chr1.1141_chr1_39381695_39392319_-_2.R 

fitVsDatCorrelation=0.828510604178807
cont.fitVsDatCorrelation=0.265498882523782

fstatistic=8208.66346817743,61,899
cont.fstatistic=2759.42548138581,61,899

residuals=-0.66191705385205,-0.100028314685090,-0.00442512700718825,0.0882109823906626,1.35049628962374
cont.residuals=-0.689528710106336,-0.198167896872259,-0.0571401030776343,0.139134761115502,1.75669538708556

predictedValues:
Include	Exclude	Both
chr1.1141_chr1_39381695_39392319_-_2.R.tl.Lung	64.5403642354987	60.4503499586058	62.1861511510577
chr1.1141_chr1_39381695_39392319_-_2.R.tl.cerebhem	78.1383346414302	115.020133061560	89.835023462645
chr1.1141_chr1_39381695_39392319_-_2.R.tl.cortex	61.5331067617978	77.3172828916834	85.5395744626514
chr1.1141_chr1_39381695_39392319_-_2.R.tl.heart	64.9233435989504	59.5568318079992	57.9911631903339
chr1.1141_chr1_39381695_39392319_-_2.R.tl.kidney	64.3718068269454	63.635058425751	62.5542156714149
chr1.1141_chr1_39381695_39392319_-_2.R.tl.liver	68.1652756351779	64.1543685874841	60.0536167605597
chr1.1141_chr1_39381695_39392319_-_2.R.tl.stomach	66.5831674890618	62.6627338076743	68.3389091668602
chr1.1141_chr1_39381695_39392319_-_2.R.tl.testicle	67.8555184358714	61.4470935962132	61.6588691132171


diffExp=4.09001427689292,-36.8817984201302,-15.7841761298856,5.36651179095123,0.736748401194426,4.01090704769382,3.92043368138744,6.40842483965825
diffExpScore=2.64988803497861
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,-1,0,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,-1,0,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,-1,-1,0,0,0,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	61.4846827003227	54.0655729828943	62.892469571279
cerebhem	61.6448223234175	54.0909632549197	57.8359073266427
cortex	61.1688946333614	57.2928341987364	61.5624991041659
heart	65.2039476070118	56.9987654416646	60.4218713393713
kidney	61.4207573221113	63.7611479718541	62.6404720892664
liver	67.0261413714897	53.1771483760339	64.594124054742
stomach	60.5987144645681	52.3299700454287	62.3777585645793
testicle	59.0040339191118	70.1304561552977	57.093439618371
cont.diffExp=7.41910971742836,7.55385906849779,3.87606043462493,8.20518216534715,-2.34039064974286,13.8489929954558,8.2687444191394,-11.1264222361860
cont.diffExpScore=1.70653942903852

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=0,0,0,0,0,1,0,0
cont.diffExp1.2Score=0.5

tran.correlation=0.780913076862167
cont.tran.correlation=-0.485441975905334

tran.covariance=0.0113644565581035
cont.tran.covariance=-0.00203681388952235

tran.mean=68.7721731101066
cont.tran.mean=59.962428298014

weightedLogRatios:
wLogRatio
Lung	0.270683069400091
cerebhem	-1.75984374843454
cortex	-0.966742810854295
heart	0.356326800589694
kidney	0.0478741761553419
liver	0.254192417160495
stomach	0.252941263796933
testicle	0.41346105280634

cont.weightedLogRatios:
wLogRatio
Lung	0.521369091446789
cerebhem	0.53021255058415
cortex	0.267149424130381
heart	0.552792522086082
kidney	-0.154687333845657
liver	0.946497541515856
stomach	0.59135404145673
testicle	-0.719333439904007

varWeightedLogRatios=0.624827034264653
cont.varWeightedLogRatios=0.273331813280450

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.78075701115293	0.082946134579013	57.636887305446	3.69061695980995e-304	***
df.mm.trans1	-0.273062530344695	0.0713486389003501	-3.82715822688742	0.000138603445740317	***
df.mm.trans2	-0.698443687118828	0.0627599342779456	-11.1288148267591	4.83477691562591e-27	***
df.mm.exp2	0.466632172695574	0.0801079075569406	5.82504507890052	7.94706090618959e-09	***
df.mm.exp3	-0.120467135914591	0.0801079075569406	-1.50381079207397	0.132981297433426	   
df.mm.exp4	0.0608667458704037	0.0801079075569406	0.759809458599823	0.447567685485868	   
df.mm.exp5	0.0428258033926367	0.0801079075569406	0.534601448205299	0.593057668109283	   
df.mm.exp6	0.14900882093872	0.0801079075569406	1.86010127443167	0.0631976030038812	.  
df.mm.exp7	-0.0272414374912623	0.0801079075569406	-0.340059281562174	0.733891321801154	   
df.mm.exp8	0.0749593003050498	0.0801079075569406	0.935729100797806	0.349663965400573	   
df.mm.trans1:exp2	-0.275442225963461	0.073688557396166	-3.73792398299539	0.000197269690669644	***
df.mm.trans2:exp2	0.176652644176927	0.0528892666401476	3.34004714754036	0.000872117849164735	***
df.mm.trans1:exp3	0.0727516570441585	0.073688557396166	0.987285673853398	0.323768250421685	   
df.mm.trans2:exp3	0.366562282288825	0.0528892666401477	6.93074995315915	7.9824646931002e-12	***
df.mm.trans1:exp4	-0.0549503313476499	0.073688557396166	-0.745710504986883	0.456037240479621	   
df.mm.trans2:exp4	-0.0757580990217968	0.0528892666401476	-1.43239080128008	0.152379616638707	   
df.mm.trans1:exp5	-0.0454408784972187	0.073688557396166	-0.616661257906278	0.537614305284022	   
df.mm.trans2:exp5	0.00851638192127992	0.0528892666401477	0.161022877840685	0.872111558900765	   
df.mm.trans1:exp6	-0.0943643708320967	0.073688557396166	-1.28058377265785	0.200670187324898	   
df.mm.trans2:exp6	-0.0895389988929673	0.0528892666401477	-1.69295217311634	0.0908110300334402	.  
df.mm.trans1:exp7	0.058402412518887	0.073688557396166	0.792557414374429	0.428244823254629	   
df.mm.trans2:exp7	0.0631859850272446	0.0528892666401476	1.19468446135120	0.232525425190606	   
df.mm.trans1:exp8	-0.024869414622053	0.073688557396166	-0.337493574319138	0.735823638388626	   
df.mm.trans2:exp8	-0.0586051287308856	0.0528892666401477	-1.10807225083358	0.268126976254484	   
df.mm.trans1:probe2	-0.655382145304067	0.0521056786306831	-12.5779408795213	1.54954380858601e-33	***
df.mm.trans1:probe3	-0.268163258133896	0.0521056786306831	-5.14652654338495	3.25939499868422e-07	***
df.mm.trans1:probe4	-0.579959461903884	0.0521056786306831	-11.1304463763834	4.75762626589251e-27	***
df.mm.trans1:probe5	-0.630954190203661	0.0521056786306831	-12.1091252774149	2.25420309434374e-31	***
df.mm.trans1:probe6	-0.405979273281336	0.0521056786306831	-7.79145927949339	1.82477290365574e-14	***
df.mm.trans1:probe7	-0.789166689394913	0.0521056786306831	-15.1455025658221	2.53642994596877e-46	***
df.mm.trans1:probe8	-0.731412918001067	0.0521056786306831	-14.0371056902494	1.28338216369259e-40	***
df.mm.trans1:probe9	-0.0462146576523628	0.0521056786306831	-0.88694090292778	0.375347924391912	   
df.mm.trans1:probe10	-0.536512392440956	0.0521056786306831	-10.2966203788204	1.40188546234996e-23	***
df.mm.trans1:probe11	-0.59824432839617	0.0521056786306831	-11.4813652584094	1.43640137609407e-28	***
df.mm.trans1:probe12	-0.595955642741227	0.0521056786306831	-11.4374413385011	2.23584262216615e-28	***
df.mm.trans1:probe13	-0.62016529702608	0.0521056786306831	-11.9020673624024	1.94877182717682e-30	***
df.mm.trans1:probe14	-0.672357960882832	0.0521056786306831	-12.9037367625206	4.50779797013058e-35	***
df.mm.trans1:probe15	-0.633961086731834	0.0521056786306831	-12.1668329324573	1.22991963127352e-31	***
df.mm.trans1:probe16	-0.542852458703029	0.0521056786306831	-10.4182974479746	4.50059277009386e-24	***
df.mm.trans1:probe17	-0.506891670101219	0.0521056786306831	-9.72814640212227	2.46716043534497e-21	***
df.mm.trans1:probe18	-0.494311055087147	0.0521056786306831	-9.48670218059622	2.06762350351951e-20	***
df.mm.trans1:probe19	-0.489229651418187	0.0521056786306831	-9.38918106960606	4.8211131476964e-20	***
df.mm.trans1:probe20	-0.558682907915653	0.0521056786306831	-10.7221117275050	2.52285599739562e-25	***
df.mm.trans1:probe21	-0.563054745468747	0.0521056786306831	-10.8060150115228	1.12590382236571e-25	***
df.mm.trans1:probe22	-0.65427233091173	0.0521056786306831	-12.5566415812201	1.94849553141314e-33	***
df.mm.trans2:probe2	0.300081263474158	0.0521056786306831	5.75908943823738	1.16052979578144e-08	***
df.mm.trans2:probe3	0.0508305631859262	0.0521056786306831	0.975528282554485	0.329560698509932	   
df.mm.trans2:probe4	-0.0632048813103017	0.0521056786306831	-1.21301330241350	0.225443366011527	   
df.mm.trans2:probe5	0.0605283155685122	0.0521056786306831	1.16164527857947	0.245687902261539	   
df.mm.trans2:probe6	0.00292749929704914	0.0521056786306831	0.056183881948814	0.955207805251622	   
df.mm.trans3:probe2	0.306551572427627	0.0521056786306831	5.88326609466919	5.67126794990613e-09	***
df.mm.trans3:probe3	0.525463735554909	0.0521056786306831	10.0845771394575	9.90614947421193e-23	***
df.mm.trans3:probe4	0.111744372518358	0.0521056786306831	2.14457186730807	0.0322545831794215	*  
df.mm.trans3:probe5	0.179349248517496	0.0521056786306831	3.4420288389044	0.000603990855536983	***
df.mm.trans3:probe6	0.0112025269792121	0.0521056786306831	0.214996278210170	0.829818981646569	   
df.mm.trans3:probe7	0.541293279046772	0.0521056786306831	10.3883740366069	5.9570686819157e-24	***
df.mm.trans3:probe8	0.279527586065766	0.0521056786306831	5.36462806764333	1.03228424437704e-07	***
df.mm.trans3:probe9	0.857107212744652	0.0521056786306831	16.4494012028841	2.37835656693869e-53	***
df.mm.trans3:probe10	0.453254508375609	0.0521056786306831	8.69875453668316	1.57828832177759e-17	***
df.mm.trans3:probe11	0.285954222743371	0.0521056786306831	5.487966575969	5.28903516098909e-08	***
df.mm.trans3:probe12	0.299130106557353	0.0521056786306831	5.74083505710654	1.28789574217790e-08	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.99948630130512	0.142809102129432	28.0058220496357	1.38860250576938e-124	***
df.mm.trans1	0.154364757978452	0.122841590041908	1.25661641082461	0.209218981049947	   
df.mm.trans2	-0.0490804482390359	0.108054340439432	-0.454220052979244	0.649780092746493	   
df.mm.exp2	0.086887287847765	0.137922501268297	0.629971810609391	0.528873106128742	   
df.mm.exp3	0.0742021860978189	0.137922501268297	0.537999132958555	0.590710807505639	   
df.mm.exp4	0.151639203743342	0.137922501268297	1.09945224563730	0.271865185298474	   
df.mm.exp5	0.167921025358425	0.137922501268297	1.21750275563646	0.223732463527976	   
df.mm.exp6	0.0430287570409408	0.137922501268297	0.311977789303851	0.755129743520595	   
df.mm.exp7	-0.0389251217114980	0.137922501268297	-0.282224592459921	0.77783626125721	   
df.mm.exp8	0.315714492323070	0.137922501268297	2.28907168460438	0.0223062933984137	*  
df.mm.trans1:exp2	-0.0842861287940286	0.126870248654387	-0.664349047061747	0.506637293513443	   
df.mm.trans2:exp2	-0.086417778128333	0.0910599236419956	-0.949020981700871	0.342864980785293	   
df.mm.trans1:exp3	-0.0793514654191048	0.126870248654387	-0.62545369194688	0.531832066980634	   
df.mm.trans2:exp3	-0.0162242521899384	0.0910599236419956	-0.178171159617094	0.858628698376217	   
df.mm.trans1:exp4	-0.0929072725318274	0.126870248654387	-0.73230149319657	0.464175436174065	   
df.mm.trans2:exp4	-0.0988072194402966	0.0910599236419956	-1.08507909394653	0.278177512768288	   
df.mm.trans1:exp5	-0.168961262209847	0.126870248654387	-1.33176425522837	0.183275214780248	   
df.mm.trans2:exp5	-0.00297461083994276	0.0910599236419956	-0.0326665202536027	0.973947773540471	   
df.mm.trans1:exp6	0.0432658739692744	0.126870248654387	0.341024585575906	0.733164756430779	   
df.mm.trans2:exp6	-0.0595976191555063	0.0910599236419956	-0.654487910508424	0.512964913145118	   
df.mm.trans1:exp7	0.0244107190977227	0.126870248654387	0.192406961889238	0.847466893261381	   
df.mm.trans2:exp7	0.00629674529986447	0.0910599236419956	0.0691494682624629	0.944886022617847	   
df.mm.trans1:exp8	-0.35689676125227	0.126870248654387	-2.81308474632622	0.00501383339803568	** 
df.mm.trans2:exp8	-0.0555549497495802	0.0910599236419956	-0.610092206622047	0.541954909243177	   
df.mm.trans1:probe2	-0.044631969740311	0.0897108131543402	-0.49750936560485	0.61895155948769	   
df.mm.trans1:probe3	-0.0368442174338599	0.0897108131543402	-0.410699849197358	0.68139050577714	   
df.mm.trans1:probe4	-0.0912613115397358	0.0897108131543402	-1.01728329429729	0.309292370605667	   
df.mm.trans1:probe5	-0.0346525041203058	0.0897108131543402	-0.386268978085049	0.699388871587257	   
df.mm.trans1:probe6	0.00883469459125933	0.0897108131543402	0.0984797069675419	0.92157333801755	   
df.mm.trans1:probe7	-0.056214530948097	0.0897108131543402	-0.626619344664555	0.5310678659219	   
df.mm.trans1:probe8	-0.0453726131014437	0.0897108131543402	-0.505765264031035	0.613145430895251	   
df.mm.trans1:probe9	-0.0163129602875146	0.0897108131543402	-0.181839398328153	0.855749756074918	   
df.mm.trans1:probe10	-0.0594558805811953	0.0897108131543402	-0.662750436548894	0.507660278963897	   
df.mm.trans1:probe11	-0.0784169954584761	0.0897108131543402	-0.87410862415845	0.382292542025745	   
df.mm.trans1:probe12	-0.163755567092065	0.0897108131543402	-1.82537156151217	0.0682766357296288	.  
df.mm.trans1:probe13	-0.20990025430133	0.0897108131543402	-2.33974308024846	0.0195150404569015	*  
df.mm.trans1:probe14	-0.164786529901218	0.0897108131543402	-1.83686363000318	0.0665600075246662	.  
df.mm.trans1:probe15	0.0778738483829066	0.0897108131543402	0.868054202662626	0.385596317155622	   
df.mm.trans1:probe16	0.0174484671005617	0.0897108131543402	0.194496811332465	0.845830834473258	   
df.mm.trans1:probe17	-0.0561344279715081	0.0897108131543402	-0.625726442529657	0.531653201893877	   
df.mm.trans1:probe18	0.0301466183421179	0.0897108131543402	0.336042192486352	0.736917463438515	   
df.mm.trans1:probe19	-0.0751027360414706	0.0897108131543402	-0.837164812142126	0.402722420241067	   
df.mm.trans1:probe20	0.0404893756287115	0.0897108131543402	0.451332166157638	0.651859015582449	   
df.mm.trans1:probe21	-0.189907626868377	0.0897108131543402	-2.11688669616289	0.0345436177506304	*  
df.mm.trans1:probe22	-0.0441841060260987	0.0897108131543402	-0.492517060904169	0.622474122426552	   
df.mm.trans2:probe2	0.181005755106975	0.0897108131543402	2.01765817009783	0.04392357006987	*  
df.mm.trans2:probe3	0.176869518427971	0.0897108131543402	1.97155183649580	0.0489670668764372	*  
df.mm.trans2:probe4	0.0792596013711837	0.0897108131543402	0.88350109183409	0.377201791762202	   
df.mm.trans2:probe5	0.191374438316232	0.0897108131543402	2.13323713816959	0.0331755119124877	*  
df.mm.trans2:probe6	0.0877425704061372	0.0897108131543402	0.978060139251923	0.328307696110723	   
df.mm.trans3:probe2	0.0434277872497115	0.0897108131543402	0.484086429748413	0.628442432749363	   
df.mm.trans3:probe3	-0.0179365375032955	0.0897108131543402	-0.199937297106394	0.8415748366799	   
df.mm.trans3:probe4	0.0457022339009650	0.0897108131543402	0.509439523442264	0.610569201604164	   
df.mm.trans3:probe5	0.0566447558525875	0.0897108131543402	0.631415030818355	0.527929698582687	   
df.mm.trans3:probe6	-0.0151441893791536	0.0897108131543402	-0.168811192839143	0.865983127072868	   
df.mm.trans3:probe7	0.0324709429346501	0.0897108131543402	0.361951272014294	0.717473503447466	   
df.mm.trans3:probe8	-0.0141955657314998	0.0897108131543402	-0.158236953075852	0.87430562232405	   
df.mm.trans3:probe9	0.0988978115780551	0.0897108131543402	1.10240681252002	0.270579882543061	   
df.mm.trans3:probe10	0.0899206676259596	0.0897108131543402	1.00233923274398	0.316449489390928	   
df.mm.trans3:probe11	0.0877448634059625	0.0897108131543402	0.978085699156517	0.328295062450748	   
df.mm.trans3:probe12	0.0323371282345319	0.0897108131543402	0.360459649149523	0.718588100175562