chr6.20048_chr6_148945505_148947405_-_2.R 

fitVsDatCorrelation=0.950333068501605
cont.fitVsDatCorrelation=0.270159939625369

fstatistic=8127.54274986758,62,922
cont.fstatistic=835.959767964613,62,922

residuals=-0.576110426247416,-0.0891876801578814,-0.00603825933598601,0.0814364406902454,1.46343596752215
cont.residuals=-0.979829837035534,-0.396044970578276,-0.213925745506957,0.386792674830661,2.2094561123433

predictedValues:
Include	Exclude	Both
chr6.20048_chr6_148945505_148947405_-_2.R.tl.Lung	56.0679508571951	190.189439651686	49.4875693328037
chr6.20048_chr6_148945505_148947405_-_2.R.tl.cerebhem	62.4962596116245	111.065049650917	50.4357491118489
chr6.20048_chr6_148945505_148947405_-_2.R.tl.cortex	52.6685131249549	150.346686387916	52.8569846210911
chr6.20048_chr6_148945505_148947405_-_2.R.tl.heart	55.6478174120804	148.644024873784	50.4619848821051
chr6.20048_chr6_148945505_148947405_-_2.R.tl.kidney	54.7798430920366	183.999711873943	52.0666430318802
chr6.20048_chr6_148945505_148947405_-_2.R.tl.liver	56.0001806871853	159.320976932753	50.2976934458235
chr6.20048_chr6_148945505_148947405_-_2.R.tl.stomach	53.7019629769409	147.629818329125	48.4823841705784
chr6.20048_chr6_148945505_148947405_-_2.R.tl.testicle	54.4886845215264	128.608066748541	51.2159875919966


diffExp=-134.121488794491,-48.5687900392928,-97.6781732629615,-92.9962074617033,-129.219868781906,-103.320796245568,-93.9278553521845,-74.1193822270149
diffExpScore=0.998709598433734
diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.888888888888889
diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.4Score=0.888888888888889
diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.3Score=0.888888888888889
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	60.8540365182688	97.0628385730102	69.1666908145429
cerebhem	65.0191205214329	70.8405667264539	63.9890491402838
cortex	65.8955827949107	65.0003705241203	62.9354128621624
heart	78.9373119936364	76.7434564524549	83.3716823256118
kidney	64.6279248893143	89.9529662515695	64.9082899958152
liver	64.4716233381674	88.912703163182	65.4913949264581
stomach	66.2086698924418	94.4781209819969	59.1164465442027
testicle	67.5957685413167	87.0040766109037	85.0638749791955
cont.diffExp=-36.2088020547414,-5.821446205021,0.895212270790395,2.19385554118149,-25.3250413622552,-24.4410798250147,-28.2694510895551,-19.4083080695870
cont.diffExpScore=1.03769067461928

cont.diffExp1.5=-1,0,0,0,0,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=-1,0,0,0,0,0,-1,0
cont.diffExp1.4Score=0.666666666666667
cont.diffExp1.3=-1,0,0,0,-1,-1,-1,0
cont.diffExp1.3Score=0.8
cont.diffExp1.2=-1,0,0,0,-1,-1,-1,-1
cont.diffExp1.2Score=0.833333333333333

tran.correlation=-0.457744074880663
cont.tran.correlation=-0.356957725594599

tran.covariance=-0.00460773887750853
cont.tran.covariance=-0.00367894686273701

tran.mean=104.103436670763
cont.tran.mean=75.2253211108238

weightedLogRatios:
wLogRatio
Lung	-5.66424996073014
cerebhem	-2.54304291503823
cortex	-4.7080845496681
heart	-4.4314202281191
kidney	-5.58447459506558
liver	-4.75537823219412
stomach	-4.53961838788941
testicle	-3.80213092857031

cont.weightedLogRatios:
wLogRatio
Lung	-2.02715674346668
cerebhem	-0.361657268727163
cortex	0.0571927340703633
heart	0.122737194656968
kidney	-1.43298426736950
liver	-1.39080769183698
stomach	-1.55399322226763
testicle	-1.09539456201612

varWeightedLogRatios=0.994707799448812
cont.varWeightedLogRatios=0.640615273965471

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.1870528319617	0.0859414133442233	60.3556845311104	0	***
df.mm.trans1	-1.36862010360542	0.0735958295030496	-18.5964355976001	8.52203720204678e-66	***
df.mm.trans2	0.00030441710669585	0.0646943457006986	0.00470546696776566	0.99624661228827	   
df.mm.exp2	-0.448340936222197	0.0821757087645187	-5.45588158548112	6.26261202564171e-08	***
df.mm.exp3	-0.36349166607575	0.0821757087645187	-4.42334689339115	1.08773495659826e-05	***
df.mm.exp4	-0.273486544551435	0.0821757087645187	-3.32807040746230	0.000909111145796768	***
df.mm.exp5	-0.107131479698204	0.0821757087645187	-1.30368793051969	0.192665419384974	   
df.mm.exp6	-0.194546888735444	0.0821757087645187	-2.36745008543746	0.0181167442620267	*  
df.mm.exp7	-0.275906526773569	0.0821757087645187	-3.35751928303049	0.000818630822358732	***
df.mm.exp8	-0.454152623131505	0.0821757087645187	-5.52660427222985	4.24952782307429e-08	***
df.mm.trans1:exp2	0.556883281645043	0.0750158156155031	7.42354498282566	2.59120423049125e-13	***
df.mm.trans2:exp2	-0.0895636274583718	0.053044191917962	-1.68847189899491	0.0916588311668771	.  
df.mm.trans1:exp3	0.300945105839984	0.0750158156155031	4.01175543278089	6.51516177860126e-05	***
df.mm.trans2:exp3	0.128414909711447	0.053044191917962	2.42090425112052	0.0156741718670543	*  
df.mm.trans1:exp4	0.265965038280516	0.0750158156155031	3.54545286348324	0.000411650172532763	***
df.mm.trans2:exp4	0.0270202710156122	0.053044191917962	0.509391698480424	0.610599585523717	   
df.mm.trans1:exp5	0.0838894158850107	0.0750158156155031	1.11828972592912	0.263734555114725	   
df.mm.trans2:exp5	0.074045045169647	0.053044191917962	1.39591239855562	0.163076906514936	   
df.mm.trans1:exp6	0.193337442707623	0.0750158156155031	2.57728908392574	0.0101122203898873	*  
df.mm.trans2:exp6	0.0174471526864939	0.053044191917962	0.328917305658603	0.742292888542131	   
df.mm.trans1:exp7	0.232791718811060	0.0750158156155031	3.10323518981977	0.00197251852520071	** 
df.mm.trans2:exp7	0.0225938135026102	0.053044191917962	0.425943212360625	0.67024863911287	   
df.mm.trans1:exp8	0.425581316471094	0.0750158156155031	5.67322121314297	1.87555536866167e-08	***
df.mm.trans2:exp8	0.0629015341720205	0.053044191917962	1.18583264062734	0.235993908303571	   
df.mm.trans1:probe2	-0.0313948998057734	0.0543541223003468	-0.577599241365601	0.563675740546465	   
df.mm.trans1:probe3	0.06800767619455	0.0543541223003468	1.2511962904811	0.211180249371154	   
df.mm.trans1:probe4	0.0759106932563982	0.0543541223003468	1.39659495993579	0.162871497992449	   
df.mm.trans1:probe5	0.0544755560934839	0.0543541223003468	1.00223412296985	0.316493486267798	   
df.mm.trans1:probe6	0.563702446642363	0.0543541223003468	10.3709235433421	6.5362768040983e-24	***
df.mm.trans1:probe7	-0.0391316596112041	0.0543541223003468	-0.719939131662776	0.471744931925039	   
df.mm.trans1:probe8	-0.0250875548179065	0.0543541223003468	-0.461557537058168	0.644507523920779	   
df.mm.trans1:probe9	0.0677627768743735	0.0543541223003468	1.24669066496804	0.212827567533960	   
df.mm.trans1:probe10	-0.0909994724312087	0.0543541223003468	-1.67419633654222	0.094431171011364	.  
df.mm.trans1:probe11	0.0826870090887085	0.0543541223003468	1.52126472821696	0.128536278999621	   
df.mm.trans1:probe12	0.0637957286957153	0.0543541223003468	1.17370543384357	0.240816128153138	   
df.mm.trans1:probe13	-0.0320680528662914	0.0543541223003468	-0.589983822921316	0.55534605266161	   
df.mm.trans1:probe14	-0.00848814167013422	0.0543541223003468	-0.156163715113105	0.875938162107408	   
df.mm.trans1:probe15	0.0100978568046677	0.0543541223003468	0.18577904264316	0.852658902675184	   
df.mm.trans1:probe16	0.90815874017064	0.0543541223003468	16.7081851704345	6.01412039546919e-55	***
df.mm.trans1:probe17	0.926910530986493	0.0543541223003468	17.0531781538965	6.9248811336301e-57	***
df.mm.trans1:probe18	1.22103842073766	0.0543541223003468	22.4645044214038	1.75518805841547e-89	***
df.mm.trans1:probe19	1.23160248908575	0.0543541223003468	22.6588607627629	1.03503206666997e-90	***
df.mm.trans1:probe20	1.16481730539404	0.0543541223003468	21.4301557287147	5.40542155069187e-83	***
df.mm.trans1:probe21	1.07280977472028	0.0543541223003468	19.7374132690840	1.32352066945964e-72	***
df.mm.trans2:probe2	0.124306816109770	0.0543541223003468	2.28698046898600	0.0224228198831475	*  
df.mm.trans2:probe3	-0.0659628244909474	0.0543541223003468	-1.21357537752986	0.225220702862782	   
df.mm.trans2:probe4	0.286859969832761	0.0543541223003468	5.27761203184639	1.63228848860019e-07	***
df.mm.trans2:probe5	0.0510961574762597	0.0543541223003468	0.940060391260032	0.347432797366697	   
df.mm.trans2:probe6	0.816967424380811	0.0543541223003468	15.0304593249885	7.8191856242877e-46	***
df.mm.trans3:probe2	-0.0656344732470757	0.0543541223003468	-1.20753441449016	0.227536068643445	   
df.mm.trans3:probe3	-0.0773814539118886	0.0543541223003468	-1.42365382121891	0.154885017108927	   
df.mm.trans3:probe4	0.0218669977065949	0.0543541223003468	0.402306150502505	0.687551977555509	   
df.mm.trans3:probe5	-0.00295815502098789	0.0543541223003468	-0.0544237473772805	0.956609349380779	   
df.mm.trans3:probe6	-0.0505174404082737	0.0543541223003468	-0.929413230686118	0.352918235498602	   
df.mm.trans3:probe7	0.0493516028728345	0.0543541223003468	0.907964304899089	0.364134334129768	   
df.mm.trans3:probe8	0.443080667450028	0.0543541223003468	8.1517398993526	1.16426246329814e-15	***
df.mm.trans3:probe9	-0.0585697977518003	0.0543541223003468	-1.07755944301996	0.281512255810196	   
df.mm.trans3:probe10	0.282401947495165	0.0543541223003468	5.19559392265935	2.51257732059391e-07	***
df.mm.trans3:probe11	0.332418107355258	0.0543541223003468	6.11578465968784	1.41775694372930e-09	***
df.mm.trans3:probe12	-0.0275313828998766	0.0543541223003468	-0.506518764993487	0.612613619686584	   
df.mm.trans3:probe13	0.0792529725766948	0.0543541223003468	1.45808577569818	0.145157436601044	   
df.mm.trans3:probe14	0.236001559570241	0.0543541223003468	4.34192568258497	1.56877099120005e-05	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.53746602157932	0.265862747834274	17.0669492380624	5.7889171761617e-57	***
df.mm.trans1	-0.426053313750284	0.227671255328950	-1.87135311892888	0.0616126443790161	.  
df.mm.trans2	0.0836274156284898	0.200134205943732	0.417856683889419	0.676149197982318	   
df.mm.exp2	-0.170916101810096	0.254213409894224	-0.672333146710133	0.501540080316128	   
df.mm.exp3	-0.226961969008845	0.254213409894224	-0.892800930931542	0.372196746733395	   
df.mm.exp4	-0.161503909721553	0.254213409894224	-0.63530838042239	0.525384944653305	   
df.mm.exp5	0.0476408355180154	0.254213409894224	0.187404887640815	0.851384422693765	   
df.mm.exp6	0.024644103189909	0.254213409894224	0.0969425774988159	0.92279306419882	   
df.mm.exp7	0.214353192431526	0.254213409894224	0.84320175131877	0.399334312248549	   
df.mm.exp8	-0.211219425675296	0.254213409894224	-0.830874444283577	0.406259667410676	   
df.mm.trans1:exp2	0.237119337532538	0.232064031698955	1.0217840989686	0.307151117251338	   
df.mm.trans2:exp2	-0.144010674314843	0.164094050483821	-0.87761057692364	0.380383710284671	   
df.mm.trans1:exp3	0.306555226577703	0.232064031698955	1.32099414257950	0.186831070266106	   
df.mm.trans2:exp3	-0.174003649839361	0.164094050483821	-1.06038975408506	0.289245016619945	   
df.mm.trans1:exp4	0.421679775333499	0.232064031698955	1.81708372575601	0.0695288231563807	.  
df.mm.trans2:exp4	-0.0733865544929527	0.164094050483821	-0.447222518284953	0.65481944450628	   
df.mm.trans1:exp5	0.0125276029112465	0.232064031698955	0.0539833890652126	0.956960093035254	   
df.mm.trans2:exp5	-0.123712488092724	0.164094050483821	-0.75391208717175	0.451094500588544	   
df.mm.trans1:exp6	0.0331029227764543	0.232064031698955	0.142645641955394	0.88660121472925	   
df.mm.trans2:exp6	-0.112347667252713	0.164094050483821	-0.684654117083846	0.493734273951894	   
df.mm.trans1:exp7	-0.130019925705398	0.232064031698955	-0.560276078776679	0.575427246484481	   
df.mm.trans2:exp7	-0.241343497836358	0.164094050483821	-1.47076324293764	0.141696340790961	   
df.mm.trans1:exp8	0.316286658438106	0.232064031698955	1.36292839576453	0.173237840955392	   
df.mm.trans2:exp8	0.101815811730014	0.164094050483821	0.620472292748071	0.535100223252231	   
df.mm.trans1:probe2	-0.206579359516047	0.168146365629461	-1.22856868623185	0.219547057078642	   
df.mm.trans1:probe3	-0.0828556291510978	0.168146365629461	-0.492758965327175	0.622300233265567	   
df.mm.trans1:probe4	-0.161066071145168	0.168146365629461	-0.95789207540831	0.338368287520342	   
df.mm.trans1:probe5	0.0220817867824726	0.168146365629461	0.131324793728421	0.895547028598036	   
df.mm.trans1:probe6	0.24088208234078	0.168146365629461	1.43257382601777	0.152318616707608	   
df.mm.trans1:probe7	0.190490097652752	0.168146365629461	1.13288263436231	0.257558055567228	   
df.mm.trans1:probe8	-0.190062142928618	0.168146365629461	-1.13033750219409	0.258627992540423	   
df.mm.trans1:probe9	-0.173214500409547	0.168146365629461	-1.03014120918471	0.303213875675267	   
df.mm.trans1:probe10	0.179112021154666	0.168146365629461	1.06521494225674	0.287057544843567	   
df.mm.trans1:probe11	-0.0523840526150596	0.168146365629461	-0.311538417253079	0.75546177101906	   
df.mm.trans1:probe12	-0.124566162370165	0.168146365629461	-0.740819832197076	0.458991311491761	   
df.mm.trans1:probe13	0.083225402034917	0.168146365629461	0.494958078477405	0.620747638970611	   
df.mm.trans1:probe14	0.0401643625397731	0.168146365629461	0.238865481209877	0.811262975120346	   
df.mm.trans1:probe15	0.102577637885288	0.168146365629461	0.610049687968487	0.541979215941733	   
df.mm.trans1:probe16	0.0747197681135017	0.168146365629461	0.444373375741939	0.656876941832228	   
df.mm.trans1:probe17	0.0116521299305497	0.168146365629461	0.0692975425720894	0.944767807857839	   
df.mm.trans1:probe18	-0.0707696718150361	0.168146365629461	-0.420881364578460	0.67393979895935	   
df.mm.trans1:probe19	-0.0146351127764358	0.168146365629461	-0.0870379369881045	0.930660255822635	   
df.mm.trans1:probe20	0.0695825397493542	0.168146365629461	0.413821253221086	0.679101258130412	   
df.mm.trans1:probe21	-0.0410645520234801	0.168146365629461	-0.2442190877558	0.807115479139958	   
df.mm.trans2:probe2	0.00327649226526587	0.168146365629461	0.0194859535203168	0.984457658321712	   
df.mm.trans2:probe3	-0.152345306041880	0.168146365629461	-0.906027944592028	0.365157768534736	   
df.mm.trans2:probe4	-0.244950571860533	0.168146365629461	-1.45676994530066	0.145520357079588	   
df.mm.trans2:probe5	-0.225981538625489	0.168146365629461	-1.34395731825378	0.179292802561108	   
df.mm.trans2:probe6	-0.294696037919994	0.168146365629461	-1.75261616162081	0.0800002811586154	.  
df.mm.trans3:probe2	0.030745741212311	0.168146365629461	0.182851060129748	0.854955082158137	   
df.mm.trans3:probe3	0.293168421001633	0.168146365629461	1.74353111888056	0.081574194610326	.  
df.mm.trans3:probe4	0.0104139443378078	0.168146365629461	0.0619338056985231	0.950628969045177	   
df.mm.trans3:probe5	-0.0164147589633077	0.168146365629461	-0.0976218480956077	0.92225379222878	   
df.mm.trans3:probe6	0.0741812184179158	0.168146365629461	0.441170513202687	0.659192990852099	   
df.mm.trans3:probe7	-0.105912713764865	0.168146365629461	-0.629884049936957	0.528926509573658	   
df.mm.trans3:probe8	0.0613295366042165	0.168146365629461	0.364738996139629	0.715389887606083	   
df.mm.trans3:probe9	-0.00183199596400156	0.168146365629461	-0.0108952456816027	0.991309380635138	   
df.mm.trans3:probe10	-0.0440857749428906	0.168146365629461	-0.262186903522145	0.79323591555834	   
df.mm.trans3:probe11	0.0232788669241390	0.168146365629461	0.138444068279406	0.889919701481863	   
df.mm.trans3:probe12	0.186847861828204	0.168146365629461	1.11122153088908	0.266762693384399	   
df.mm.trans3:probe13	-0.00567236907713733	0.168146365629461	-0.0337347111601411	0.973096000744887	   
df.mm.trans3:probe14	0.074661895779684	0.168146365629461	0.444029197420861	0.65712566576145