chr6.19722_chr6_135446263_135457216_-_2.R 

fitVsDatCorrelation=0.961381463571435
cont.fitVsDatCorrelation=0.225982385515349

fstatistic=10820.9265971183,58,830
cont.fstatistic=850.580332005017,58,830

residuals=-1.0522119557809,-0.0779995942921702,-0.00342887807641739,0.0788826940273812,0.629015406397729
cont.residuals=-0.80528196693643,-0.321403157351090,-0.164222366549212,0.0288053243435023,2.15906034086746

predictedValues:
Include	Exclude	Both
chr6.19722_chr6_135446263_135457216_-_2.R.tl.Lung	64.4479302624176	53.895466783087	53.5881839075295
chr6.19722_chr6_135446263_135457216_-_2.R.tl.cerebhem	60.1037924183092	55.7321084262335	62.7229633288093
chr6.19722_chr6_135446263_135457216_-_2.R.tl.cortex	60.75345098337	53.81922469282	51.9846832963618
chr6.19722_chr6_135446263_135457216_-_2.R.tl.heart	65.421932336258	52.142350059857	52.5688350236012
chr6.19722_chr6_135446263_135457216_-_2.R.tl.kidney	63.4834082263488	55.491833980533	54.1056968116311
chr6.19722_chr6_135446263_135457216_-_2.R.tl.liver	67.656887598937	57.6424531090851	55.2063608098686
chr6.19722_chr6_135446263_135457216_-_2.R.tl.stomach	66.9655059506892	57.5061965351118	57.4816326174021
chr6.19722_chr6_135446263_135457216_-_2.R.tl.testicle	68.225001315604	56.0456459464329	55.4172228147109


diffExp=10.5524634793305,4.37168399207570,6.93422629055,13.2795822764010,7.99157424581577,10.0144344898519,9.4593094155774,12.1793553691711
diffExpScore=0.986804363931124
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=0,0,0,1,0,0,0,1
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	70.0725341914595	63.2752281031485	55.7069562800069
cerebhem	72.4368457197516	66.1716909982851	63.4807425869871
cortex	66.6035614240665	53.4732892897711	59.8737876351933
heart	67.491283943099	65.5899117022987	66.9116103344824
kidney	68.640454892881	67.9884784432909	65.6140662101353
liver	68.876039382794	61.015849407636	65.2524982056472
stomach	75.0659441901297	91.153140024567	69.4914870809977
testicle	68.4117089541803	90.185222763925	67.49210638602
cont.diffExp=6.79730608831096,6.26515472146643,13.1302721342954,1.9013722408002,0.651976449590137,7.86018997515798,-16.0871958344373,-21.7735138097447
cont.diffExpScore=33.0312832343189

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,-1
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,0,1,0,0,0,-1,-1
cont.diffExp1.2Score=1.5

tran.correlation=0.400714150573533
cont.tran.correlation=0.547075719028594

tran.covariance=0.00063068068339352
cont.tran.covariance=0.00406699197834458

tran.mean=59.9583242890684
cont.tran.mean=69.7781989644552

weightedLogRatios:
wLogRatio
Lung	0.728915455376029
cerebhem	0.306469751984778
cortex	0.490375022713453
heart	0.92281601001071
kidney	0.549406127052544
liver	0.662281513332253
stomach	0.628637599611101
testicle	0.811058531951862

cont.weightedLogRatios:
wLogRatio
Lung	0.428403597844876
cerebhem	0.383332734720871
cortex	0.897838841682391
heart	0.119956132270574
kidney	0.0403141733985058
liver	0.505507047564072
stomach	-0.857366210207907
testicle	-1.20578585750804

varWeightedLogRatios=0.0370806507000862
cont.varWeightedLogRatios=0.51213614383709

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.75858191135001	0.074635614027159	50.3590941180213	1.46750357517519e-254	***
df.mm.trans1	0.0280732994527478	0.0646156574548038	0.434465895087177	0.664063079720426	   
df.mm.trans2	0.203855934327767	0.0572456495944267	3.56107295090619	0.000390362098683044	***
df.mm.exp2	-0.193673637683096	0.0739881603225002	-2.61763012945462	0.00901550604871565	** 
df.mm.exp3	-0.0300698875460850	0.0739881603225002	-0.406414856309659	0.684542571595279	   
df.mm.exp4	0.00113619366049409	0.0739881603225002	0.0153564253461857	0.987751517297276	   
df.mm.exp5	0.00449958570589754	0.0739881603225002	0.0608149423675992	0.951521230251042	   
df.mm.exp6	0.0860549214499455	0.0739881603225002	1.16309043331864	0.245127088199604	   
df.mm.exp7	0.0330295031516825	0.0739881603225002	0.446416061809258	0.655413175619232	   
df.mm.exp8	0.0625117333082394	0.0739881603225002	0.84488833126493	0.398416661450045	   
df.mm.trans1:exp2	0.123888964015259	0.0685888603308397	1.80625488479730	0.0712406519831665	.  
df.mm.trans2:exp2	0.227183701257759	0.0514935802893714	4.41188396652721	1.15973673538226e-05	***
df.mm.trans1:exp3	-0.0289638405563715	0.0685888603308397	-0.422281991808347	0.672928563938922	   
df.mm.trans2:exp3	0.0286542570140762	0.0514935802893713	0.556462705701407	0.578044574633339	   
df.mm.trans1:exp4	0.0138637503863332	0.0685888603308397	0.202128309458141	0.839865948250848	   
df.mm.trans2:exp4	-0.0342050842281637	0.0514935802893714	-0.664259195727818	0.506708919395521	   
df.mm.trans1:exp5	-0.0195786167431971	0.0685888603308397	-0.285448929297838	0.775371443307702	   
df.mm.trans2:exp5	0.0246899185670071	0.0514935802893714	0.479475663340179	0.631726586973774	   
df.mm.trans1:exp6	-0.0374633747826569	0.0685888603308397	-0.546202030503957	0.585073853290547	   
df.mm.trans2:exp6	-0.0188419622479136	0.0514935802893714	-0.3659089568453	0.714526251894281	   
df.mm.trans1:exp7	0.00529053208824992	0.0685888603308397	0.0771339844798549	0.9385355472579	   
df.mm.trans2:exp7	0.0318168345052278	0.0514935802893714	0.617879633275277	0.536824177957744	   
df.mm.trans1:exp8	-0.00555826245083619	0.0685888603308397	-0.0810373933030203	0.935431750848237	   
df.mm.trans2:exp8	-0.0233916385735340	0.0514935802893714	-0.454263200229683	0.649758166808301	   
df.mm.trans1:probe2	0.163600789762240	0.0460108062596989	3.55570360664466	0.000398299252935351	***
df.mm.trans1:probe3	0.164898962245406	0.0460108062596989	3.58391811946669	0.000358218139825571	***
df.mm.trans1:probe4	0.285434972291980	0.0460108062596989	6.20365073980446	8.69723896565489e-10	***
df.mm.trans1:probe5	0.00580025289021484	0.0460108062596989	0.126062839618077	0.899712711919585	   
df.mm.trans1:probe6	0.179042779073468	0.0460108062596989	3.8913201838476	0.000107689111577869	***
df.mm.trans1:probe7	0.0364451181967670	0.0460108062596989	0.792099099308536	0.428529218611588	   
df.mm.trans1:probe8	0.126436024198556	0.0460108062596989	2.74796367368380	0.00612676101512962	** 
df.mm.trans1:probe9	0.0329148489598736	0.0460108062596989	0.715372140494393	0.474580304279571	   
df.mm.trans1:probe10	0.00563702175241607	0.0460108062596989	0.122515170036339	0.902520690183766	   
df.mm.trans1:probe11	0.337117973072045	0.0460108062596989	7.32693035564841	5.58399832914602e-13	***
df.mm.trans1:probe12	0.127070504416536	0.0460108062596989	2.76175348241696	0.00587619725540435	** 
df.mm.trans1:probe13	0.153298340449661	0.0460108062596989	3.33178991875079	0.000901043219092552	***
df.mm.trans1:probe14	0.320142346775298	0.0460108062596989	6.95798167431186	7.00530767150283e-12	***
df.mm.trans1:probe15	0.208517125401788	0.0460108062596989	4.53191635514611	6.70334402194121e-06	***
df.mm.trans1:probe16	0.195568143382728	0.0460108062596989	4.25048286002385	2.37511750954929e-05	***
df.mm.trans1:probe17	1.48774849408647	0.0460108062596989	32.3347625270717	4.35543925648428e-149	***
df.mm.trans1:probe18	2.15758095702463	0.0460108062596989	46.8929178255777	1.55973307291992e-235	***
df.mm.trans1:probe19	1.00540804958596	0.0460108062596989	21.8515633895032	5.69473169984558e-84	***
df.mm.trans1:probe20	1.62689615015579	0.0460108062596989	35.3590011218907	8.93654935655602e-168	***
df.mm.trans1:probe21	1.50226091062732	0.0460108062596989	32.6501757467171	4.76620457476241e-151	***
df.mm.trans1:probe22	1.63345476639499	0.0460108062596989	35.5015462492720	1.19527081190714e-168	***
df.mm.trans2:probe2	-0.0602592981951395	0.0460108062596989	-1.30967707575081	0.190667492697319	   
df.mm.trans2:probe3	0.0162671142971151	0.0460108062596989	0.353549864031911	0.723766035085807	   
df.mm.trans2:probe4	-0.00627433479617768	0.0460108062596989	-0.136366547475031	0.89156458580259	   
df.mm.trans2:probe5	0.282668255346006	0.0460108062596989	6.14351884534562	1.25133401616361e-09	***
df.mm.trans2:probe6	0.136726130703130	0.0460108062596989	2.97160910268355	0.00304796414624655	** 
df.mm.trans3:probe2	-0.146553921490759	0.0460108062596989	-3.18520655046914	0.00150052760425114	** 
df.mm.trans3:probe3	-0.134998206743893	0.0460108062596989	-2.93405436066306	0.00343783495339259	** 
df.mm.trans3:probe4	0.0468088512461142	0.0460108062596989	1.01734472945140	0.309285917421407	   
df.mm.trans3:probe5	0.000271266102532582	0.0460108062596989	0.0058957041743949	0.995297352624714	   
df.mm.trans3:probe6	-0.0117683101664697	0.0460108062596989	-0.255772743908155	0.798189693947917	   
df.mm.trans3:probe7	-0.09572146260074	0.0460108062596989	-2.08041263307709	0.0377939281347574	*  
df.mm.trans3:probe8	0.122082656578887	0.0460108062596989	2.65334747428280	0.00812214164281481	** 
df.mm.trans3:probe9	0.137236169489863	0.0460108062596989	2.98269429827551	0.00294086219425365	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.34566163230789	0.264170737535649	16.4502006272419	7.67363262376241e-53	***
df.mm.trans1	-0.0177393305598138	0.228705372209774	-0.0775641183607304	0.9381934794744	   
df.mm.trans2	-0.201636401118295	0.202619428689420	-0.995148404190636	0.319954117726536	   
df.mm.exp2	-0.0526885539856724	0.261879092656602	-0.201194197868870	0.840596022093325	   
df.mm.exp3	-0.291218284898913	0.261879092656602	-1.11203335075238	0.266445802922541	   
df.mm.exp4	-0.184871930012100	0.261879092656602	-0.705943831318067	0.480421161989703	   
df.mm.exp5	-0.112489550556433	0.261879092656602	-0.429547656574246	0.667636203461333	   
df.mm.exp6	-0.211742109355924	0.261879092656602	-0.808549117869362	0.41900623238881	   
df.mm.exp7	0.212783883367273	0.261879092656602	0.812527190348461	0.416722176197719	   
df.mm.exp8	0.138479138899616	0.261879092656602	0.528790357011056	0.597092260200878	   
df.mm.trans1:exp2	0.0858727344061844	0.242768416345234	0.353722842942087	0.72363643192578	   
df.mm.trans2:exp2	0.0974473856711314	0.182260134932961	0.534660998176999	0.593027486989461	   
df.mm.trans1:exp3	0.240445427554347	0.242768416345234	0.990431256149959	0.322252016145964	   
df.mm.trans2:exp3	0.122906637140846	0.182260134932961	0.674347339784719	0.50027828504591	   
df.mm.trans1:exp4	0.147339484487086	0.242768416345234	0.606913727515358	0.54407414505999	   
df.mm.trans2:exp4	0.220799917736382	0.182260134932961	1.21145481329528	0.226065934531116	   
df.mm.trans1:exp5	0.0918407246444536	0.242768416345234	0.378305901678122	0.705300096938683	   
df.mm.trans2:exp5	0.184333895345682	0.182260134932961	1.01137802522468	0.312130273974025	   
df.mm.trans1:exp6	0.194519559275386	0.242768416345234	0.80125562543838	0.423212987044799	   
df.mm.trans2:exp6	0.175381854761205	0.182260134932961	0.962261192365044	0.336198667299416	   
df.mm.trans1:exp7	-0.14394780857859	0.242768416345234	-0.592942899021451	0.553380885964723	   
df.mm.trans2:exp7	0.152263154770787	0.182260134932961	0.835416668745433	0.40372356026783	   
df.mm.trans1:exp8	-0.162466053677707	0.242768416345234	-0.669222364768689	0.503539743853314	   
df.mm.trans2:exp8	0.215892535923139	0.182260134932961	1.18452966142348	0.236542539746572	   
df.mm.trans1:probe2	-0.337344476995996	0.162854004521374	-2.07145337314514	0.0386249014529792	*  
df.mm.trans1:probe3	-0.251616773385367	0.162854004521374	-1.54504504893733	0.122716540864574	   
df.mm.trans1:probe4	-0.113720042887343	0.162854004521374	-0.698294421568353	0.485188677686591	   
df.mm.trans1:probe5	-0.150267278557846	0.162854004521374	-0.922711596804017	0.356425663202882	   
df.mm.trans1:probe6	-0.0433178695202917	0.162854004521374	-0.265992043902158	0.79031139463084	   
df.mm.trans1:probe7	0.0112849229793411	0.162854004521375	0.0692947220580012	0.944771717511938	   
df.mm.trans1:probe8	-0.109634891768093	0.162854004521374	-0.67320967691466	0.501001306319498	   
df.mm.trans1:probe9	-0.0808570523627593	0.162854004521374	-0.496500240202241	0.619672982219893	   
df.mm.trans1:probe10	-0.00483137533814781	0.162854004521374	-0.0296669114913517	0.97633983291375	   
df.mm.trans1:probe11	-0.144249318322403	0.162854004521374	-0.885758497289334	0.376004223894992	   
df.mm.trans1:probe12	0.089603200836245	0.162854004521374	0.550205695583522	0.582326330674175	   
df.mm.trans1:probe13	-0.0389203226459438	0.162854004521375	-0.238989042733889	0.811173076459335	   
df.mm.trans1:probe14	-0.138187282498434	0.162854004521374	-0.84853475298053	0.396384872963272	   
df.mm.trans1:probe15	-0.108311106547672	0.162854004521375	-0.665081014531986	0.506183431638793	   
df.mm.trans1:probe16	-0.196828389793306	0.162854004521375	-1.20861866658902	0.227153588652961	   
df.mm.trans1:probe17	-0.108392995524921	0.162854004521374	-0.665583851275177	0.505862049213432	   
df.mm.trans1:probe18	-0.0329413715558167	0.162854004521374	-0.202275477674810	0.839750938515923	   
df.mm.trans1:probe19	-0.212466863111012	0.162854004521374	-1.30464623044087	0.192374958594677	   
df.mm.trans1:probe20	-0.0698831633272454	0.162854004521374	-0.429115412498642	0.667950593468612	   
df.mm.trans1:probe21	-0.145229982104422	0.162854004521374	-0.891780233045241	0.372769190075731	   
df.mm.trans1:probe22	-0.244020764551568	0.162854004521374	-1.49840199059729	0.134409052958020	   
df.mm.trans2:probe2	0.154409896339410	0.162854004521374	0.94814921372808	0.343329467471202	   
df.mm.trans2:probe3	0.0390182535315034	0.162854004521375	0.239590384321083	0.810706973162006	   
df.mm.trans2:probe4	-0.178038758820822	0.162854004521375	-1.09324151619160	0.274604964118833	   
df.mm.trans2:probe5	0.108277453427417	0.162854004521374	0.664874368583341	0.506315538252513	   
df.mm.trans2:probe6	-0.0716366417160416	0.162854004521375	-0.439882592550184	0.660136660071351	   
df.mm.trans3:probe2	-0.128503432340883	0.162854004521374	-0.789071369282891	0.430295628535217	   
df.mm.trans3:probe3	-0.203685043600973	0.162854004521374	-1.25072173815805	0.211388474967135	   
df.mm.trans3:probe4	-0.0588190246303702	0.162854004521375	-0.361176409528512	0.718059488173476	   
df.mm.trans3:probe5	-0.169562867170220	0.162854004521374	-1.04119556450922	0.298087980051787	   
df.mm.trans3:probe6	-0.0703104007365325	0.162854004521374	-0.431738850654448	0.666043352031428	   
df.mm.trans3:probe7	-0.123267759222628	0.162854004521374	-0.756921879722335	0.449311472463886	   
df.mm.trans3:probe8	-0.151902674837854	0.162854004521374	-0.932753697302647	0.351218402216847	   
df.mm.trans3:probe9	-0.0495766559363625	0.162854004521374	-0.304423929163226	0.760881248764392