chr10.2215_chr10_62513235_62527235_-_2.R 

fitVsDatCorrelation=0.876959570714357
cont.fitVsDatCorrelation=0.249176029535802

fstatistic=8135.97504404317,68,1060
cont.fstatistic=1991.57128120090,68,1060

residuals=-0.929134629769005,-0.107999107510856,-0.000286185305448613,0.097746528173256,1.04737008673208
cont.residuals=-0.698083157867653,-0.261922319059068,-0.0845008363004249,0.177643955784460,1.84530650433294

predictedValues:
Include	Exclude	Both
chr10.2215_chr10_62513235_62527235_-_2.R.tl.Lung	99.0744362181728	54.5203322670979	137.272200226615
chr10.2215_chr10_62513235_62527235_-_2.R.tl.cerebhem	64.175329360951	61.9088269234632	75.543235735614
chr10.2215_chr10_62513235_62527235_-_2.R.tl.cortex	60.9008996240704	50.8502099010942	70.3939447131247
chr10.2215_chr10_62513235_62527235_-_2.R.tl.heart	75.2797928189507	50.5967361999959	97.1181761818966
chr10.2215_chr10_62513235_62527235_-_2.R.tl.kidney	70.0240090814083	52.8332164474197	81.6338735585044
chr10.2215_chr10_62513235_62527235_-_2.R.tl.liver	65.5293997230343	49.0257990367525	77.8979886771636
chr10.2215_chr10_62513235_62527235_-_2.R.tl.stomach	61.7745352662597	55.3757361375012	78.2054625363094
chr10.2215_chr10_62513235_62527235_-_2.R.tl.testicle	63.2236516131406	49.9521790958813	74.8723865540797


diffExp=44.554103951075,2.26650243748781,10.0506897229762,24.6830566189548,17.1907926339886,16.5036006862819,6.3987991287585,13.2714725172592
diffExpScore=0.992642677846371
diffExp1.5=1,0,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=1,0,0,1,0,0,0,0
diffExp1.4Score=0.666666666666667
diffExp1.3=1,0,0,1,1,1,0,0
diffExp1.3Score=0.8
diffExp1.2=1,0,0,1,1,1,0,1
diffExp1.2Score=0.833333333333333

cont.predictedValues:
Include	Exclude	Both
Lung	71.5089082914842	71.8302640809833	73.2664997309161
cerebhem	67.7939435328125	56.0095755611249	72.8345788138556
cortex	68.1152825980639	65.7106997059285	63.5895976988607
heart	66.7443545561253	60.4729103550847	70.0680131583675
kidney	67.802755982463	69.4188789221161	72.5670703419727
liver	68.1722130759937	61.973359691791	68.680626474743
stomach	68.2629763188789	65.0064573246999	66.0334889530328
testicle	68.5812462166897	67.0340167220334	69.8753912807642
cont.diffExp=-0.321355789499108,11.7843679716876,2.40458289213538,6.2714442010406,-1.61612293965307,6.19885338420266,3.25651899417900,1.54722949465628
cont.diffExpScore=1.09418210163195

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

tran.correlation=0.0486474141719091
cont.tran.correlation=0.659523203721633

tran.covariance=0.000628842299936892
cont.tran.covariance=0.00101688454170106

tran.mean=61.5653181071996
cont.tran.mean=66.5273651835171

weightedLogRatios:
wLogRatio
Lung	2.56672136401959
cerebhem	0.148989120873299
cortex	0.724893617708115
heart	1.63799058666639
kidney	1.15721264198703
liver	1.17146719189638
stomach	0.444923878011477
testicle	0.949252012854816

cont.weightedLogRatios:
wLogRatio
Lung	-0.0191553329769250
cerebhem	0.786905323812798
cortex	0.151063444003598
heart	0.409649224360081
kidney	-0.09960381659326
liver	0.397952950841934
stomach	0.205247489022545
testicle	0.0962184606983652

varWeightedLogRatios=0.56372316935036
cont.varWeightedLogRatios=0.0807299542860303

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.69705705432448	0.0890019344727779	41.539064023999	1.27899713489459e-224	***
df.mm.trans1	0.978124357291894	0.0777916758742295	12.573637812782	6.77173049393396e-34	***
df.mm.trans2	0.248109053119303	0.0678030702237184	3.65925985800731	0.000265399648440998	***
df.mm.exp2	0.290097144905939	0.087096149746208	3.33076887728404	0.000895926901472981	***
df.mm.exp3	0.111545617998293	0.087096149746208	1.28071812959963	0.200572838441707	   
df.mm.exp4	-0.00330906497557776	0.0870961497462079	-0.0379932406337151	0.969700225220712	   
df.mm.exp5	0.141254637215709	0.087096149746208	1.62182412916432	0.105138388982625	   
df.mm.exp6	0.0469660976980392	0.0870961497462079	0.539244247132567	0.589831574367031	   
df.mm.exp7	0.105813920050807	0.0870961497462079	1.21490927393624	0.224671247183938	   
df.mm.exp8	0.0694801112804322	0.087096149746208	0.797740330461133	0.425199862230944	   
df.mm.trans1:exp2	-0.724349734535819	0.0825750692882999	-8.77201485604387	6.88706103152822e-18	***
df.mm.trans2:exp2	-0.163008076866198	0.0591147533178762	-2.75748552970624	0.00592486494718345	** 
df.mm.trans1:exp3	-0.598169119844653	0.0825750692882999	-7.24394329911156	8.371116647203e-13	***
df.mm.trans2:exp3	-0.181235068881061	0.0591147533178763	-3.06581790008512	0.00222571962038136	** 
df.mm.trans1:exp4	-0.271350640495751	0.0825750692882999	-3.28610854140935	0.00104911550288243	** 
df.mm.trans2:exp4	-0.0713775640049887	0.0591147533178762	-1.20744078252635	0.227531786057977	   
df.mm.trans1:exp5	-0.488287915700969	0.0825750692882999	-5.91326074454962	4.51934612098005e-09	***
df.mm.trans2:exp5	-0.172688246137888	0.0591147533178762	-2.92123770202162	0.00356034334900503	** 
df.mm.trans1:exp6	-0.46033865363217	0.0825750692882999	-5.57478979551272	3.14329086618882e-08	***
df.mm.trans2:exp6	-0.153193128408819	0.0591147533178762	-2.59145339886741	0.00968850004033157	** 
df.mm.trans1:exp7	-0.578194139816482	0.0825750692882999	-7.00204244210555	4.47149896037892e-12	***
df.mm.trans2:exp7	-0.0902460993116665	0.0591147533178762	-1.52662566020344	0.127152435172383	   
df.mm.trans1:exp8	-0.518673094356035	0.0825750692883	-6.28123111280908	4.89389435655576e-10	***
df.mm.trans2:exp8	-0.156987682811545	0.0591147533178762	-2.65564303326073	0.008034493037695	** 
df.mm.trans1:probe2	0.511452692410367	0.0553930404526181	9.23315796048154	1.39010528429217e-19	***
df.mm.trans1:probe3	-0.454591840961235	0.0553930404526181	-8.20665984836275	6.54552217650478e-16	***
df.mm.trans1:probe4	-0.215167220583983	0.0553930404526181	-3.88437281697927	0.000108949761431907	***
df.mm.trans1:probe5	-0.0708863097757446	0.0553930404526181	-1.27969703768796	0.200931721039754	   
df.mm.trans1:probe6	0.742837848912438	0.0553930404526181	13.4103100830481	5.43291558537486e-38	***
df.mm.trans1:probe7	-0.179797986067326	0.0553930404526181	-3.24585876850578	0.00120762246735480	** 
df.mm.trans1:probe8	-0.247183015456916	0.0553930404526181	-4.46234785881361	8.97268043793165e-06	***
df.mm.trans1:probe9	0.173752621368222	0.0553930404526181	3.13672295198971	0.00175555756560037	** 
df.mm.trans1:probe10	0.137996840069523	0.0553930404526181	2.49123064814546	0.012882202153715	*  
df.mm.trans1:probe11	-0.501332815266778	0.0553930404526181	-9.05046574750859	6.6560489157309e-19	***
df.mm.trans1:probe12	-0.424893497545494	0.0553930404526181	-7.67052131592123	3.86704617891892e-14	***
df.mm.trans1:probe13	-0.358103417528339	0.0553930404526181	-6.46477273322182	1.54493127948998e-10	***
df.mm.trans1:probe14	-0.315088553877316	0.0553930404526181	-5.68823359943267	1.65949889656365e-08	***
df.mm.trans1:probe15	-0.0962351184316075	0.0553930404526181	-1.73731424823891	0.0826221778033334	.  
df.mm.trans1:probe16	-0.259058648796198	0.0553930404526181	-4.6767364036966	3.29078511934706e-06	***
df.mm.trans1:probe17	-0.237605045427648	0.0553930404526181	-4.28943859167452	1.95479964818069e-05	***
df.mm.trans1:probe18	-0.276588560077434	0.0553930404526181	-4.99320055041971	6.9398502861046e-07	***
df.mm.trans1:probe19	-0.373785823542219	0.0553930404526181	-6.7478842195338	2.46411477039136e-11	***
df.mm.trans1:probe20	-0.282756440871019	0.0553930404526181	-5.10454812663482	3.92838668541707e-07	***
df.mm.trans1:probe21	0.0199234472671673	0.0553930404526181	0.359674195609634	0.719162433626877	   
df.mm.trans1:probe22	-0.338103483427596	0.0553930404526181	-6.10371773538593	1.45150801900251e-09	***
df.mm.trans1:probe23	-0.275442926426610	0.0553930404526181	-4.97251864450766	7.70408593327895e-07	***
df.mm.trans1:probe24	-0.109588651081381	0.0553930404526181	-1.97838302764985	0.0481440833480007	*  
df.mm.trans1:probe25	-0.407617312078109	0.0553930404526181	-7.35863763294914	3.71750959827057e-13	***
df.mm.trans1:probe26	0.7399245792557	0.0553930404526181	13.3577173812767	9.9536397356924e-38	***
df.mm.trans1:probe27	0.186374812701410	0.0553930404526181	3.36458896602418	0.000794032233743296	***
df.mm.trans1:probe28	-0.175321676516786	0.0553930404526181	-3.16504880548581	0.0015947517672046	** 
df.mm.trans1:probe29	-0.273860950863097	0.0553930404526181	-4.94395954122344	8.89402406411744e-07	***
df.mm.trans1:probe30	0.0811056569598575	0.0553930404526181	1.46418496434102	0.143439909351599	   
df.mm.trans1:probe31	0.0957426636613832	0.0553930404526181	1.72842405614617	0.0842034322852636	.  
df.mm.trans1:probe32	-0.0678103514560602	0.0553930404526181	-1.22416734849685	0.221161114110561	   
df.mm.trans2:probe2	0.0605420241103426	0.0553930404526181	1.09295362044856	0.274662488759947	   
df.mm.trans2:probe3	0.111675986161313	0.0553930404526181	2.01606528994988	0.0440450487556903	*  
df.mm.trans2:probe4	0.230056382798762	0.0553930404526181	4.15316402419807	3.54272584030367e-05	***
df.mm.trans2:probe5	0.193734704218838	0.0553930404526181	3.49745568460995	0.000489190280576229	***
df.mm.trans2:probe6	0.205104809313172	0.0553930404526181	3.70271802445316	0.000224290259735623	***
df.mm.trans3:probe2	0.161977984087181	0.0553930404526181	2.92415766969378	0.00352738228885037	** 
df.mm.trans3:probe3	-0.0409705762232752	0.0553930404526181	-0.739634002548036	0.459685870110413	   
df.mm.trans3:probe4	0.276604190118335	0.0553930404526181	4.99348271656862	6.92994749418994e-07	***
df.mm.trans3:probe5	0.215609733125631	0.0553930404526181	3.89236141153975	0.000105471941426341	***
df.mm.trans3:probe6	0.335385117511106	0.0553930404526181	6.05464359368368	1.95091128036461e-09	***
df.mm.trans3:probe7	-0.338704405407313	0.0553930404526181	-6.1145660653351	1.35927583565650e-09	***
df.mm.trans3:probe8	-0.438414616547292	0.0553930404526181	-7.91461549979914	6.21748421073782e-15	***
df.mm.trans3:probe9	-0.183409250935297	0.0553930404526181	-3.31105224477037	0.000960800428213522	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.17943512234822	0.179361387103320	23.3017551316142	2.65984574645277e-97	***
df.mm.trans1	0.0698500118072139	0.156769883402492	0.445557592384504	0.65600783124813	   
df.mm.trans2	0.0350469036092173	0.136640319081037	0.256490206147954	0.797622112905382	   
df.mm.exp2	-0.2962197464775	0.175520749322773	-1.68766227138632	0.091770260808978	.  
df.mm.exp3	0.00398902136893503	0.175520749322773	0.0227267795079854	0.981872491723526	   
df.mm.exp4	-0.1964256182324	0.175520749322773	-1.11910198076459	0.263350162779035	   
df.mm.exp5	-0.077773989600079	0.175520749322773	-0.443104247789286	0.65778074773187	   
df.mm.exp6	-0.130749949547050	0.175520749322773	-0.74492588512489	0.456481651296783	   
df.mm.exp7	-0.0423323192415812	0.175520749322773	-0.241181281443452	0.809461261149028	   
df.mm.exp8	-0.0635186609242842	0.175520749322773	-0.361886906074433	0.717508672543514	   
df.mm.trans1:exp2	0.242870575580858	0.166409629806779	1.45947428560990	0.144730889216668	   
df.mm.trans2:exp2	0.0474365222061539	0.119131165138976	0.398187343763618	0.690572278910788	   
df.mm.trans1:exp3	-0.0526094527504296	0.166409629806779	-0.316144280901984	0.751955238132644	   
df.mm.trans2:exp3	-0.0930331446744254	0.119131165138976	-0.780930368354029	0.435017815096211	   
df.mm.trans1:exp4	0.127473302569437	0.166409629806779	0.766021189503569	0.443834236178153	   
df.mm.trans2:exp4	0.024315227715713	0.119131165138976	0.204104674770429	0.838310880326785	   
df.mm.trans1:exp5	0.0245547990008094	0.166409629806779	0.147556358543195	0.88272096003361	   
df.mm.trans2:exp5	0.0436269581453244	0.119131165138976	0.366209447330008	0.714281870073318	   
df.mm.trans1:exp6	0.0829649650414346	0.166409629806779	0.498558677990971	0.618193755701301	   
df.mm.trans2:exp6	-0.0168513326902018	0.119131165138976	-0.141451925451609	0.88753981359781	   
df.mm.trans1:exp7	-0.00412216897965197	0.166409629806779	-0.0247712165722518	0.980242112193618	   
df.mm.trans2:exp7	-0.0574869648920408	0.119131165138976	-0.482551856392721	0.629513603144812	   
df.mm.trans1:exp8	0.0217157460875042	0.166409629806779	0.130495729800726	0.89619899258315	   
df.mm.trans2:exp8	-0.00558702880980603	0.119131165138976	-0.0468981294969146	0.962603252850493	   
df.mm.trans1:probe2	0.120740655226448	0.11163097330756	1.08160532555592	0.279673937322326	   
df.mm.trans1:probe3	0.118325850103344	0.11163097330756	1.05997329054311	0.289398213231001	   
df.mm.trans1:probe4	0.0538958478064252	0.11163097330756	0.482803707694405	0.629334810695317	   
df.mm.trans1:probe5	-0.072244360795219	0.11163097330756	-0.647171288170846	0.517661212270888	   
df.mm.trans1:probe6	0.0946692740214478	0.11163097330756	0.848055617687931	0.396598450162559	   
df.mm.trans1:probe7	0.193190396457119	0.11163097330756	1.73061642958940	0.0838112250396124	.  
df.mm.trans1:probe8	-0.147674713807873	0.11163097330756	-1.32288297264064	0.186159606200236	   
df.mm.trans1:probe9	-0.0525952715087125	0.11163097330756	-0.471153031728968	0.637628404201895	   
df.mm.trans1:probe10	0.123199798626133	0.11163097330756	1.10363454671939	0.270002175600173	   
df.mm.trans1:probe11	-0.211383793744838	0.11163097330756	-1.89359447007995	0.0585509673988248	.  
df.mm.trans1:probe12	0.0736210166854883	0.11163097330756	0.659503491765242	0.5097157580072	   
df.mm.trans1:probe13	-0.0517649473053425	0.11163097330756	-0.463714915059661	0.642947214355601	   
df.mm.trans1:probe14	0.0468359902703262	0.11163097330756	0.41956088783071	0.67489128250635	   
df.mm.trans1:probe15	0.129272881148288	0.11163097330756	1.15803774990049	0.247109482433696	   
df.mm.trans1:probe16	-0.100766345481163	0.11163097330756	-0.902673715865013	0.366904162853977	   
df.mm.trans1:probe17	0.000745926686493646	0.11163097330756	0.00668207634845668	0.994669771435	   
df.mm.trans1:probe18	0.0682341901441916	0.11163097330756	0.611247829544549	0.541166579463014	   
df.mm.trans1:probe19	-0.0096196010447331	0.11163097330756	-0.0861732255816641	0.93134498845623	   
df.mm.trans1:probe20	0.0103093284364390	0.11163097330756	0.0923518637433651	0.926435933453237	   
df.mm.trans1:probe21	0.087036038731639	0.11163097330756	0.779676429872574	0.435755399861587	   
df.mm.trans1:probe22	0.115114736406477	0.11163097330756	1.03120785383927	0.302678584281142	   
df.mm.trans1:probe23	0.103326715879515	0.11163097330756	0.925609737315778	0.354859508515376	   
df.mm.trans1:probe24	0.092160803960465	0.11163097330756	0.825584523988231	0.409225581289882	   
df.mm.trans1:probe25	-0.0507791414476336	0.11163097330756	-0.454883980163189	0.649285853669489	   
df.mm.trans1:probe26	0.145685597691440	0.11163097330756	1.30506429689594	0.192154180172718	   
df.mm.trans1:probe27	0.113041689706407	0.11163097330756	1.01263732060241	0.31146451230654	   
df.mm.trans1:probe28	-0.0071733158160817	0.11163097330756	-0.0642591890363451	0.948775964461275	   
df.mm.trans1:probe29	0.0214109289397935	0.11163097330756	0.191800969797183	0.847934845755156	   
df.mm.trans1:probe30	-0.139887490504665	0.11163097330756	-1.25312434676399	0.210436804143055	   
df.mm.trans1:probe31	-0.0627647242368422	0.11163097330756	-0.562251876671504	0.574063295679374	   
df.mm.trans1:probe32	0.0378489089560045	0.11163097330756	0.339053829188832	0.734636335003037	   
df.mm.trans2:probe2	0.188108043972380	0.11163097330756	1.68508827253628	0.092265887427044	.  
df.mm.trans2:probe3	0.0765401147319919	0.11163097330756	0.68565302679134	0.493081857938309	   
df.mm.trans2:probe4	0.244960395781255	0.11163097330756	2.19437660107425	0.0284247460127643	*  
df.mm.trans2:probe5	0.286695750441509	0.11163097330756	2.5682455500197	0.0103575153963664	*  
df.mm.trans2:probe6	0.101053693990558	0.11163097330756	0.905247808886692	0.365539824525306	   
df.mm.trans3:probe2	0.00866931749924925	0.11163097330756	0.0776605026578419	0.938112769800042	   
df.mm.trans3:probe3	0.0191049835457283	0.11163097330756	0.171144109736383	0.864143116336235	   
df.mm.trans3:probe4	-0.0173240480145558	0.11163097330756	-0.15519033384064	0.876700814026546	   
df.mm.trans3:probe5	-0.0151535672501566	0.11163097330756	-0.135746977753264	0.892047082497661	   
df.mm.trans3:probe6	0.0191062731932257	0.11163097330756	0.171155662511201	0.864134034842396	   
df.mm.trans3:probe7	0.0235198669681935	0.11163097330756	0.210693020685152	0.833167315475347	   
df.mm.trans3:probe8	0.120207229407915	0.11163097330756	1.07682685052585	0.281802637089641	   
df.mm.trans3:probe9	-0.0701871217534801	0.11163097330756	-0.62874236131673	0.52965319858616