chr17.10769_chr17_79120327_79124211_-_2.R 

fitVsDatCorrelation=0.88758284123876
cont.fitVsDatCorrelation=0.247268128184815

fstatistic=8728.42555671588,57,807
cont.fstatistic=1961.80271180105,57,807

residuals=-0.825595571287838,-0.088778880071562,-0.00341408003222285,0.0889550467649052,0.884554836939468
cont.residuals=-0.769372368018203,-0.240073799631553,-0.0660980304457135,0.140404004987611,1.57922144529381

predictedValues:
Include	Exclude	Both
chr17.10769_chr17_79120327_79124211_-_2.R.tl.Lung	59.2269673850047	67.0542798421182	81.585137900263
chr17.10769_chr17_79120327_79124211_-_2.R.tl.cerebhem	66.6351772190666	79.3281002249016	114.178614236038
chr17.10769_chr17_79120327_79124211_-_2.R.tl.cortex	57.9324962869248	67.8455732200696	106.828529479567
chr17.10769_chr17_79120327_79124211_-_2.R.tl.heart	58.7694072250543	75.8761237089976	101.98362052138
chr17.10769_chr17_79120327_79124211_-_2.R.tl.kidney	58.5709837658781	73.8540682021026	90.6040638336784
chr17.10769_chr17_79120327_79124211_-_2.R.tl.liver	58.4360923082397	74.7413763279248	100.929899935587
chr17.10769_chr17_79120327_79124211_-_2.R.tl.stomach	60.323880666951	69.8065698612092	84.8472844144121
chr17.10769_chr17_79120327_79124211_-_2.R.tl.testicle	59.520077998303	123.196668724422	231.459627822165


diffExp=-7.82731245711356,-12.6929230058350,-9.91307693314482,-17.1067164839433,-15.2830844362245,-16.3052840196851,-9.48268919425821,-63.6765907261193
diffExpScore=0.993476318397546
diffExp1.5=0,0,0,0,0,0,0,-1
diffExp1.5Score=0.5
diffExp1.4=0,0,0,0,0,0,0,-1
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,0,0,0,-1
diffExp1.3Score=0.5
diffExp1.2=0,0,0,-1,-1,-1,0,-1
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	75.1677451080027	69.5135072438765	77.1762534677476
cerebhem	73.2330390308058	77.2610234694936	69.5166901250446
cortex	69.5559182054627	74.4860259180587	84.530621612283
heart	69.771711754198	82.3549562816251	69.4125655068743
kidney	69.4882424847515	79.3040099159607	64.0520220418974
liver	70.1495223816385	74.6911329224559	81.9831516019387
stomach	67.1881035087622	66.9405629691054	67.2120664022157
testicle	63.4982352137514	66.9970468188851	66.6610705027576
cont.diffExp=5.65423786412622,-4.02798443868784,-4.93010771259601,-12.5832445274271,-9.8157674312092,-4.54161054081743,0.247540539656768,-3.49881160513364
cont.diffExpScore=1.31318517441308

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=0.077926240214455
cont.tran.correlation=0.339099588148825

tran.covariance=0.00103687147640166
cont.tran.covariance=0.00147002564509596

tran.mean=69.444865185448
cont.tran.mean=71.8500489516771

weightedLogRatios:
wLogRatio
Lung	-0.514306400493177
cerebhem	-0.747378007316547
cortex	-0.653661026713838
heart	-1.07336652512947
kidney	-0.970569440799751
liver	-1.03140161432668
stomach	-0.609218606710821
testicle	-3.23726879407495

cont.weightedLogRatios:
wLogRatio
Lung	0.334749471478124
cerebhem	-0.231327855503767
cortex	-0.29284816542542
heart	-0.717647790039306
kidney	-0.569118252337108
liver	-0.268619769076433
stomach	0.0155234558224149
testicle	-0.224083893403361

varWeightedLogRatios=0.785339522944042
cont.varWeightedLogRatios=0.105128108163003

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.78977887880842	0.0835569454359163	45.3556417008443	3.52103979276331e-224	***
df.mm.trans1	0.344783040443457	0.072235374208663	4.77304982801776	2.15407768845323e-06	***
df.mm.trans2	0.439955217921237	0.064152674417117	6.85794040417822	1.38973407249145e-11	***
df.mm.exp2	-0.0501712647575066	0.0829895963555042	-0.604548846611893	0.545648733177299	   
df.mm.exp3	-0.279944699476742	0.0829895963555043	-3.37325052501204	0.000778269694356819	***
df.mm.exp4	-0.107321018580979	0.0829895963555043	-1.29318641485188	0.196316654605135	   
df.mm.exp5	-0.0194008503280241	0.0829895963555042	-0.233774487164828	0.815219346205068	   
df.mm.exp6	-0.117690953955134	0.0829895963555042	-1.41814105771739	0.156535613708069	   
df.mm.exp7	0.0193709042863380	0.0829895963555043	0.233413646252217	0.815499410737809	   
df.mm.exp8	-0.429542047132062	0.0829895963555042	-5.17585415516451	2.86574335231345e-07	***
df.mm.trans1:exp2	0.168026921015241	0.0766771118286529	2.19135693830936	0.0287111422932813	*  
df.mm.trans2:exp2	0.218261245737130	0.0579624483283727	3.76556291239841	0.000178237378292231	***
df.mm.trans1:exp3	0.257846206773806	0.0766771118286529	3.36275324701853	0.00080804296320056	***
df.mm.trans2:exp3	0.291676401708153	0.0579624483283727	5.03216151353249	5.98191067026697e-07	***
df.mm.trans1:exp4	0.0995654844823086	0.0766771118286529	1.29850332267083	0.194485370178030	   
df.mm.trans2:exp4	0.230920639557847	0.0579624483283727	3.98396972898073	7.39020262970641e-05	***
df.mm.trans1:exp5	0.0082632983814188	0.0766771118286529	0.107767470426957	0.914206934105588	   
df.mm.trans2:exp5	0.115989506859441	0.0579624483283727	2.00111469071025	0.0457144837917037	*  
df.mm.trans1:exp6	0.104247703551238	0.0766771118286529	1.35956742585971	0.174346600695477	   
df.mm.trans2:exp6	0.226222354423768	0.0579624483283727	3.90291233286348	0.000102972294005473	***
df.mm.trans1:exp7	-0.00101981631142036	0.0766771118286529	-0.013300139860501	0.989391623862506	   
df.mm.trans2:exp7	0.0208547868422953	0.0579624483283727	0.359798239096929	0.719092154655133	   
df.mm.trans1:exp8	0.434478779791696	0.0766771118286529	5.66634252947096	2.02990931981902e-08	***
df.mm.trans2:exp8	1.03782161999502	0.0579624483283727	17.9050687113057	1.25994771753884e-60	***
df.mm.trans1:probe2	-0.160966701978523	0.0514365703101663	-3.1294213632029	0.00181451399812961	** 
df.mm.trans1:probe3	-0.140960062846988	0.0514365703101663	-2.74046387612916	0.00627081909728143	** 
df.mm.trans1:probe4	0.00483436468819407	0.0514365703101663	0.0939869174605246	0.925142878695708	   
df.mm.trans1:probe5	-0.25395142703959	0.0514365703101663	-4.93717651679037	9.63364410201536e-07	***
df.mm.trans1:probe6	-0.305627825839814	0.0514365703101663	-5.94183912334853	4.18946470712012e-09	***
df.mm.trans1:probe7	-0.245512228523649	0.0514365703101663	-4.77310650852482	2.15348799110645e-06	***
df.mm.trans1:probe8	-0.0663588937549471	0.0514365703101663	-1.29011116710928	0.197381611965969	   
df.mm.trans1:probe9	-0.0740964328749315	0.0514365703101663	-1.44053991990766	0.150102553352531	   
df.mm.trans1:probe10	-0.051447440394024	0.0514365703101663	-1.00021132987274	0.317508057611251	   
df.mm.trans1:probe11	-0.168419040640381	0.0514365703101663	-3.27430541392636	0.00110434804903635	** 
df.mm.trans1:probe12	-0.132523371946760	0.0514365703101663	-2.57644261947548	0.0101589346794145	*  
df.mm.trans1:probe13	-0.211857171107742	0.0514365703101663	-4.1188043804287	4.20106135432826e-05	***
df.mm.trans1:probe14	-0.0921160968922396	0.0514365703101663	-1.79086778797211	0.0736892016530869	.  
df.mm.trans1:probe15	0.0563880318884147	0.0514365703101663	1.09626344735644	0.273290532666513	   
df.mm.trans1:probe16	-0.0189488514629357	0.0514365703101663	-0.368392592054111	0.712677134618744	   
df.mm.trans1:probe17	0.0343727222014224	0.0514365703101663	0.66825455107431	0.504162200188946	   
df.mm.trans1:probe18	-0.00333111682960591	0.0514365703101663	-0.064761643506148	0.948379819857878	   
df.mm.trans1:probe19	-0.00570667035447559	0.0514365703101663	-0.110945778850805	0.911686929437328	   
df.mm.trans1:probe20	0.103376635887166	0.0514365703101663	2.00978866327589	0.0447859740430264	*  
df.mm.trans1:probe21	0.137303049856413	0.0514365703101663	2.6693663482706	0.0077521651590738	** 
df.mm.trans2:probe2	-0.068399959094714	0.0514365703101663	-1.32979237694615	0.183962422081288	   
df.mm.trans2:probe3	0.0400455272425284	0.0514365703101663	0.77854194012258	0.436477803966297	   
df.mm.trans2:probe4	-0.204338154926173	0.0514365703101663	-3.97262402399691	7.74417018229e-05	***
df.mm.trans2:probe5	-0.0229769372192291	0.0514365703101663	-0.446704301641351	0.655208424129732	   
df.mm.trans2:probe6	-0.107805352501331	0.0514365703101663	-2.09588920589488	0.0364029783697073	*  
df.mm.trans3:probe2	-0.145714452987317	0.0514365703101663	-2.83289597476364	0.00472782437145043	** 
df.mm.trans3:probe3	-0.0899619073167014	0.0514365703101663	-1.74898728228232	0.0806733849666012	.  
df.mm.trans3:probe4	-0.0776856731687566	0.0514365703101663	-1.51031985026035	0.131353263482306	   
df.mm.trans3:probe5	-0.440263087488713	0.0514365703101663	-8.55933987888177	5.68850134214401e-17	***
df.mm.trans3:probe6	-0.374073546865338	0.0514365703101663	-7.27252117724114	8.35445524702285e-13	***
df.mm.trans3:probe7	-0.114982481911401	0.0514365703101663	-2.23542279778858	0.0256624006075735	*  
df.mm.trans3:probe8	-0.231340623334256	0.0514365703101663	-4.49759037080534	7.88065234860143e-06	***
df.mm.trans3:probe9	-0.0818084552268381	0.0514365703101663	-1.5904725904843	0.112119958768213	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.14380217582308	0.175757273759182	23.5768459944413	6.51241388208432e-94	***
df.mm.trans1	0.147702589878533	0.151942993770948	0.972092139379538	0.331295983331841	   
df.mm.trans2	0.123876510349058	0.134941495301075	0.91800161301511	0.358892297927165	   
df.mm.exp2	0.184117918943262	0.174563887295342	1.05473085983561	0.291864101409002	   
df.mm.exp3	-0.0995227987543545	0.174563887295342	-0.570122493812098	0.568753303679898	   
df.mm.exp4	0.201047894093598	0.174563887295342	1.15171526716432	0.24977918445122	   
df.mm.exp5	0.239599173678929	0.174563887295342	1.37255865111181	0.170270922018324	   
df.mm.exp6	-0.0576748651876316	0.174563887295342	-0.330394024109077	0.741188010604855	   
df.mm.exp7	-0.0117029723080958	0.174563887295342	-0.0670411990098257	0.946565510405685	   
df.mm.exp8	-0.0591119650873538	0.174563887295342	-0.338626539562236	0.734979171425823	   
df.mm.trans1:exp2	-0.210193464431757	0.161285935770208	-1.30323492515324	0.192866268084641	   
df.mm.trans2:exp2	-0.0784493972318822	0.121920707434373	-0.643446046883459	0.520117512432676	   
df.mm.trans1:exp3	0.0219315888146493	0.161285935770208	0.135979549053157	0.891871360296219	   
df.mm.trans2:exp3	0.168613252456225	0.121920707434373	1.38297468907803	0.167055145200625	   
df.mm.trans1:exp4	-0.275541459706046	0.161285935770208	-1.70840351572020	0.087946035798583	.  
df.mm.trans2:exp4	-0.0315303362320239	0.121920707434373	-0.258613461942024	0.795999440081165	   
df.mm.trans1:exp5	-0.318163825807351	0.161285935770208	-1.97266937311047	0.0488742043867407	*  
df.mm.trans2:exp5	-0.107831562431221	0.121920707434373	-0.884440097997822	0.376722110254815	   
df.mm.trans1:exp6	-0.0114183543233697	0.161285935770208	-0.0707957223228566	0.943577876346472	   
df.mm.trans2:exp6	0.129515165249858	0.121920707434373	1.06229013901984	0.288421774813875	   
df.mm.trans1:exp7	-0.100523044460818	0.161285935770208	-0.623259827217906	0.533289893158478	   
df.mm.trans2:exp7	-0.026013004408948	0.121920707434373	-0.213360018624811	0.831100051763823	   
df.mm.trans1:exp8	-0.109598138816178	0.161285935770208	-0.679526942586786	0.496998900774278	   
df.mm.trans2:exp8	0.022239423656598	0.121920707434373	0.182408912518564	0.855307643363204	   
df.mm.trans1:probe2	0.0126877165184160	0.108193894859055	0.117268322163135	0.906676605664987	   
df.mm.trans1:probe3	0.049335415901866	0.108193894859055	0.455990755912205	0.648519305227589	   
df.mm.trans1:probe4	0.137373494664968	0.108193894859055	1.26969728600607	0.204558486264072	   
df.mm.trans1:probe5	0.0485242960393616	0.108193894859055	0.448493846187668	0.653917219313966	   
df.mm.trans1:probe6	0.103595366809194	0.108193894859055	0.957497342564	0.338603041262275	   
df.mm.trans1:probe7	0.0278080036039499	0.108193894859055	0.257020080848145	0.797228786222059	   
df.mm.trans1:probe8	0.0555917410250514	0.108193894859055	0.513815877480622	0.607521379649495	   
df.mm.trans1:probe9	0.0265171821202117	0.108193894859055	0.245089449407066	0.806449481025482	   
df.mm.trans1:probe10	0.0832178901891871	0.108193894859055	0.769155138537122	0.442026269301284	   
df.mm.trans1:probe11	0.0820817477605888	0.108193894859055	0.758654153892117	0.448280979697549	   
df.mm.trans1:probe12	0.00684201866637634	0.108193894859055	0.0632384911855656	0.94959225434036	   
df.mm.trans1:probe13	0.0918458489609267	0.108193894859055	0.848900477060884	0.396188411634022	   
df.mm.trans1:probe14	-0.028715062075782	0.108193894859055	-0.265403719065567	0.790766252598072	   
df.mm.trans1:probe15	0.0212276407051939	0.108193894859055	0.196199986448841	0.844503033489424	   
df.mm.trans1:probe16	-0.0776385947548894	0.108193894859055	-0.717587576046042	0.473219281144351	   
df.mm.trans1:probe17	-0.0304779782008893	0.108193894859055	-0.281697763451378	0.778247488451978	   
df.mm.trans1:probe18	0.0561363508174441	0.108193894859055	0.518849523723806	0.604007924812636	   
df.mm.trans1:probe19	-0.0288424169165058	0.108193894859055	-0.26658081728252	0.789860027137501	   
df.mm.trans1:probe20	0.253793425140985	0.108193894859055	2.34572778317672	0.0192311863749658	*  
df.mm.trans1:probe21	-0.0443805328276267	0.108193894859055	-0.410194428118533	0.681772201137769	   
df.mm.trans2:probe2	-0.144490280536261	0.108193894859055	-1.33547535860956	0.182097357049204	   
df.mm.trans2:probe3	-0.0292545331788047	0.108193894859055	-0.270389870120812	0.78692946688914	   
df.mm.trans2:probe4	-0.0374045162733110	0.108193894859055	-0.345717439251432	0.729645178442948	   
df.mm.trans2:probe5	-0.0937382715258366	0.108193894859055	-0.866391506174636	0.38653301209738	   
df.mm.trans2:probe6	-0.0874764532646614	0.108193894859055	-0.808515613368183	0.419032101921616	   
df.mm.trans3:probe2	-0.0443899438202182	0.108193894859055	-0.410281410776878	0.68170842592736	   
df.mm.trans3:probe3	-0.0273378890352468	0.108193894859055	-0.252674969053107	0.800583736827685	   
df.mm.trans3:probe4	-0.0872265546187827	0.108193894859055	-0.806205883727668	0.420361653101856	   
df.mm.trans3:probe5	-0.110608636442017	0.108193894859055	-1.02231864918171	0.306936468056933	   
df.mm.trans3:probe6	-0.0690264895896664	0.108193894859055	-0.637988767107311	0.523661976936167	   
df.mm.trans3:probe7	-0.0253814308836172	0.108193894859055	-0.234592080418973	0.814584863614223	   
df.mm.trans3:probe8	-0.0911922800734109	0.108193894859055	-0.842859758327473	0.399556617530524	   
df.mm.trans3:probe9	-0.168441950689358	0.108193894859055	-1.55685263857807	0.119897536773148