chr6.19900_chr6_48270884_48273611_+_1.R 

fitVsDatCorrelation=0.905996664276561
cont.fitVsDatCorrelation=0.264497205672113

fstatistic=6898.4206926711,60,876
cont.fstatistic=1317.17560988077,60,876

residuals=-0.994640288704002,-0.112718538858942,-0.00803314472544034,0.104275104815756,1.30886957852430
cont.residuals=-0.847351575074942,-0.379759406391763,-0.0846989973759451,0.319089933433455,1.73316811607572

predictedValues:
Include	Exclude	Both
chr6.19900_chr6_48270884_48273611_+_1.R.tl.Lung	61.7870815209563	96.707584371314	77.4236599306677
chr6.19900_chr6_48270884_48273611_+_1.R.tl.cerebhem	46.004181484688	52.3342234610855	88.7231991131343
chr6.19900_chr6_48270884_48273611_+_1.R.tl.cortex	51.9494369557555	67.6941361721315	68.3557583113857
chr6.19900_chr6_48270884_48273611_+_1.R.tl.heart	65.0260436330746	94.7436508317423	67.9194816001563
chr6.19900_chr6_48270884_48273611_+_1.R.tl.kidney	62.50797624211	95.1085052546356	74.7854377562912
chr6.19900_chr6_48270884_48273611_+_1.R.tl.liver	66.7095628086589	95.5809258791467	74.056427285593
chr6.19900_chr6_48270884_48273611_+_1.R.tl.stomach	61.6224667628113	80.0269474715117	74.1010333518983
chr6.19900_chr6_48270884_48273611_+_1.R.tl.testicle	62.8741919953722	82.6158043684708	73.7507677525586


diffExp=-34.9205028503576,-6.3300419763975,-15.7446992163759,-29.7176071986677,-32.6005290125256,-28.8713630704879,-18.4044807087004,-19.7416123730986
diffExpScore=0.99466185055711
diffExp1.5=-1,0,0,0,-1,0,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=-1,0,0,-1,-1,-1,0,0
diffExp1.4Score=0.8
diffExp1.3=-1,0,-1,-1,-1,-1,0,-1
diffExp1.3Score=0.857142857142857
diffExp1.2=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	74.5788443404245	83.1470677761775	79.7249312722959
cerebhem	84.7748177928343	71.0458973644202	80.7267957331329
cortex	67.5433095610285	74.3079198473644	83.9877099009056
heart	85.347191065108	73.7412313215666	79.7392154724803
kidney	85.7512606351649	71.098906367246	85.0535488434219
liver	74.230607324977	99.3869450340644	69.7377465079707
stomach	79.0111500211013	68.0958254209502	76.9437726160118
testicle	82.4896413222796	82.9900027906858	81.3725467307948
cont.diffExp=-8.56822343575301,13.7289204284140,-6.76461028633594,11.6059597435414,14.6523542679188,-25.1563377090875,10.9153246001511,-0.500361468406126
cont.diffExpScore=8.4204042725659

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

tran.correlation=0.933423103513127
cont.tran.correlation=-0.378203468267228

tran.covariance=0.0264167322155018
cont.tran.covariance=-0.00386549576200389

tran.mean=71.4557949508416
cont.tran.mean=78.5962886240871

weightedLogRatios:
wLogRatio
Lung	-1.94775573684973
cerebhem	-0.501903350065669
cortex	-1.08079064090575
heart	-1.64216933396381
kidney	-1.82376738411587
liver	-1.57521518178365
stomach	-1.11112477172242
testicle	-1.16808246385463

cont.weightedLogRatios:
wLogRatio
Lung	-0.474845671985557
cerebhem	0.768818752008129
cortex	-0.40665779319575
heart	0.639275749768952
kidney	0.81655223649609
liver	-1.29961103786740
stomach	0.638588373881742
testicle	-0.0267035997039719

varWeightedLogRatios=0.228489504532265
cont.varWeightedLogRatios=0.585880413827591

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.32922492650085	0.0961415956712817	45.0296762423512	3.58188053663037e-230	***
df.mm.trans1	-0.388957257796654	0.0801882694711995	-4.85055059002555	1.45678102466467e-06	***
df.mm.trans2	0.165605558347508	0.0726739110846065	2.27874839644603	0.0229219342684855	*  
df.mm.exp2	-1.0452323007248	0.0926777901730867	-11.2781314570913	1.21745212563034e-27	***
df.mm.exp3	-0.405549085817517	0.0926777901730867	-4.37590370961701	1.35499632793568e-05	***
df.mm.exp4	0.161546064141161	0.0926777901730867	1.74309361325356	0.0816681249686916	.  
df.mm.exp5	0.0295956659113387	0.0926777901730867	0.319339356884376	0.749545327235146	   
df.mm.exp6	0.109400540292327	0.0926777901730867	1.18043967263364	0.238145816686105	   
df.mm.exp7	-0.148133251348752	0.0926777901730868	-1.59836840166448	0.110321620595761	   
df.mm.exp8	-0.0914483489400249	0.0926777901730867	-0.98673424095713	0.324045396383676	   
df.mm.trans1:exp2	0.750270289188955	0.0796161698740846	9.42359184541948	3.76943129308976e-20	***
df.mm.trans2:exp2	0.431190994719192	0.0609362221655851	7.0761031681205	3.03657970221191e-12	***
df.mm.trans1:exp3	0.232125659374085	0.0796161698740846	2.91555923553217	0.00364104500758427	** 
df.mm.trans2:exp3	0.0488568157454767	0.0609362221655851	0.801769686553846	0.422903629507274	   
df.mm.trans1:exp4	-0.110452508949417	0.0796161698740846	-1.38731251608940	0.165699323003755	   
df.mm.trans2:exp4	-0.182063063466958	0.0609362221655851	-2.98776420652118	0.00288865634502267	** 
df.mm.trans1:exp5	-0.0179958031726076	0.0796161698740846	-0.226032013359454	0.82122924782773	   
df.mm.trans2:exp5	-0.0462690968565488	0.0609362221655851	-0.75930366557381	0.447875194263547	   
df.mm.trans1:exp6	-0.0327465329373097	0.0796161698740846	-0.411305052592952	0.680949468384846	   
df.mm.trans2:exp6	-0.121119091586070	0.0609362221655851	-1.98763702903909	0.0471628161223833	*  
df.mm.trans1:exp7	0.145465469834838	0.0796161698740846	1.82708449885112	0.0680271795419288	.  
df.mm.trans2:exp7	-0.0411951586541782	0.0609362221655851	-0.676037292601378	0.499195403209625	   
df.mm.trans1:exp8	0.108889820574457	0.0796161698740846	1.36768473975411	0.171761544776211	   
df.mm.trans2:exp8	-0.0660424840071496	0.0609362221655851	-1.08379682330304	0.278753096969767	   
df.mm.trans1:probe2	-0.129669447790250	0.0604728221159296	-2.14425990474973	0.032286665006565	*  
df.mm.trans1:probe3	-0.0780336265040345	0.0604728221159296	-1.29039167966132	0.197255192109003	   
df.mm.trans1:probe4	-0.0344089586946861	0.0604728221159296	-0.568998725224405	0.569502856537524	   
df.mm.trans1:probe5	-0.043607204760463	0.0604728221159296	-0.721104179276861	0.471037819535455	   
df.mm.trans1:probe6	-0.08794307798929	0.0604728221159296	-1.45425787836887	0.146233010857371	   
df.mm.trans1:probe7	-0.0622346874988674	0.0604728221159296	-1.02913482985068	0.303700386821764	   
df.mm.trans1:probe8	1.26374798899108	0.0604728221159296	20.8977842404710	5.32548824624721e-79	***
df.mm.trans1:probe9	1.35721312260732	0.0604728221159296	22.4433567860529	1.73396732182744e-88	***
df.mm.trans1:probe10	1.06962517724752	0.0604728221159296	17.6877006863843	4.26056610445981e-60	***
df.mm.trans1:probe11	0.627427762417628	0.0604728221159296	10.3753676521796	7.24434820598649e-24	***
df.mm.trans1:probe12	1.12965089582099	0.0604728221159296	18.6803072238863	8.36297211666559e-66	***
df.mm.trans1:probe13	1.04131107815839	0.0604728221159296	17.2194887177936	1.86754793967363e-57	***
df.mm.trans2:probe2	0.153729096673852	0.0604728221159296	2.54211877823636	0.0111894677608931	*  
df.mm.trans2:probe3	0.49588557777786	0.0604728221159296	8.20013950774814	8.50437573029877e-16	***
df.mm.trans2:probe4	0.323668945431541	0.0604728221159295	5.35230429317571	1.10960099822561e-07	***
df.mm.trans2:probe5	0.601868338914281	0.0604728221159296	9.95270797450909	3.50463250082994e-22	***
df.mm.trans2:probe6	0.42324305028957	0.0604728221159296	6.99889695040511	5.12933176978855e-12	***
df.mm.trans3:probe2	0.597838329072405	0.0604728221159296	9.88606630473302	6.38714571890614e-22	***
df.mm.trans3:probe3	-0.103695517787053	0.0604728221159296	-1.71474580082047	0.0867455225466726	.  
df.mm.trans3:probe4	0.367014659327159	0.0604728221159296	6.0690843669173	1.9134172735381e-09	***
df.mm.trans3:probe5	0.402922712887135	0.0604728221159296	6.66287265566524	4.74169214815707e-11	***
df.mm.trans3:probe6	0.0344982701485558	0.0604728221159296	0.570475611050875	0.568501452052258	   
df.mm.trans3:probe7	0.213284818521429	0.0604728221159296	3.5269532834527	0.000442200945706509	***
df.mm.trans3:probe8	0.119740202415478	0.0604728221159296	1.98006638727608	0.0480086267752156	*  
df.mm.trans3:probe9	0.641408202312514	0.0604728221159296	10.6065531567702	8.23989382890103e-25	***
df.mm.trans3:probe10	-0.0846446985310446	0.0604728221159296	-1.39971470768763	0.161952793899318	   
df.mm.trans3:probe11	0.554936282095084	0.0604728221159296	9.17662286425531	3.1215779281743e-19	***
df.mm.trans3:probe12	0.238110337814657	0.0604728221159296	3.93747686122845	8.88790378019076e-05	***
df.mm.trans3:probe13	0.668492592740723	0.0604728221159296	11.0544302275027	1.10302020722185e-26	***
df.mm.trans3:probe14	0.0456102709344941	0.0604728221159296	0.754227590818514	0.450915264921608	   
df.mm.trans3:probe15	0.623177155495335	0.0604728221159296	10.3050781109681	1.39280723148052e-23	***
df.mm.trans3:probe16	0.399549810181552	0.0604728221159296	6.60709714217725	6.79655470098858e-11	***
df.mm.trans3:probe17	0.304486625064491	0.0604728221159296	5.03509865110602	5.79863770803803e-07	***
df.mm.trans3:probe18	-0.00942717979047347	0.0604728221159296	-0.155891183189716	0.876154710919148	   
df.mm.trans3:probe19	-0.0616646798182775	0.0604728221159296	-1.01970898100411	0.308148030922922	   
df.mm.trans3:probe20	-0.0832543792653363	0.0604728221159296	-1.37672389599634	0.168949374394329	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.49142650271142	0.21904317497484	20.5047543856471	1.27225135534581e-76	***
df.mm.trans1	-0.17686955332525	0.182696085061508	-0.968108064634794	0.333257606587333	   
df.mm.trans2	-0.101014055180989	0.165575827098181	-0.610077309902796	0.541968819552268	   
df.mm.exp2	-0.0416313817934079	0.211151450809848	-0.197163607608356	0.843745244729518	   
df.mm.exp3	-0.263569392283097	0.211151450809848	-1.24824807630829	0.212273743947246	   
df.mm.exp4	0.0146426564270785	0.211151450809848	0.0693467005361232	0.94472947980622	   
df.mm.exp5	-0.0816437712006151	0.211151450809848	-0.386659769030615	0.699102006934058	   
df.mm.exp6	0.307570133174101	0.211151450809848	1.45663281968677	0.145576091099250	   
df.mm.exp7	-0.106455505746125	0.211151450809848	-0.504166584401038	0.614271096539742	   
df.mm.exp8	0.078469456616851	0.211151450809848	0.371626414670087	0.71026088769622	   
df.mm.trans1:exp2	0.169773041438667	0.181392648070693	0.935942240462258	0.349560867061557	   
df.mm.trans2:exp2	-0.115653449016225	0.138833389241417	-0.833037712672389	0.405050522232492	   
df.mm.trans1:exp3	0.164481528474729	0.181392648070693	0.90677064491956	0.364777450317918	   
df.mm.trans2:exp3	0.151175990407604	0.138833389241417	1.08890225351139	0.276496462594289	   
df.mm.trans1:exp4	0.120228002432833	0.181392648070693	0.662805266429417	0.507629633913515	   
df.mm.trans2:exp4	-0.134691506360567	0.138833389241417	-0.970166521875746	0.332231283840135	   
df.mm.trans1:exp5	0.221237679362235	0.181392648070693	1.21966177634726	0.222921390503449	   
df.mm.trans2:exp5	-0.0748952144723469	0.138833389241417	-0.539461111491788	0.589705810013245	   
df.mm.trans1:exp6	-0.312250449474419	0.181392648070693	-1.72140631274497	0.0855301756026962	.  
df.mm.trans2:exp6	-0.129160306572470	0.138833389241417	-0.930325963215332	0.352458638531084	   
df.mm.trans1:exp7	0.164187608700427	0.181392648070693	0.905150293833514	0.365634643283935	   
df.mm.trans2:exp7	-0.0932395244475156	0.138833389241417	-0.67159294285744	0.502019935252513	   
df.mm.trans1:exp8	0.0223463900494702	0.181392648070693	0.123193471660226	0.901982153414435	   
df.mm.trans2:exp8	-0.0803602451296036	0.138833389241417	-0.57882506195873	0.56285601141357	   
df.mm.trans1:probe2	-0.0337856064900472	0.137777606700558	-0.245218416106442	0.80634475131871	   
df.mm.trans1:probe3	0.121870855751866	0.137777606700558	0.884547632016407	0.376643375078234	   
df.mm.trans1:probe4	0.0735417072326437	0.137777606700558	0.533771118498793	0.593635310108021	   
df.mm.trans1:probe5	-0.0257267634422232	0.137777606700558	-0.186726740711479	0.851918123448058	   
df.mm.trans1:probe6	-0.0518482195609463	0.137777606700558	-0.376318189890116	0.70677148137607	   
df.mm.trans1:probe7	-0.0600160342539059	0.137777606700558	-0.435600789497984	0.663233708743377	   
df.mm.trans1:probe8	0.186611264857354	0.137777606700558	1.35443828156291	0.175945835662169	   
df.mm.trans1:probe9	-0.172102454817854	0.137777606700558	-1.24913227148659	0.211950375828050	   
df.mm.trans1:probe10	-0.00836255238236027	0.137777606700558	-0.06069602007629	0.95161514565747	   
df.mm.trans1:probe11	-0.0812799207706359	0.137777606700558	-0.589935641336022	0.555385930577377	   
df.mm.trans1:probe12	-0.0130232744598641	0.137777606700558	-0.0945238836102625	0.92471462713668	   
df.mm.trans1:probe13	-0.0249813223918083	0.137777606700558	-0.181316274756477	0.856161275233101	   
df.mm.trans2:probe2	0.285462493475737	0.137777606700558	2.07190776724807	0.0385661813929677	*  
df.mm.trans2:probe3	-0.0145342382980283	0.137777606700558	-0.105490570246416	0.916010702077902	   
df.mm.trans2:probe4	0.233060072004553	0.137777606700558	1.69156713914388	0.0910842016870607	.  
df.mm.trans2:probe5	0.145542574366164	0.137777606700558	1.05635870626264	0.291095596722666	   
df.mm.trans2:probe6	0.135629922157170	0.137777606700558	0.984411947668279	0.325184812815676	   
df.mm.trans3:probe2	0.290837501856253	0.137777606700558	2.11091997328964	0.0350620029775289	*  
df.mm.trans3:probe3	0.143496955604225	0.137777606700558	1.04151145487741	0.297925593095116	   
df.mm.trans3:probe4	0.189594818445677	0.137777606700558	1.37609313288288	0.169144481000086	   
df.mm.trans3:probe5	0.207779988353444	0.137777606700558	1.50808243319996	0.131893979291383	   
df.mm.trans3:probe6	0.357689456320734	0.137777606700558	2.59613637431028	0.009585764145565	** 
df.mm.trans3:probe7	0.035229952854908	0.137777606700558	0.255701588223083	0.798241296489775	   
df.mm.trans3:probe8	0.210197417815184	0.137777606700558	1.52562831398299	0.127463398536459	   
df.mm.trans3:probe9	0.139661830454681	0.137777606700558	1.01367583455139	0.311017351605290	   
df.mm.trans3:probe10	0.133192136770154	0.137777606700558	0.966718322082847	0.333951673795592	   
df.mm.trans3:probe11	0.144843893370811	0.137777606700558	1.05128762822547	0.293416423230252	   
df.mm.trans3:probe12	0.0673254764411835	0.137777606700558	0.488653258344854	0.625209505938855	   
df.mm.trans3:probe13	0.245916860060149	0.137777606700558	1.78488265219048	0.0746263004143221	.  
df.mm.trans3:probe14	0.233231715920039	0.137777606700558	1.69281294330317	0.090846644218017	.  
df.mm.trans3:probe15	0.110184417557011	0.137777606700558	0.799726604313012	0.424086016653301	   
df.mm.trans3:probe16	0.310983638208205	0.137777606700558	2.25714211224534	0.0242447905716903	*  
df.mm.trans3:probe17	0.042348926636682	0.137777606700558	0.30737162337797	0.75863358209534	   
df.mm.trans3:probe18	0.0236003313403628	0.137777606700558	0.171292940163020	0.864032989883326	   
df.mm.trans3:probe19	0.243206248450933	0.137777606700558	1.76520883382385	0.0778770451760973	.  
df.mm.trans3:probe20	0.171467566158074	0.137777606700558	1.24452420291156	0.213639558165156