chr4.15956_chr4_114890442_114890964_+_2.R 

fitVsDatCorrelation=0.868302975213617
cont.fitVsDatCorrelation=0.266160788438584

fstatistic=13894.0099952156,50,646
cont.fstatistic=3669.76662062087,50,646

residuals=-0.521745280079038,-0.0823397657275121,-0.00502218079826435,0.0768163154169826,0.566282078267096
cont.residuals=-0.46987091436177,-0.165067804458474,-0.0297369392657959,0.109797798014679,1.19529637029342

predictedValues:
Include	Exclude	Both
chr4.15956_chr4_114890442_114890964_+_2.R.tl.Lung	58.8843744235815	47.8445256372033	72.4606670400058
chr4.15956_chr4_114890442_114890964_+_2.R.tl.cerebhem	56.5860182108912	46.6987908994622	59.222273556675
chr4.15956_chr4_114890442_114890964_+_2.R.tl.cortex	54.2031434135774	46.4537156977909	66.5400685709983
chr4.15956_chr4_114890442_114890964_+_2.R.tl.heart	54.1064721446613	45.0749079516393	78.6389713944788
chr4.15956_chr4_114890442_114890964_+_2.R.tl.kidney	59.1964899993705	48.262163064894	75.8883666594267
chr4.15956_chr4_114890442_114890964_+_2.R.tl.liver	58.6568963431023	48.530805961877	75.9741374482049
chr4.15956_chr4_114890442_114890964_+_2.R.tl.stomach	56.3295553105515	45.5211794996183	75.9550065542447
chr4.15956_chr4_114890442_114890964_+_2.R.tl.testicle	57.1976053935979	49.6805584816373	78.1823998281266


diffExp=11.0398487863782,9.88722731142902,7.7494277157864,9.031564193022,10.9343269344765,10.1260903812253,10.8083758109331,7.51704691196053
diffExpScore=0.987194903865983
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=1,1,0,1,1,1,1,0
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	58.8681226017602	59.8539048903911	51.9579184289985
cerebhem	59.7039428000267	59.1727897093582	67.4513303252874
cortex	62.7913970600709	55.2395343338237	62.3922014350001
heart	55.1105655942995	53.9298415097567	55.8255005160472
kidney	56.1679320658869	52.0473680392198	54.3390373474265
liver	56.235795659589	64.2445685648623	61.2954820244497
stomach	55.5492795736365	57.9982938825886	53.6320606377378
testicle	59.3212447519562	53.0579131265884	58.7146948734347
cont.diffExp=-0.985782288630851,0.531153090668511,7.55186272624711,1.18072408454278,4.12056402666700,-8.00877290527335,-2.44901430895217,6.2633316253678
cont.diffExpScore=3.37798586899519

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=0.716270735438898
cont.tran.correlation=-0.0622581369358015

tran.covariance=0.000854133258539838
cont.tran.covariance=-0.000147353610445254

tran.mean=52.076700152091
cont.tran.mean=57.4557808852384

weightedLogRatios:
wLogRatio
Lung	0.824614375966386
cerebhem	0.756602081007071
cortex	0.604107994466084
heart	0.712183742144967
kidney	0.812518956251617
liver	0.753657778142092
stomach	0.836124279402032
testicle	0.560220714340693

cont.weightedLogRatios:
wLogRatio
Lung	-0.0678161637462837
cerebhem	0.0365039911819315
cortex	0.522263052528753
heart	0.0865977103348248
kidney	0.304024188462155
liver	-0.54537326919952
stomach	-0.174247954355453
testicle	0.449366298818990

varWeightedLogRatios=0.0104617220513239
cont.varWeightedLogRatios=0.123090124730981

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	2.87249981077338	0.0686160579575476	41.8633756627432	3.52088616687231e-186	***
df.mm.trans1	1.03832380066258	0.0614839588040385	16.8877186970331	2.8646502554774e-53	***
df.mm.trans2	0.92419723303472	0.0567359084213573	16.2894586294633	3.09245275195305e-50	***
df.mm.exp2	0.137693907420125	0.0777717397538895	1.77048768429073	0.0771174909934244	.  
df.mm.exp3	-0.0270975213264094	0.0777717397538896	-0.348423751508711	0.72763548469851	   
df.mm.exp4	-0.226076436261110	0.0777717397538896	-2.90692270709815	0.00377514993418933	** 
df.mm.exp5	-0.0322418499576854	0.0777717397538896	-0.41457025469297	0.678594155047437	   
df.mm.exp6	-0.0369776410587347	0.0777717397538896	-0.475463724686515	0.634617209496178	   
df.mm.exp7	-0.141232665369211	0.0777717397538895	-1.81598953316649	0.0698353968879257	.  
df.mm.exp8	-0.0674074222739511	0.0777717397538896	-0.866734143883928	0.386409501832989	   
df.mm.trans1:exp2	-0.177507746343305	0.0741524443558779	-2.39382191491082	0.0169580899738283	*  
df.mm.trans2:exp2	-0.161932338492254	0.0649275121682856	-2.49404810202094	0.0128784286152030	*  
df.mm.trans1:exp3	-0.0557393408889885	0.0741524443558779	-0.751685819303273	0.452513784835105	   
df.mm.trans2:exp3	-0.00240272772716712	0.0649275121682856	-0.0370063112989682	0.970491405863596	   
df.mm.trans1:exp4	0.141454482406554	0.0741524443558779	1.90761725571277	0.0568838501986529	.  
df.mm.trans2:exp4	0.166445458624805	0.0649275121682856	2.56355823696733	0.0105857097206975	*  
df.mm.trans1:exp5	0.0375283339989879	0.074152444355878	0.50609705890313	0.612961175978408	   
df.mm.trans2:exp5	0.040933025613293	0.0649275121682856	0.630441922789198	0.528628438648	   
df.mm.trans1:exp6	0.0331070284135776	0.0741524443558779	0.446472516194987	0.65540558426325	   
df.mm.trans2:exp6	0.0512197072279371	0.0649275121682856	0.788875247447965	0.430474336797023	   
df.mm.trans1:exp7	0.0968762583422854	0.0741524443558779	1.30644726797339	0.191865435513617	   
df.mm.trans2:exp7	0.0914536619223707	0.0649275121682855	1.40855022575533	0.159449307929053	   
df.mm.trans1:exp8	0.0383436904953735	0.074152444355878	0.517092738188799	0.605268415929079	   
df.mm.trans2:exp8	0.105064396806840	0.0649275121682855	1.61817992555334	0.106111943413053	   
df.mm.trans1:probe2	0.194619949021618	0.037076222177939	5.24918499213817	2.07527031475485e-07	***
df.mm.trans1:probe3	0.247767297675499	0.037076222177939	6.68264680490898	5.07361984890248e-11	***
df.mm.trans1:probe4	0.252295111760019	0.037076222177939	6.80476858049846	2.31282405279145e-11	***
df.mm.trans1:probe5	-0.062388291889166	0.037076222177939	-1.68270358262898	0.0929156958679722	.  
df.mm.trans1:probe6	0.350363931661304	0.0370762221779390	9.44982824786764	6.12257815863585e-20	***
df.mm.trans1:probe7	-0.0456165030955594	0.0370762221779390	-1.23034388122483	0.219016184347629	   
df.mm.trans1:probe8	-0.00352383226368567	0.037076222177939	-0.0950429158282047	0.924310212428545	   
df.mm.trans1:probe9	0.467989673295784	0.0370762221779390	12.6223667300777	8.36344494346955e-33	***
df.mm.trans1:probe10	0.461931436602769	0.0370762221779390	12.4589672158569	4.39092923627089e-32	***
df.mm.trans1:probe11	0.0551568583997894	0.0370762221779390	1.48766123298853	0.137328195804954	   
df.mm.trans1:probe12	0.260835842563058	0.0370762221779390	7.03512459579175	5.09012605406916e-12	***
df.mm.trans1:probe13	0.122713160854527	0.0370762221779390	3.30975362769142	0.00098570139528514	***
df.mm.trans1:probe14	0.123646611921471	0.0370762221779390	3.33493016974752	0.000902028240886694	***
df.mm.trans1:probe15	0.114387948976894	0.0370762221779390	3.08521047338413	0.00212097823474005	** 
df.mm.trans1:probe16	0.192693113841424	0.0370762221779390	5.19721542601178	2.71682650805444e-07	***
df.mm.trans1:probe17	0.170481662521537	0.037076222177939	4.59814006139429	5.1297639464861e-06	***
df.mm.trans1:probe18	0.388992770161186	0.037076222177939	10.4917045834471	6.9140311335146e-24	***
df.mm.trans1:probe19	0.176960459715353	0.0370762221779390	4.77288270811602	2.24779984706132e-06	***
df.mm.trans1:probe20	0.319992342663055	0.0370762221779390	8.63066202180265	4.73580327125028e-17	***
df.mm.trans2:probe2	0.175620079215367	0.0370762221779390	4.73673068341533	2.67199109066812e-06	***
df.mm.trans2:probe3	0.167065629729469	0.0370762221779390	4.50600465515811	7.84162234420745e-06	***
df.mm.trans2:probe4	0.00831235469486256	0.0370762221779390	0.224196377262206	0.822675390236863	   
df.mm.trans2:probe5	0.103588781550602	0.0370762221779390	2.79394111550663	0.00536138132165044	** 
df.mm.trans2:probe6	0.186750102008829	0.0370762221779390	5.03692369499148	6.14604815562238e-07	***
df.mm.trans3:probe2	-0.724801652530169	0.0370762221779390	-19.5489618400614	3.30881627823003e-67	***
df.mm.trans3:probe3	-0.931129207715855	0.0370762221779390	-25.1139181129920	1.22047662467950e-97	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.25017234106539	0.133339559529469	31.8748041171239	1.10692512787435e-134	***
df.mm.trans1	-0.176503620277655	0.119479961820755	-1.47726545596363	0.140091824970998	   
df.mm.trans2	-0.125173532281069	0.110253215698992	-1.13532772252930	0.256659080483680	   
df.mm.exp2	-0.258318717360773	0.151131525641418	-1.70923118961740	0.0878884077328697	.  
df.mm.exp3	-0.198715593804924	0.151131525641418	-1.31485203342952	0.189026203713962	   
df.mm.exp4	-0.241977618587452	0.151131525641418	-1.60110617265640	0.109842276636375	   
df.mm.exp5	-0.231514946952825	0.151131525641418	-1.53187725704648	0.126042270701859	   
df.mm.exp6	-0.140227742167194	0.151131525641418	-0.927852356231122	0.353830697139589	   
df.mm.exp7	-0.121235170635277	0.151131525641418	-0.802183198513627	0.422741988785484	   
df.mm.exp8	-0.235110792318898	0.151131525641418	-1.55567007823856	0.120276314168433	   
df.mm.trans1:exp2	0.272417047174952	0.144098255754703	1.89049510521963	0.0591390763139213	.  
df.mm.trans2:exp2	0.246873845805399	0.126171717402065	1.95664964295206	0.0508190806530792	.  
df.mm.trans1:exp3	0.263233936450708	0.144098255754703	1.82676698667893	0.0681961070245721	.  
df.mm.trans2:exp3	0.118487817943925	0.126171717402065	0.939099668163714	0.348030563192105	   
df.mm.trans1:exp4	0.176019337481502	0.144098255754703	1.22152302649061	0.222333634723546	   
df.mm.trans2:exp4	0.137754914624482	0.126171717402065	1.09180502144950	0.275325831883116	   
df.mm.trans1:exp5	0.184561205231186	0.144098255754703	1.280801105222	0.200723167125063	   
df.mm.trans2:exp5	0.0917625002323662	0.126171717402065	0.72728264401721	0.467316310706038	   
df.mm.trans1:exp6	0.0944814978003322	0.144098255754703	0.655674125307715	0.512267257031657	   
df.mm.trans2:exp6	0.21101825192	0.126171717402065	1.67246872964056	0.0949161285068545	.  
df.mm.trans1:exp7	0.0632059857102425	0.144098255754703	0.438631164403805	0.661075464766757	   
df.mm.trans2:exp7	0.0897420904378978	0.126171717402065	0.711269468988213	0.477174007670164	   
df.mm.trans1:exp8	0.242778561094329	0.144098255754703	1.68481262887462	0.0925077215132452	.  
df.mm.trans2:exp8	0.114588135316323	0.126171717402065	0.908191928236742	0.364115501256087	   
df.mm.trans1:probe2	-0.0185823239279665	0.0720491278773514	-0.257911850919265	0.796557078451849	   
df.mm.trans1:probe3	-0.0301884684642713	0.0720491278773514	-0.418998388372735	0.675356588967178	   
df.mm.trans1:probe4	-0.0296349577533728	0.0720491278773514	-0.411315981559418	0.680977270162118	   
df.mm.trans1:probe5	0.0282717424506887	0.0720491278773514	0.392395345837016	0.694895554969236	   
df.mm.trans1:probe6	0.0669609367929606	0.0720491278773514	0.929378866416644	0.353039918426491	   
df.mm.trans1:probe7	0.0205633050421852	0.0720491278773514	0.285406716888925	0.775424045721904	   
df.mm.trans1:probe8	-0.0320116479281739	0.0720491278773514	-0.444303059194097	0.656972289706259	   
df.mm.trans1:probe9	0.0301840518962703	0.0720491278773514	0.418937088977015	0.675401366241038	   
df.mm.trans1:probe10	0.00777613298065937	0.0720491278773514	0.107928204126171	0.91408615594344	   
df.mm.trans1:probe11	0.0658183408215676	0.0720491278773514	0.913520298727413	0.361309776441974	   
df.mm.trans1:probe12	0.0248421199889894	0.0720491278773514	0.34479418031649	0.730361332227828	   
df.mm.trans1:probe13	0.0319837719751623	0.0720491278773514	0.443916157175531	0.657251855837447	   
df.mm.trans1:probe14	0.00160898005305590	0.0720491278773514	0.0223317075509206	0.982190252156862	   
df.mm.trans1:probe15	-0.0441653980604353	0.0720491278773514	-0.612990043899181	0.540098663394906	   
df.mm.trans1:probe16	-0.0661931996889564	0.0720491278773514	-0.918723121834819	0.358583309672304	   
df.mm.trans1:probe17	0.0187651880969778	0.0720491278773514	0.260449899253765	0.79459975254898	   
df.mm.trans1:probe18	-0.0722547371981164	0.0720491278773514	-1.00285373781505	0.316306925802668	   
df.mm.trans1:probe19	-0.0132204549874564	0.0720491278773514	-0.183492227830452	0.854469393593	   
df.mm.trans1:probe20	0.0469898747603886	0.0720491278773514	0.65219213812524	0.514509216210546	   
df.mm.trans2:probe2	-0.105777664525332	0.0720491278773514	-1.46813247629307	0.142554965213482	   
df.mm.trans2:probe3	-0.0603700920169912	0.0720491278773514	-0.837901773353297	0.402395770837731	   
df.mm.trans2:probe4	-0.0243491072549215	0.0720491278773514	-0.337951450243377	0.735509567946558	   
df.mm.trans2:probe5	-0.0368170362796356	0.0720491278773514	-0.510999055287788	0.609526307489934	   
df.mm.trans2:probe6	-0.0705153085386421	0.0720491278773514	-0.978711479459956	0.328088929850277	   
df.mm.trans3:probe2	-0.0224631514160513	0.0720491278773514	-0.311775479840507	0.755311755600306	   
df.mm.trans3:probe3	0.0282799758126263	0.0720491278773514	0.392509620113196	0.694811177227117