chr1.657_chr1_60589764_60596342_+_2.R 

fitVsDatCorrelation=0.882868925115495
cont.fitVsDatCorrelation=0.213651319509424

fstatistic=10619.7094342473,68,1060
cont.fstatistic=2442.13384744676,68,1060

residuals=-0.585379447449429,-0.096652930842576,-0.00516733331565519,0.095393870876501,0.839813768656392
cont.residuals=-0.724710020534994,-0.240714844116838,-0.0779318730709914,0.199260413316371,1.30757894395808

predictedValues:
Include	Exclude	Both
chr1.657_chr1_60589764_60596342_+_2.R.tl.Lung	62.3518800519817	123.713826322730	67.1281544642234
chr1.657_chr1_60589764_60596342_+_2.R.tl.cerebhem	61.3685725202579	90.7231491604392	64.4581000851515
chr1.657_chr1_60589764_60596342_+_2.R.tl.cortex	57.256937231514	135.360228444253	70.300963079908
chr1.657_chr1_60589764_60596342_+_2.R.tl.heart	58.7247432475702	82.3174183700594	60.0040073182395
chr1.657_chr1_60589764_60596342_+_2.R.tl.kidney	61.8958908797085	78.5696421317038	58.7709528578047
chr1.657_chr1_60589764_60596342_+_2.R.tl.liver	61.1859968603453	57.9247378348842	56.6111124341076
chr1.657_chr1_60589764_60596342_+_2.R.tl.stomach	62.1105525070024	72.5553952857016	56.2670868638137
chr1.657_chr1_60589764_60596342_+_2.R.tl.testicle	60.0460051996374	76.3195329883881	57.1717102838622


diffExp=-61.361946270748,-29.3545766401813,-78.103291212739,-23.5926751224892,-16.6737512519953,3.26125902546109,-10.4448427786992,-16.2735277887507
diffExpScore=1.02364665062259
diffExp1.5=-1,0,-1,0,0,0,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=-1,-1,-1,-1,0,0,0,0
diffExp1.4Score=0.8
diffExp1.3=-1,-1,-1,-1,0,0,0,0
diffExp1.3Score=0.8
diffExp1.2=-1,-1,-1,-1,-1,0,0,-1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	67.8605450998373	63.6226578017407	68.6364165352023
cerebhem	61.9531664700473	56.5315732327774	63.1302454691619
cortex	65.771553544898	65.8889089977917	65.2243460549385
heart	67.5320698374383	63.7313038082372	66.0779011347863
kidney	70.5388006758512	67.7737753613624	66.9237549899384
liver	65.6732369628471	62.6638905035841	63.1008718574315
stomach	65.6572687726523	66.4994508077592	64.4784086763511
testicle	70.239794659203	68.5168876846948	65.4559349526769
cont.diffExp=4.23788729809668,5.42159323726986,-0.117355452893690,3.80076602920118,2.76502531448888,3.00934645926301,-0.842182035106958,1.72290697450818
cont.diffExpScore=1.04376966896393

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=-0.387274349973816
cont.tran.correlation=0.830748420057021

tran.covariance=-0.00316079575147145
cont.tran.covariance=0.00213847449980906

tran.mean=75.151531814761
cont.tran.mean=65.6534302637951

weightedLogRatios:
wLogRatio
Lung	-3.06643010143814
cerebhem	-1.68576302554108
cortex	-3.85260979540671
heart	-1.43252100175682
kidney	-1.01249974818667
liver	0.223834895103272
stomach	-0.653855667309186
testicle	-1.01083717848595

cont.weightedLogRatios:
wLogRatio
Lung	0.269883956153768
cerebhem	0.373697973736996
cortex	-0.00746430092778125
heart	0.242344524747648
kidney	0.169394221979257
liver	0.195187539358090
stomach	-0.0534135827423421
testicle	0.105286971989713

varWeightedLogRatios=1.73742073012728
cont.varWeightedLogRatios=0.0203433845657382

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.68419393072874	0.0763210447741015	61.3748664551597	0	***
df.mm.trans1	-0.744009848133344	0.0663209380156675	-11.2183251684043	1.11962031425569e-27	***
df.mm.trans2	0.101201469938405	0.0576107841682017	1.75664107683268	0.0792677257287898	.  
df.mm.exp2	-0.28546631881464	0.073370994379685	-3.8907244099404	0.000106175946795169	***
df.mm.exp3	-0.0414584307552656	0.073370994379685	-0.565052049597744	0.572157926193724	   
df.mm.exp4	-0.355128785521362	0.073370994379685	-4.84017953584789	1.48965582135699e-06	***
df.mm.exp5	-0.328369872578252	0.073370994379685	-4.47547256725161	8.44836043715297e-06	***
df.mm.exp6	-0.607303725902189	0.073370994379685	-8.27716362626181	3.76176043956669e-16	***
df.mm.exp7	-0.361004841699638	0.073370994379685	-4.92026644523157	1.00139564177861e-06	***
df.mm.exp8	-0.360180596284488	0.073370994379685	-4.90903250432456	1.05913418557231e-06	***
df.mm.trans1:exp2	0.269570349853626	0.0690395975888732	3.90457591394003	0.000100356556776827	***
df.mm.trans2:exp2	-0.0246921750141570	0.0479491283665579	-0.514966087086966	0.60668408232302	   
df.mm.trans1:exp3	-0.0437865846726459	0.0690395975888732	-0.634224216273572	0.526071348522538	   
df.mm.trans2:exp3	0.131426968117367	0.0479491283665579	2.74096678280872	0.00622886643530273	** 
df.mm.trans1:exp4	0.295196119071349	0.0690395975888732	4.27575086444196	2.07668417494908e-05	***
df.mm.trans2:exp4	-0.0522595305260965	0.0479491283665579	-1.0898953183588	0.276006961491947	   
df.mm.trans1:exp5	0.321029841991091	0.0690395975888732	4.64993790813796	3.73885592480541e-06	***
df.mm.trans2:exp5	-0.125615781188172	0.0479491283665579	-2.61977194304501	0.00892458202452145	** 
df.mm.trans1:exp6	0.588428254897273	0.0690395975888732	8.523054528813	5.28159543338034e-17	***
df.mm.trans2:exp6	-0.151522775903889	0.0479491283665579	-3.1600736252292	0.00162197449992206	** 
df.mm.trans1:exp7	0.357126918981163	0.0690395975888732	5.17278390160721	2.75662898297241e-07	***
df.mm.trans2:exp7	-0.172615861462163	0.0479491283665579	-3.59997913085223	0.000332965884448382	***
df.mm.trans1:exp8	0.322497793157888	0.0690395975888732	4.67120036067336	3.37889934865225e-06	***
df.mm.trans2:exp8	-0.122861541892658	0.0479491283665579	-2.56233108041955	0.0105344646350380	*  
df.mm.trans1:probe2	0.134018750992165	0.048095092565285	2.78653691767503	0.00542253819907658	** 
df.mm.trans1:probe3	1.08083408122682	0.048095092565285	22.4728558274355	8.89485958277169e-92	***
df.mm.trans1:probe4	0.254353238315391	0.048095092565285	5.2885486803072	1.49709143816199e-07	***
df.mm.trans1:probe5	0.133557360393341	0.048095092565285	2.77694361877042	0.00558398827865565	** 
df.mm.trans1:probe6	0.311518673035594	0.048095092565285	6.47714052348966	1.42793956866755e-10	***
df.mm.trans1:probe7	0.0713773043926079	0.048095092565285	1.48408705723394	0.138083109218994	   
df.mm.trans1:probe8	0.643013466622862	0.048095092565285	13.3696273845408	8.67957721747711e-38	***
df.mm.trans1:probe9	0.170333718827627	0.048095092565285	3.54160289007477	0.00041499351791935	***
df.mm.trans1:probe10	0.138411197337626	0.048095092565285	2.87786528635421	0.00408411643340718	** 
df.mm.trans1:probe11	0.7297411485348	0.048095092565285	15.1728816727869	3.33080212410340e-47	***
df.mm.trans1:probe12	0.542629835390082	0.048095092565285	11.2824366572017	5.84876668962234e-28	***
df.mm.trans1:probe13	0.281812755617878	0.048095092565285	5.85949086666881	6.19189008705659e-09	***
df.mm.trans1:probe14	0.380619931536829	0.048095092565285	7.91390371107342	6.25115718731869e-15	***
df.mm.trans1:probe15	0.447720561089385	0.048095092565285	9.30906953722237	7.19635592174574e-20	***
df.mm.trans1:probe16	0.463882987679695	0.048095092565285	9.64512100792847	3.69973274085819e-21	***
df.mm.trans1:probe17	0.100749945551505	0.048095092565285	2.09480718671547	0.0364250388084025	*  
df.mm.trans1:probe18	-0.0270167867939975	0.048095092565285	-0.561736870707223	0.574414057352416	   
df.mm.trans1:probe19	-0.0942824562428057	0.048095092565285	-1.96033422983489	0.0502183692890764	.  
df.mm.trans1:probe20	-0.0633757925451079	0.048095092565285	-1.31771848570788	0.187882622969847	   
df.mm.trans1:probe21	-0.070361602014348	0.048095092565285	-1.46296842903126	0.143772455290933	   
df.mm.trans1:probe22	0.00626151111700235	0.048095092565285	0.130190229044738	0.896440626165277	   
df.mm.trans1:probe23	0.150118167773677	0.048095092565285	3.12127827948152	0.00184940104160567	** 
df.mm.trans1:probe24	0.951698031189642	0.048095092565285	19.7878407219571	2.05296661754231e-74	***
df.mm.trans1:probe25	0.0526833196467128	0.048095092565285	1.09539906956619	0.27359066237603	   
df.mm.trans1:probe26	0.059008246139847	0.048095092565285	1.22690784012419	0.220129667121186	   
df.mm.trans1:probe27	0.163487328257507	0.048095092565285	3.39925176431642	0.00070085705490845	***
df.mm.trans1:probe28	0.610697854057008	0.048095092565285	12.6977165753042	1.71903326071196e-34	***
df.mm.trans1:probe29	0.0969126658118318	0.048095092565285	2.01502192100537	0.0441544415292433	*  
df.mm.trans1:probe30	0.176593990351796	0.048095092565285	3.67176734532915	0.000252895476200405	***
df.mm.trans2:probe2	0.215962636481095	0.048095092565285	4.49032583080995	7.89036360045301e-06	***
df.mm.trans2:probe3	-0.0586996166016025	0.048095092565285	-1.22049077090189	0.222550320942641	   
df.mm.trans2:probe4	0.191453298778766	0.048095092565285	3.980724197981	7.33860424273947e-05	***
df.mm.trans2:probe5	0.0506418699827637	0.048095092565285	1.05295295801794	0.29260251388282	   
df.mm.trans2:probe6	0.15442778496806	0.048095092565285	3.2108844526796	0.00136305054929279	** 
df.mm.trans3:probe2	0.0383265981115934	0.048095092565285	0.79689207499847	0.425692164831123	   
df.mm.trans3:probe3	-0.0483019915500743	0.048095092565285	-1.00430187309669	0.315462331005685	   
df.mm.trans3:probe4	0.242454157757124	0.048095092565285	5.04114130621565	5.43923888479197e-07	***
df.mm.trans3:probe5	0.171039125835883	0.048095092565285	3.55626981284446	0.000392769719543979	***
df.mm.trans3:probe6	-0.157583735354961	0.048095092565285	-3.27650342165481	0.00108508536078065	** 
df.mm.trans3:probe7	0.108660807328924	0.048095092565285	2.25929094910102	0.0240677379645078	*  
df.mm.trans3:probe8	0.310057156121938	0.048095092565285	6.44675245610686	1.73234984775887e-10	***
df.mm.trans3:probe9	0.2550948194951	0.048095092565285	5.30396774159089	1.37892970420459e-07	***
df.mm.trans3:probe10	0.32363532088437	0.048095092565285	6.72907158760662	2.78977198797381e-11	***
df.mm.trans3:probe11	0.574015665156306	0.048095092565285	11.9350152903257	6.71463831203974e-31	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.17667136633324	0.158764260904217	26.3073776336416	8.29911069575692e-118	***
df.mm.trans1	0.0193470117303273	0.137961878505427	0.140234475928554	0.88850137503922	   
df.mm.trans2	-0.0549147645602406	0.119842876832324	-0.458223016767812	0.646886147885308	   
df.mm.exp2	-0.125623166767356	0.152627518779079	-0.823070228568607	0.410653183051947	   
df.mm.exp3	0.0547235432588055	0.152627518779079	0.358543096923531	0.720008316638478	   
df.mm.exp4	0.0348428884411354	0.152627518779079	0.228287065922684	0.819467109020714	   
df.mm.exp5	0.127183055971865	0.152627518779079	0.833290464191824	0.404868652473376	   
df.mm.exp6	0.0361410699948970	0.152627518779079	0.236792619600987	0.81286342906278	   
df.mm.exp7	0.0737103787108835	0.152627518779079	0.482942914230136	0.629235995536008	   
df.mm.exp8	0.156016902381269	0.152627518779079	1.02220689708712	0.306916216875962	   
df.mm.trans1:exp2	0.0345470948183840	0.143617277734666	0.240549712146822	0.809950644331341	   
df.mm.trans2:exp2	0.00745280547143526	0.0997445455398328	0.0747189275473615	0.940452445810403	   
df.mm.trans1:exp3	-0.0859909073861217	0.143617277734666	-0.598750434087678	0.549467246916967	   
df.mm.trans2:exp3	-0.0197230780499771	0.0997445455398328	-0.197735905690208	0.843289607398978	   
df.mm.trans1:exp4	-0.0396950867241021	0.143617277734666	-0.276394925110884	0.782298634751965	   
df.mm.trans2:exp4	-0.0331366826587630	0.0997445455398328	-0.332215485863634	0.739792232031774	   
df.mm.trans1:exp5	-0.0884749253878376	0.143617277734666	-0.616046528547183	0.537996072648437	   
df.mm.trans2:exp5	-0.0639773915766155	0.0997445455398328	-0.641412432432871	0.521393418906356	   
df.mm.trans1:exp6	-0.0689043716942668	0.143617277734666	-0.479777731350459	0.631484426918205	   
df.mm.trans2:exp6	-0.0513253589358465	0.0997445455398328	-0.51456807646038	0.60696214610102	   
df.mm.trans1:exp7	-0.106716856056065	0.143617277734666	-0.743064189346527	0.457607466518541	   
df.mm.trans2:exp7	-0.0294863512598852	0.0997445455398328	-0.295618683711480	0.767579201054553	   
df.mm.trans1:exp8	-0.121556668511332	0.143617277734666	-0.846393069334662	0.39752453706105	   
df.mm.trans2:exp8	-0.0819063136017663	0.0997445455398328	-0.821160827977878	0.411739305676289	   
df.mm.trans1:probe2	0.0301526128877981	0.100048182606097	0.301380915698520	0.76318315631264	   
df.mm.trans1:probe3	0.0857589632873514	0.100048182606096	0.85717662283778	0.391541029820096	   
df.mm.trans1:probe4	0.111072330951229	0.100048182606096	1.11018839181253	0.267169632874176	   
df.mm.trans1:probe5	-0.0549362465401996	0.100048182606096	-0.549097895725814	0.583053915834182	   
df.mm.trans1:probe6	0.0072948595999017	0.100048182606096	0.0729134643916779	0.941888735005489	   
df.mm.trans1:probe7	-0.0394104310625248	0.100048182606096	-0.393914512347407	0.693723381782137	   
df.mm.trans1:probe8	0.0475273314771068	0.100048182606097	0.475044425986511	0.634853170758412	   
df.mm.trans1:probe9	-0.0342969798407953	0.100048182606097	-0.342804626205227	0.731813412693669	   
df.mm.trans1:probe10	0.118184105855552	0.100048182606097	1.18127189097336	0.237759692647661	   
df.mm.trans1:probe11	0.0845576127321962	0.100048182606096	0.845168902918619	0.398207266590852	   
df.mm.trans1:probe12	0.0641272327768911	0.100048182606096	0.640963494852964	0.521684948526722	   
df.mm.trans1:probe13	0.0325767918321849	0.100048182606096	0.325611030441644	0.744782928280286	   
df.mm.trans1:probe14	-0.117219464109830	0.100048182606096	-1.17163011917307	0.241608870829454	   
df.mm.trans1:probe15	0.105120685544901	0.100048182606096	1.05070060051741	0.293635596711436	   
df.mm.trans1:probe16	0.0905492343800819	0.100048182606097	0.905056264106133	0.365641239041182	   
df.mm.trans1:probe17	-0.00746576667087347	0.100048182606096	-0.0746217120231681	0.940529778190925	   
df.mm.trans1:probe18	0.0356223836821008	0.100048182606097	0.356052281552690	0.72187226217587	   
df.mm.trans1:probe19	0.0678140882410834	0.100048182606096	0.677814293819577	0.498037367494633	   
df.mm.trans1:probe20	0.0110028473482338	0.100048182606096	0.109975484427873	0.91244963431629	   
df.mm.trans1:probe21	0.0378775048946220	0.100048182606096	0.37859263314908	0.705066205387204	   
df.mm.trans1:probe22	0.0990308441642453	0.100048182606096	0.98983151502255	0.322482366588777	   
df.mm.trans1:probe23	-0.00140507748040979	0.100048182606097	-0.0140440080350262	0.988797513911507	   
df.mm.trans1:probe24	0.0708087615778679	0.100048182606096	0.707746605019821	0.479258211075777	   
df.mm.trans1:probe25	-0.0162072811604946	0.100048182606096	-0.161994758308654	0.871340854300425	   
df.mm.trans1:probe26	-0.073304984210839	0.100048182606096	-0.732696809690695	0.463905354816471	   
df.mm.trans1:probe27	0.00135340919122553	0.100048182606097	0.0135275739745727	0.989209432318881	   
df.mm.trans1:probe28	0.057352381972812	0.100048182606096	0.573247614088267	0.566598637304991	   
df.mm.trans1:probe29	0.0771607091652006	0.100048182606096	0.771235490293641	0.440739241247836	   
df.mm.trans1:probe30	-0.0118054876235148	0.100048182606096	-0.117998021713144	0.906091580595088	   
df.mm.trans2:probe2	0.171491713077192	0.100048182606097	1.71409123694309	0.086804308501082	.  
df.mm.trans2:probe3	0.0468916911595265	0.100048182606096	0.468691084016444	0.639386830689108	   
df.mm.trans2:probe4	0.0355149281083470	0.100048182606096	0.354978243314766	0.722676505797748	   
df.mm.trans2:probe5	0.191860234211309	0.100048182606096	1.91767835470524	0.0554202969549189	.  
df.mm.trans2:probe6	0.0848634512978253	0.100048182606096	0.848225815674678	0.396503718656706	   
df.mm.trans3:probe2	0.094950965587493	0.100048182606097	0.94905237770613	0.342810292415859	   
df.mm.trans3:probe3	0.128783739841711	0.100048182606097	1.28721718363191	0.198299595537226	   
df.mm.trans3:probe4	0.118278250722784	0.100048182606097	1.18221288624964	0.237386365667433	   
df.mm.trans3:probe5	0.165737667222513	0.100048182606097	1.65657848953684	0.0979006688368599	.  
df.mm.trans3:probe6	0.0464552552755129	0.100048182606097	0.46432882702541	0.64250752188328	   
df.mm.trans3:probe7	0.00824913288099633	0.100048182606097	0.0824516014796021	0.934303170045763	   
df.mm.trans3:probe8	0.0765435286073537	0.100048182606097	0.76506665701981	0.444402150359462	   
df.mm.trans3:probe9	0.157662812585687	0.100048182606097	1.57586883118534	0.115354419476379	   
df.mm.trans3:probe10	0.160993175690386	0.100048182606097	1.60915642340289	0.107879900092323	   
df.mm.trans3:probe11	0.00726144183004597	0.100048182606097	0.0725794476311006	0.942154474226077