712696511	4.14383213781556	3.83867594229679e-05	***
df.mm.trans1:probe12	0.0636984668688763	0.0477445712696511	1.33415098669796	0.182593255706339	   
df.mm.trans1:probe13	0.00705395031301142	0.0477445712696511	0.147743505186636	0.882588233054086	   
df.mm.trans1:probe14	0.142872859579409	0.0477445712696511	2.99244198408429	0.00286603879971616	** 
df.mm.trans1:probe15	0.0568661374030692	0.0477445712696511	1.19104928352799	0.234042608067662	   
df.mm.trans1:probe16	-0.0199674007386505	0.0477445712696511	-0.418213007419816	0.675921135056049	   
df.mm.trans1:probe17	0.642667178107163	0.0477445712696511	13.4605288311736	7.49306866989288e-37	***
df.mm.trans1:probe18	0.719457340431938	0.0477445712696511	15.0688826247616	1.38462896589964e-44	***
df.mm.trans1:probe19	0.970315335896149	0.0477445712696511	20.3230505603666	2.31290579103593e-72	***
df.mm.trans1:probe20	0.772821481868971	0.0477445712696511	16.1865833395852	3.25702273266470e-50	***
df.mm.trans1:probe21	0.718045643247054	0.0477445712696511	15.0393149242389	1.93905270412959e-44	***
df.mm.trans1:probe22	0.988670506981368	0.0477445712696511	20.7074957569012	1.69546925258557e-74	***
df.mm.trans2:probe2	-0.0338900229984676	0.0477445712696511	-0.709819401394642	0.478055245291146	   
df.mm.trans2:probe3	0.0563282792713866	0.0477445712696511	1.17978395812283	0.238491570132119	   
df.mm.trans2:probe4	0.0196726604755209	0.0477445712696511	0.41203973462059	0.68043790204822	   
df.mm.trans2:probe5	0.282748627161329	0.0477445712696511	5.92211050685586	5.00626563086163e-09	***
df.mm.trans2:probe6	0.215517122110742	0.0477445712696511	4.51396077877729	7.4769914080172e-06	***
df.mm.trans3:probe2	-0.116408983451226	0.0477445712696511	-2.43816166645990	0.0150127450966604	*  
df.mm.trans3:probe3	0.71743282414823	0.0477445712696511	15.0264795571485	2.24406270844926e-44	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.11001773920078	0.197804574419275	20.7781733626090	6.85155875778966e-75	***
df.mm.trans1	0.153522118795018	0.177657434575722	0.86414688561532	0.387806636800939	   
df.mm.trans2	-0.0670520190355384	0.163380139184565	-0.410404957237747	0.681635945981831	   
df.mm.exp2	-0.114927138388934	0.223790329474541	-0.51354827824233	0.607731773000232	   
df.mm.exp3	-0.118373883226454	0.223790329474541	-0.528949948393193	0.597009789121028	   
df.mm.exp4	0.210721186483572	0.223790329474541	0.94160094843394	0.346725568978253	   
df.mm.exp5	0.0239573579767105	0.223790329474541	0.107052695408967	0.914778202936363	   
df.mm.exp6	-0.388875695156489	0.223790329474541	-1.73767872843106	0.0827123161457179	.  
df.mm.exp7	-0.298799851828312	0.223790329474541	-1.33517767514750	0.182257247446639	   
df.mm.exp8	-0.210592487659880	0.223790329474541	-0.941025861816058	0.347019979806061	   
df.mm.trans1:exp2	0.028588755976297	0.214262927892648	0.133428382863417	0.89389339166177	   
df.mm.trans2:exp2	-0.0258069962503714	0.186491941228785	-0.138381294549945	0.889979337488638	   
df.mm.trans1:exp3	0.111947854170495	0.214262927892648	0.522478878038032	0.60150416924252	   
df.mm.trans2:exp3	0.204339619263771	0.186491941228785	1.09570214089354	0.27359033076287	   
df.mm.trans1:exp4	-0.325625470452083	0.214262927892648	-1.51974713336892	0.129031288698850	   
df.mm.trans2:exp4	-0.0599912100210911	0.186491941228785	-0.321682586527935	0.747790313903299	   
df.mm.trans1:exp5	-0.0658457955402959	0.214262927892648	-0.307313057783316	0.7586975578963	   
df.mm.trans2:exp5	-0.0569104352774648	0.186491941228785	-0.305162973276407	0.760333794592084	   
df.mm.trans1:exp6	0.399759308122818	0.214262927892648	1.86574183436487	0.062500391247868	.  
df.mm.trans2:exp6	0.179075537272768	0.186491941228785	0.960232040552797	0.337273827998358	   
df.mm.trans1:exp7	0.286052708411828	0.214262927892648	1.33505460429043	0.182297501058358	   
df.mm.trans2:exp7	0.069595063401503	0.186491941228785	0.373180004148947	0.709128762015527	   
df.mm.trans1:exp8	0.0532146271636708	0.214262927892648	0.248361336639313	0.803928529958375	   
df.mm.trans2:exp8	0.154920290893465	0.186491941228785	0.830707696390013	0.406425290299564	   
df.mm.trans1:probe2	-0.158181805619742	0.107131463946324	-1.47652052714407	0.140259111061958	   
df.mm.trans1:probe3	-0.127041714910426	0.107131463946324	-1.18584877150636	0.236089043815236	   
df.mm.trans1:probe4	-0.0682042914680471	0.107131463946324	-0.636641085220486	0.52456918879627	   
df.mm.trans1:probe5	-0.0752237115850514	0.107131463946324	-0.7021626403121	0.482813844094187	   
df.mm.trans1:probe6	-0.0478196832890279	0.107131463946324	-0.44636450887096	0.655473606285032	   
df.mm.trans1:probe7	-0.106917900504154	0.107131463946324	-0.998006529227705	0.318625037564100	   
df.mm.trans1:probe8	-0.172032085572455	0.107131463946324	-1.60580355420746	0.108773287063826	   
df.mm.trans1:probe9	-0.108031438503054	0.107131463946324	-1.00840065582582	0.313614623760580	   
df.mm.trans1:probe10	0.0769985253909318	0.107131463946324	0.718729330810884	0.472550317583997	   
df.mm.trans1:probe11	-0.0594501671349238	0.107131463946324	-0.554927235613153	0.579123751500583	   
df.mm.trans1:probe12	-0.103365446409268	0.107131463946324	-0.964846764915463	0.334958620642571	   
df.mm.trans1:probe13	-0.0871542882879784	0.107131463946324	-0.813526531585951	0.416196064132573	   
df.mm.trans1:probe14	-0.184809969977363	0.107131463946324	-1.72507649172010	0.0849601711679913	.  
df.mm.trans1:probe15	-0.112297244512072	0.107131463946324	-1.04821907939517	0.294903642768105	   
df.mm.trans1:probe16	-0.139101619888958	0.107131463946324	-1.29841985505445	0.194575639390776	   
df.mm.trans1:probe17	-0.0423137678964631	0.107131463946324	-0.394970500147963	0.692986370912843	   
df.mm.trans1:probe18	-0.144591475052865	0.107131463946324	-1.34966395236892	0.177565147632345	   
df.mm.trans1:probe19	-0.214174709860106	0.107131463946324	-1.99917654413286	0.0459798538024587	*  
df.mm.trans1:probe20	-0.149184953197521	0.107131463946324	-1.39254097444488	0.164205911633584	   
df.mm.trans1:probe21	-0.0951114697554897	0.107131463946324	-0.88780145675171	0.374956024661758	   
df.mm.trans1:probe22	-0.0200150794286153	0.107131463946324	-0.186827274559072	0.851850820288335	   
df.mm.trans2:probe2	0.263513445839017	0.107131463946324	2.45972038589004	0.0141480063770431	*  
df.mm.trans2:probe3	0.160433519574415	0.107131463946324	1.49753875905959	0.134709105640635	   
df.mm.trans2:probe4	0.105452440937457	0.107131463946324	0.984327452019997	0.325298559369893	   
df.mm.trans2:probe5	0.187427139550822	0.107131463946324	1.74950600548806	0.0806468664618566	.  
df.mm.trans2:probe6	0.250681072431059	0.107131463946324	2.33993883026426	0.0195702357498082	*  
df.mm.trans3:probe2	0.0319855163291477	0.107131463946324	0.298563233908325	0.765362951621009	   
df.mm.trans3:probe3	-0.0262910085896370	0.107131463946324	-0.245408842754259	0.806212644435823