chr5.18459_chr5_42770796_42773935_+_2.R 

fitVsDatCorrelation=0.862254278775626
cont.fitVsDatCorrelation=0.279451246341714

fstatistic=9517.23765253056,53,715
cont.fstatistic=2638.40288215329,53,715

residuals=-0.636626589404771,-0.0865383003630842,-0.00380209009625759,0.0839802429267112,0.80521537305695
cont.residuals=-0.740670148945742,-0.221437511059874,-0.045521931783324,0.176491188448756,0.884319790275623

predictedValues:
Include	Exclude	Both
chr5.18459_chr5_42770796_42773935_+_2.R.tl.Lung	67.500026577265	70.2317024950023	72.2196403539186
chr5.18459_chr5_42770796_42773935_+_2.R.tl.cerebhem	62.8450419470634	73.008314860129	58.6600884920895
chr5.18459_chr5_42770796_42773935_+_2.R.tl.cortex	60.0408344323884	67.0498792950736	56.8059352352084
chr5.18459_chr5_42770796_42773935_+_2.R.tl.heart	61.5621775550654	67.8751821602612	61.1844052923436
chr5.18459_chr5_42770796_42773935_+_2.R.tl.kidney	68.2614777418422	68.6957370568556	66.2400817327783
chr5.18459_chr5_42770796_42773935_+_2.R.tl.liver	67.0781216929067	72.7127492431307	58.9529092257976
chr5.18459_chr5_42770796_42773935_+_2.R.tl.stomach	62.5986868768864	77.1962721536468	60.9327654774627
chr5.18459_chr5_42770796_42773935_+_2.R.tl.testicle	61.3539166767907	67.457687447223	57.9645001298841


diffExp=-2.73167591773725,-10.1632729130657,-7.00904486268517,-6.31300460519584,-0.434259315013364,-5.63462755022404,-14.5975852767604,-6.1037707704323
diffExpScore=0.98147710500543
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=0,0,0,0,0,0,-1,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	66.2471056016953	61.2414449545926	70.5246947704307
cerebhem	76.2192245479546	72.2640638764823	61.5292289239912
cortex	73.3710929040558	68.3813774469285	74.1793462195727
heart	66.977371266153	72.875549949127	61.1953248919705
kidney	68.7243397644557	70.9112276664753	57.9466158246242
liver	66.3656381449044	59.1570152514357	73.3717815748212
stomach	68.4113310081198	70.3294437276476	63.1275733596781
testicle	63.4077977752976	63.2000563477756	73.622346852428
cont.diffExp=5.00566064710267,3.95516067147229,4.98971545712726,-5.89817868297395,-2.18688790201956,7.2086228934687,-1.91811271952778,0.207741427522016
cont.diffExpScore=2.53726838313985

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=0.177233973772553
cont.tran.correlation=0.56459366699886

tran.covariance=0.000494056007805203
cont.tran.covariance=0.00273541772356692

tran.mean=67.2167380132206
cont.tran.mean=68.0052550145688

weightedLogRatios:
wLogRatio
Lung	-0.167889710012333
cerebhem	-0.631927287986881
cortex	-0.458234894675765
heart	-0.406975615238737
kidney	-0.0268026807768669
liver	-0.342492381309494
stomach	-0.889057528574598
testicle	-0.394927730902917

cont.weightedLogRatios:
wLogRatio
Lung	0.326378332497831
cerebhem	0.229504485280283
cortex	0.300051876560302
heart	-0.358402240718775
kidney	-0.13300012239174
liver	0.475768831257337
stomach	-0.117227212124693
testicle	0.0136121255156049

varWeightedLogRatios=0.070163168919225
cont.varWeightedLogRatios=0.0811160921777823

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.79324748212768	0.0818357470935466	46.3519625206282	1.28896139851569e-217	***
df.mm.trans1	0.112014640378204	0.0719973815367859	1.55581547533047	0.120194474428158	   
df.mm.trans2	0.429903784038429	0.0650976677905986	6.60398135031983	7.81029913034614e-11	***
df.mm.exp2	0.175270042363345	0.0867415175649948	2.02060152143426	0.0436933392879665	*  
df.mm.exp3	0.0766051330377565	0.0867415175649948	0.883142642510915	0.377456038494947	   
df.mm.exp4	0.0396100344529961	0.0867415175649948	0.456644471585555	0.648065296159348	   
df.mm.exp5	0.0755312265015323	0.0867415175649948	0.870762105873203	0.384176316731684	   
df.mm.exp6	0.231419928853029	0.0867415175649948	2.66792575630958	0.00780497727420063	** 
df.mm.exp7	0.189108650937332	0.0867415175649948	2.18013998654836	0.0295725118194692	*  
df.mm.exp8	0.0841130356612201	0.0867415175649948	0.969697533804326	0.332525184356820	   
df.mm.trans1:exp2	-0.246725989133846	0.0816042452235408	-3.02344551386981	0.00258853080758192	** 
df.mm.trans2:exp2	-0.136496517090728	0.0670608511806068	-2.03541283308675	0.0421776112396033	*  
df.mm.trans1:exp3	-0.193708220043558	0.0816042452235408	-2.37375175167576	0.0178716217797716	*  
df.mm.trans2:exp3	-0.122968135117266	0.0670608511806068	-1.83367990343712	0.0671170282312745	.  
df.mm.trans1:exp4	-0.131690344834289	0.0816042452235408	-1.61376830915531	0.107018906143879	   
df.mm.trans2:exp4	-0.0737393840247027	0.0670608511806068	-1.09958914517964	0.271881263301171	   
df.mm.trans1:exp5	-0.0643136261498181	0.0816042452235408	-0.788116181623174	0.430889954375218	   
df.mm.trans2:exp5	-0.0976438923556207	0.0670608511806068	-1.45604910520220	0.145817992899838	   
df.mm.trans1:exp6	-0.237689984905922	0.0816042452235408	-2.9127159286237	0.00369469195322012	** 
df.mm.trans2:exp6	-0.196703003415668	0.0670608511806068	-2.93320171087467	0.00346216351709181	** 
df.mm.trans1:exp7	-0.264492341074518	0.0816042452235408	-3.24115908859872	0.00124563056770426	** 
df.mm.trans2:exp7	-0.094557294820669	0.0670608511806068	-1.41002228805610	0.158967948193221	   
df.mm.trans1:exp8	-0.179582016645268	0.0816042452235408	-2.20064551976842	0.0280801224781136	*  
df.mm.trans2:exp8	-0.124412298553686	0.0670608511806068	-1.85521502282489	0.0639769190181217	.  
df.mm.trans1:probe2	0.434189918091938	0.0476466140592184	9.11271297373403	7.96576324480881e-19	***
df.mm.trans1:probe3	0.555393593059289	0.0476466140592184	11.6565175516776	7.20073260968268e-29	***
df.mm.trans1:probe4	0.229376140141527	0.0476466140592184	4.81411207638896	1.80506669710449e-06	***
df.mm.trans1:probe5	0.372508067623122	0.0476466140592184	7.81814353398008	1.92239293009820e-14	***
df.mm.trans1:probe6	-0.0130144557272725	0.0476466140592184	-0.273145447672258	0.784820286845557	   
df.mm.trans1:probe7	0.350790548773006	0.0476466140592184	7.36233950091437	4.98356428714544e-13	***
df.mm.trans1:probe8	0.133730535479205	0.0476466140592184	2.80671645026016	0.00514115580561456	** 
df.mm.trans1:probe9	0.0980131606209305	0.0476466140592184	2.05708553600710	0.0400402042917466	*  
df.mm.trans1:probe10	0.760168641920518	0.0476466140592184	15.9543056086993	3.02368955502558e-49	***
df.mm.trans1:probe11	1.06048722650143	0.0476466140592184	22.2573470841683	8.6382200972138e-84	***
df.mm.trans1:probe12	0.763090545967197	0.0476466140592184	16.0156300932271	1.46447635725398e-49	***
df.mm.trans1:probe13	0.815774137675977	0.0476466140592184	17.1213454257648	2.4947542936884e-55	***
df.mm.trans1:probe14	0.699762783970762	0.0476466140592184	14.6865165088342	7.17978677364647e-43	***
df.mm.trans1:probe15	0.816170186693275	0.0476466140592184	17.1296576432248	2.25444657179668e-55	***
df.mm.trans1:probe16	0.194732430635060	0.0476466140592184	4.08701508974035	4.86489354803475e-05	***
df.mm.trans1:probe17	0.127050703353263	0.0476466140592184	2.66652113401713	0.00783733885052944	** 
df.mm.trans1:probe18	0.133968128126699	0.0476466140592184	2.8117030091623	0.00506300299548409	** 
df.mm.trans1:probe19	0.106598298124909	0.0476466140592184	2.23726911617311	0.0255761212787585	*  
df.mm.trans1:probe20	0.0306963478694856	0.0476466140592184	0.644250351794865	0.519619721489478	   
df.mm.trans1:probe21	0.309025657954058	0.0476466140592184	6.48578422739504	1.64706940724098e-10	***
df.mm.trans2:probe2	-0.0921518899371376	0.0476466140592184	-1.93407006471866	0.0534988018248705	.  
df.mm.trans2:probe3	0.00601234177855843	0.0476466140592184	0.126186128799958	0.899620065349395	   
df.mm.trans2:probe4	0.112783642131055	0.0476466140592184	2.36708618981571	0.0181941535447477	*  
df.mm.trans2:probe5	0.124994120754487	0.0476466140592184	2.62335788644154	0.00889238772710154	** 
df.mm.trans2:probe6	0.163495784858427	0.0476466140592184	3.43142504638889	0.000634947405396796	***
df.mm.trans3:probe2	-0.0914855021459438	0.0476466140592184	-1.92008401755977	0.0552448296994738	.  
df.mm.trans3:probe3	-0.0669240412588209	0.0476466140592184	-1.40459175494912	0.160576970734440	   
df.mm.trans3:probe4	0.0921996436205828	0.0476466140592184	1.9350723118749	0.0533754739707848	.  
df.mm.trans3:probe5	-0.211059453093806	0.0476466140592184	-4.42968419186066	1.09151540124209e-05	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.97357594895501	0.155141526015636	25.6125877513576	3.60609038021416e-103	***
df.mm.trans1	0.217433410031496	0.13649027518474	1.59303224890710	0.111594909497466	   
df.mm.trans2	0.133855544123043	0.123410024100444	1.08464077451357	0.27844637198226	   
df.mm.exp2	0.442175344918363	0.164441724819381	2.68894859503596	0.00733475436993212	** 
df.mm.exp3	0.161891786401782	0.164441724819381	0.984493361277991	0.325206011717110	   
df.mm.exp4	0.326784203790906	0.164441724819381	1.98723410466436	0.0472775978822708	*  
df.mm.exp5	0.379757025965257	0.164441724819381	2.30937145899178	0.0212070975728440	*  
df.mm.exp6	-0.07241781676889	0.164441724819381	-0.440385898703217	0.659790739025468	   
df.mm.exp7	0.281318345468191	0.164441724819381	1.71074796118312	0.0875614117833194	.  
df.mm.exp8	-0.0553095768733982	0.164441724819381	-0.336347584131395	0.736707457787922	   
df.mm.trans1:exp2	-0.30195339827105	0.154702652361228	-1.95183077770376	0.0513483274689023	.  
df.mm.trans2:exp2	-0.276672546597684	0.127131762800113	-2.17626610772865	0.0298620010256638	*  
df.mm.trans1:exp3	-0.0597535328785145	0.154702652361228	-0.386247630318522	0.699428189316341	   
df.mm.trans2:exp3	-0.051615423849218	0.127131762800113	-0.405999434856983	0.684864489687192	   
df.mm.trans1:exp4	-0.315821158624862	0.154702652361228	-2.04147216485613	0.0415705005478963	*  
df.mm.trans2:exp4	-0.152855178135751	0.127131762800113	-1.20233665269066	0.229631149491335	   
df.mm.trans1:exp5	-0.343045373760542	0.154702652361228	-2.21744985315143	0.0269060447391919	*  
df.mm.trans2:exp5	-0.23315241123477	0.127131762800113	-1.83394303751888	0.0670779061862707	.  
df.mm.trans1:exp6	0.0742054666044408	0.154702652361228	0.479665121908655	0.63161221930685	   
df.mm.trans2:exp6	0.0377888357406285	0.127131762800113	0.297241498963899	0.766368476046446	   
df.mm.trans1:exp7	-0.249171651426936	0.154702652361228	-1.61064886492783	0.107697622754778	   
df.mm.trans2:exp7	-0.142951970098732	0.127131762800113	-1.12443945517764	0.261203989535009	   
df.mm.trans1:exp8	0.0115046491738238	0.154702652361228	0.0743662050923385	0.940739798951334	   
df.mm.trans2:exp8	0.0867906041457885	0.127131762800113	0.682682299326312	0.495028736630366	   
df.mm.trans1:probe2	-0.0143371840675599	0.0903268886416524	-0.158725538797631	0.873929936901542	   
df.mm.trans1:probe3	-0.0864812788499637	0.0903268886416524	-0.957425636490756	0.338676077377706	   
df.mm.trans1:probe4	-0.0829250838344292	0.0903268886416524	-0.918055355182355	0.358899462153276	   
df.mm.trans1:probe5	0.0464127044878738	0.0903268886416524	0.513830435054657	0.607529300083845	   
df.mm.trans1:probe6	-0.0410069965812548	0.0903268886416524	-0.453984380486512	0.649977838819759	   
df.mm.trans1:probe7	0.0278396832637599	0.0903268886416524	0.308210364404406	0.758012034834727	   
df.mm.trans1:probe8	0.100235375895235	0.0903268886416524	1.10969587686001	0.267503177671622	   
df.mm.trans1:probe9	0.0136725466837775	0.0903268886416524	0.151367404428372	0.879728597144212	   
df.mm.trans1:probe10	-0.000615220015929766	0.0903268886416524	-0.00681103960494516	0.994567518534274	   
df.mm.trans1:probe11	0.0575175548813959	0.0903268886416524	0.636771129243489	0.524477744115521	   
df.mm.trans1:probe12	0.00299013739227944	0.0903268886416524	0.033103513662936	0.973601279464761	   
df.mm.trans1:probe13	-0.0677362869042231	0.0903268886416524	-0.74990169508604	0.453560587099934	   
df.mm.trans1:probe14	-0.0537235407060993	0.0903268886416524	-0.594767975671486	0.55218674269636	   
df.mm.trans1:probe15	-0.0164655324713759	0.0903268886416524	-0.182288272285105	0.855408171546946	   
df.mm.trans1:probe16	-0.00483292267236135	0.0903268886416524	-0.0535048062104151	0.957344646835287	   
df.mm.trans1:probe17	0.0279885630261038	0.0903268886416524	0.30985859744534	0.756758775058767	   
df.mm.trans1:probe18	-0.0305443706074362	0.0903268886416524	-0.338153688970875	0.735346637900333	   
df.mm.trans1:probe19	0.01940574247542	0.0903268886416524	0.214839044798798	0.829954071003806	   
df.mm.trans1:probe20	0.124436100284624	0.0903268886416524	1.37761968950675	0.168751778094648	   
df.mm.trans1:probe21	0.0401128215750657	0.0903268886416524	0.44408505793001	0.657115457512944	   
df.mm.trans2:probe2	0.0934485269032987	0.0903268886416524	1.03455934670827	0.301224527568036	   
df.mm.trans2:probe3	0.104700438846183	0.0903268886416524	1.15912814468296	0.246790916708305	   
df.mm.trans2:probe4	-0.067046376098758	0.0903268886416524	-0.742263761179093	0.458171309352219	   
df.mm.trans2:probe5	-0.00153672070110814	0.0903268886416524	-0.0170128820356545	0.986431085000573	   
df.mm.trans2:probe6	-0.0482464727619216	0.0903268886416524	-0.534131901225187	0.593416306403893	   
df.mm.trans3:probe2	-0.0936248958189902	0.0903268886416524	-1.03651190943177	0.300313801338388	   
df.mm.trans3:probe3	-0.00736168237411809	0.0903268886416524	-0.0815004533514221	0.935066772528984	   
df.mm.trans3:probe4	-0.136229083139693	0.0903268886416524	-1.50817862973389	0.131950531473958	   
df.mm.trans3:probe5	-0.107294209634960	0.0903268886416524	-1.18784352310220	0.2352894967541