chr1.1614_chr1_169392040_169399948_-_2.R 

fitVsDatCorrelation=0.883958183347246
cont.fitVsDatCorrelation=0.224335022709339

fstatistic=8279.93319285173,60,876
cont.fstatistic=1894.82793443592,60,876

residuals=-0.697120502366612,-0.116270250392809,-0.00575827921651649,0.109814562692802,0.635073163689339
cont.residuals=-0.855566375321983,-0.279471901432039,-0.0621931801216938,0.240352819420437,1.44050209345548

predictedValues:
Include	Exclude	Both
chr1.1614_chr1_169392040_169399948_-_2.R.tl.Lung	77.8097199613655	143.219476322069	108.991645276471
chr1.1614_chr1_169392040_169399948_-_2.R.tl.cerebhem	85.8172315756697	76.991517964598	87.196044916447
chr1.1614_chr1_169392040_169399948_-_2.R.tl.cortex	122.255593964871	90.2470361897924	128.432051478148
chr1.1614_chr1_169392040_169399948_-_2.R.tl.heart	82.9223488615828	90.5795016344444	92.9954251597894
chr1.1614_chr1_169392040_169399948_-_2.R.tl.kidney	74.0854298231396	146.054543675383	77.2191145457767
chr1.1614_chr1_169392040_169399948_-_2.R.tl.liver	69.3088665620657	123.642560514354	62.9988015734741
chr1.1614_chr1_169392040_169399948_-_2.R.tl.stomach	71.585812068695	90.085357685842	87.6440739728383
chr1.1614_chr1_169392040_169399948_-_2.R.tl.testicle	69.8407138495335	107.652161953867	91.864345968581


diffExp=-65.4097563607036,8.82571361107172,32.0085577750786,-7.65715277286162,-71.9691138522433,-54.3336939522882,-18.4995456171470,-37.8114481043335
diffExpScore=1.3737311722345
diffExp1.5=-1,0,0,0,-1,-1,0,-1
diffExp1.5Score=0.8
diffExp1.4=-1,0,0,0,-1,-1,0,-1
diffExp1.4Score=0.8
diffExp1.3=-1,0,1,0,-1,-1,0,-1
diffExp1.3Score=1.25
diffExp1.2=-1,0,1,0,-1,-1,-1,-1
diffExp1.2Score=1.2

cont.predictedValues:
Include	Exclude	Both
Lung	74.384813315752	91.597719864179	78.3941547703954
cerebhem	76.6861107286071	84.3365417509291	85.7624832115896
cortex	77.0310978433941	80.698652677475	81.5905389985127
heart	80.1942932019147	91.5427764437562	82.9484885326256
kidney	81.6462702311371	73.9235184186314	81.5183439515825
liver	78.701320225295	78.796054411994	89.182302816591
stomach	74.3340943848993	71.7701564514487	84.4251329971835
testicle	78.8419216210665	85.4286294259661	78.6440305983237
cont.diffExp=-17.2129065484270,-7.65043102232202,-3.66755483408095,-11.3484832418415,7.72275181250572,-0.0947341866990001,2.56393793345056,-6.58670780489965
cont.diffExpScore=1.52511971704504

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

tran.correlation=-0.406279694119253
cont.tran.correlation=-0.0466277864787498

tran.covariance=-0.0193362927503579
cont.tran.covariance=-0.000103929948024654

tran.mean=95.1311170379545
cont.tran.mean=79.9946231872779

weightedLogRatios:
wLogRatio
Lung	-2.84270795910524
cerebhem	0.477286411601816
cortex	1.41288368301531
heart	-0.39410451715115
kidney	-3.152574190477
liver	-2.62089658597122
stomach	-1.00812950482336
testicle	-1.9308974659427

cont.weightedLogRatios:
wLogRatio
Lung	-0.918654663600919
cerebhem	-0.41720565301222
cortex	-0.203142489147518
heart	-0.589058642386916
kidney	0.43250788361962
liver	-0.00525258628729337
stomach	0.150618979191321
testicle	-0.353647117451622

varWeightedLogRatios=2.76636786834822
cont.varWeightedLogRatios=0.184001971075238

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.03939875658933	0.0880025420808235	57.2642407529663	2.26821613057655e-298	***
df.mm.trans1	-0.427277992144168	0.0753408907270007	-5.6712628165284	1.92491155347194e-08	***
df.mm.trans2	-0.139839011725179	0.0665215599319566	-2.10216074109232	0.0358241320750351	*  
df.mm.exp2	-0.299617274675626	0.0848319717674608	-3.53189096555399	0.000434140372899703	***
df.mm.exp3	-0.174108721104897	0.0848319717674608	-2.05239507555193	0.0404279525569455	*  
df.mm.exp4	-0.235791131210662	0.0848319717674608	-2.77950784707688	0.00556073802691785	** 
df.mm.exp5	0.31517861775476	0.0848319717674608	3.71532820925959	0.000215802590718670	***
df.mm.exp6	0.285478584266918	0.0848319717674608	3.36522396354838	0.000798059003601768	***
df.mm.exp7	-0.329002841775807	0.0848319717674608	-3.87828827883031	0.000113065806943802	***
df.mm.exp8	-0.222563930364218	0.0848319717674607	-2.62358549173305	0.008852280443614	** 
df.mm.trans1:exp2	0.397570736603666	0.0772713715283145	5.14512333274665	3.30056151792927e-07	***
df.mm.trans2:exp2	-0.321065718956259	0.0557775478754109	-5.75618203355617	1.18954961877528e-08	***
df.mm.trans1:exp3	0.625956248200196	0.0772713715283145	8.10075239794117	1.82565310884717e-15	***
df.mm.trans2:exp3	-0.287718775337654	0.055777547875411	-5.15832599848823	3.0825366705386e-07	***
df.mm.trans1:exp4	0.299429386600514	0.0772713715283145	3.87503651971279	0.000114560392010039	***
df.mm.trans2:exp4	-0.222359185728530	0.0557775478754109	-3.98653569757511	7.2630670598831e-05	***
df.mm.trans1:exp5	-0.364226091970917	0.0772713715283145	-4.71359683110392	2.83011589932101e-06	***
df.mm.trans2:exp5	-0.295576732108909	0.0557775478754109	-5.29920628223262	1.47251679420668e-07	***
df.mm.trans1:exp6	-0.401172100253373	0.0772713715283145	-5.19173003298345	2.59130276586652e-07	***
df.mm.trans2:exp6	-0.432462010897969	0.0557775478754109	-7.7533349415781	2.48071800077288e-14	***
df.mm.trans1:exp7	0.245633382025215	0.0772713715283145	3.17884071638624	0.0015305566281713	** 
df.mm.trans2:exp7	-0.134617771741227	0.0557775478754109	-2.41347597499121	0.0160054535010943	*  
df.mm.trans1:exp8	0.114514704439930	0.0772713715283145	1.48198099988387	0.138704971569556	   
df.mm.trans2:exp8	-0.0629090159653442	0.0557775478754109	-1.12785553258567	0.259689747276233	   
df.mm.trans1:probe2	-0.517486861318547	0.0553533778573732	-9.34878559086196	7.18486414463417e-20	***
df.mm.trans1:probe3	-0.492160983527345	0.0553533778573732	-8.89125474502164	3.39453948441213e-18	***
df.mm.trans1:probe4	-0.536259484608953	0.0553533778573731	-9.68792701306705	3.73439519595372e-21	***
df.mm.trans1:probe5	-0.383940756108701	0.0553533778573732	-6.93617573073835	7.82428893766972e-12	***
df.mm.trans1:probe6	-0.837227395296287	0.0553533778573732	-15.1251364903789	4.30910911150331e-46	***
df.mm.trans1:probe7	-0.509729718042944	0.0553533778573732	-9.20864701981412	2.37917273324146e-19	***
df.mm.trans1:probe8	-0.741501286887058	0.0553533778573732	-13.3957730420292	2.31538015667117e-37	***
df.mm.trans1:probe9	-0.358654352459353	0.0553533778573732	-6.47935801467226	1.53495453897952e-10	***
df.mm.trans1:probe10	-0.485075619793788	0.0553533778573732	-8.76325237176426	9.70600237205944e-18	***
df.mm.trans1:probe11	-0.525547154798044	0.0553533778573731	-9.49440079613932	2.03924499192301e-20	***
df.mm.trans1:probe12	-0.573478571497093	0.0553533778573732	-10.3603175396947	8.33506798329748e-24	***
df.mm.trans1:probe13	-0.381662063566967	0.0553533778573731	-6.89500945272718	1.03047254562376e-11	***
df.mm.trans1:probe14	-0.358148510231236	0.0553533778573732	-6.47021959805349	1.62621349133317e-10	***
df.mm.trans1:probe15	-0.261558025014910	0.0553533778573732	-4.7252405388675	2.67648924853430e-06	***
df.mm.trans1:probe16	-0.283635302023026	0.0553533778573731	-5.12408299189721	3.67915918438215e-07	***
df.mm.trans1:probe17	-0.361029672824004	0.0553533778573731	-6.522269946276	1.16924698793925e-10	***
df.mm.trans1:probe18	-0.368564359986337	0.0553533778573732	-6.65838968194501	4.88137753905999e-11	***
df.mm.trans1:probe19	-0.368047542938393	0.0553533778573731	-6.64905299703166	5.18536973696456e-11	***
df.mm.trans1:probe20	-0.165487731417729	0.0553533778573732	-2.98965912873708	0.00287098042874422	** 
df.mm.trans2:probe2	0.207935826163236	0.0553533778573731	3.7565155770442	0.000183689909233686	***
df.mm.trans2:probe3	0.173618878984095	0.0553533778573732	3.13655436586818	0.00176654273969018	** 
df.mm.trans2:probe4	0.475657568530914	0.0553533778573732	8.59310826082776	3.8472816729584e-17	***
df.mm.trans2:probe5	0.108050570224207	0.0553533778573732	1.95201403069957	0.0512548179767836	.  
df.mm.trans2:probe6	0.266288812844673	0.0553533778573732	4.81070574465769	1.77031200010052e-06	***
df.mm.trans3:probe2	0.235609629102023	0.0553533778573731	4.25646343948709	2.30090156214614e-05	***
df.mm.trans3:probe3	0.367267675989367	0.0553533778573731	6.63496411972709	5.67951416019941e-11	***
df.mm.trans3:probe4	0.0918882961774566	0.0553533778573731	1.66003051185461	0.0972662053329777	.  
df.mm.trans3:probe5	0.278355766543923	0.0553533778573731	5.02870425109649	5.98972495568311e-07	***
df.mm.trans3:probe6	0.94846059534194	0.0553533778573731	17.1346470993297	5.57580414589759e-57	***
df.mm.trans3:probe7	0.00973817292871145	0.0553533778573732	0.175927347266926	0.860391679984608	   
df.mm.trans3:probe8	0.187954164638089	0.0553533778573731	3.39553197859727	0.000715751109834542	***
df.mm.trans3:probe9	0.346398406360735	0.0553533778573732	6.25794521977116	6.09752792313691e-10	***
df.mm.trans3:probe10	-0.00296777308417535	0.0553533778573731	-0.053615031260103	0.957254104789011	   
df.mm.trans3:probe11	0.257636186994231	0.0553533778573732	4.65438961391068	3.75184642979648e-06	***
df.mm.trans3:probe12	-0.0738672739724244	0.0553533778573731	-1.33446732307386	0.182397510030699	   
df.mm.trans3:probe13	0.200389363493197	0.0553533778573732	3.62018310805769	0.000311284368223943	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.40520973148554	0.183416987564699	24.0174576519617	2.48903557303286e-98	***
df.mm.trans1	-0.171060625252348	0.157027273199633	-1.08936888329503	0.276290833113871	   
df.mm.trans2	0.122220961561393	0.138645814567700	0.881533726369456	0.378270814870908	   
df.mm.exp2	-0.141954612034672	0.176808809641783	-0.802870695879208	0.422267248203077	   
df.mm.exp3	-0.131691033379498	0.176808809641783	-0.744821672892352	0.45657930028071	   
df.mm.exp4	0.0181301154837341	0.176808809641783	0.102540792624904	0.918350903286501	   
df.mm.exp5	-0.160309721698117	0.176808809641782	-0.906684016610409	0.364823246303149	   
df.mm.exp6	-0.223068575473498	0.176808809641782	-1.26163722229361	0.207415192633737	   
df.mm.exp7	-0.318735489042510	0.176808809641783	-1.80271271374019	0.0717769309243222	.  
df.mm.exp8	-0.0147143987396261	0.176808809641782	-0.083222090400573	0.93369396085445	   
df.mm.trans1:exp2	0.172423419430135	0.161050827119283	1.07061492644449	0.284637496365202	   
df.mm.trans2:exp2	0.0593634767900198	0.116252889554687	0.510640871099331	0.609731205035856	   
df.mm.trans1:exp3	0.166648442893253	0.161050827119283	1.03475682723333	0.301068054731134	   
df.mm.trans2:exp3	0.00500653401181492	0.116252889554687	0.0430658887791325	0.965658824941219	   
df.mm.trans1:exp4	0.0570704408704036	0.161050827119283	0.354362916920223	0.723152204595356	   
df.mm.trans2:exp4	-0.0187301293875833	0.116252889554687	-0.161115387835348	0.872039669458098	   
df.mm.trans1:exp5	0.253454061206462	0.161050827119283	1.57375199953950	0.115905868410411	   
df.mm.trans2:exp5	-0.0540656335043522	0.116252889554687	-0.465069158379233	0.641997513275478	   
df.mm.trans1:exp6	0.279476707269672	0.161050827119283	1.73533233121912	0.08303363318572	.  
df.mm.trans2:exp6	0.0725251211121506	0.116252889554687	0.623856502749842	0.53288424297466	   
df.mm.trans1:exp7	0.318053411240794	0.161050827119283	1.97486356903480	0.0485972712099946	*  
df.mm.trans2:exp7	0.0747978513246633	0.116252889554687	0.643406384229936	0.520128833651612	   
df.mm.trans1:exp8	0.0729074555056405	0.161050827119283	0.452698423284976	0.650878006909684	   
df.mm.trans2:exp8	-0.0550106965238272	0.116252889554687	-0.473198530673506	0.636189434976762	   
df.mm.trans1:probe2	0.144085117329501	0.115368824332431	1.24890860389046	0.212032141895319	   
df.mm.trans1:probe3	0.0530275283837635	0.115368824332431	0.459634816343162	0.645892409766706	   
df.mm.trans1:probe4	-0.0411917657149492	0.115368824332431	-0.357044166422782	0.721144733503057	   
df.mm.trans1:probe5	0.275871598665254	0.115368824332431	2.39121443996291	0.0170028874409075	*  
df.mm.trans1:probe6	0.117130804688046	0.115368824332431	1.01527258655716	0.310256235350463	   
df.mm.trans1:probe7	0.0895441011654058	0.115368824332431	0.776155098082542	0.437866914992761	   
df.mm.trans1:probe8	0.159627951208684	0.115368824332431	1.38363160179844	0.166823750619576	   
df.mm.trans1:probe9	0.0200603549150856	0.115368824332431	0.173880205776236	0.861999782072418	   
df.mm.trans1:probe10	0.088038183575798	0.115368824332431	0.763102025917495	0.445608000669509	   
df.mm.trans1:probe11	0.230092971142153	0.115368824332431	1.99441203005717	0.046416575490078	*  
df.mm.trans1:probe12	0.0615795365743039	0.115368824332431	0.533762365445144	0.593641364191447	   
df.mm.trans1:probe13	0.142346719302642	0.115368824332431	1.23384042549029	0.217593299599926	   
df.mm.trans1:probe14	0.0687056573005995	0.115368824332431	0.595530531737297	0.55164271644432	   
df.mm.trans1:probe15	0.175482966941443	0.115368824332431	1.52106054609515	0.128605501525010	   
df.mm.trans1:probe16	0.291611110028333	0.115368824332431	2.52764220937248	0.0116579597530921	*  
df.mm.trans1:probe17	0.207040599856062	0.115368824332431	1.79459746646531	0.073062537231754	.  
df.mm.trans1:probe18	0.0918405641426007	0.115368824332431	0.796060501387838	0.426212538245349	   
df.mm.trans1:probe19	0.188624362441005	0.115368824332431	1.63496822935016	0.102414967506126	   
df.mm.trans1:probe20	0.114870496163982	0.115368824332431	0.995680564733732	0.319680324509486	   
df.mm.trans2:probe2	-0.0145540666849049	0.115368824332431	-0.126152509303275	0.899640150488475	   
df.mm.trans2:probe3	-0.0331009097675083	0.115368824332431	-0.286913817134247	0.774246159221031	   
df.mm.trans2:probe4	0.0689689476906636	0.115368824332431	0.597812694111643	0.55011942866144	   
df.mm.trans2:probe5	-0.133954131321840	0.115368824332431	-1.16109470731761	0.245919679974268	   
df.mm.trans2:probe6	-0.0778218057098407	0.115368824332431	-0.674547965276996	0.500140977150479	   
df.mm.trans3:probe2	-0.0130053582340933	0.115368824332431	-0.112728532247315	0.910271606840929	   
df.mm.trans3:probe3	0.0732670422437378	0.115368824332431	0.63506794550165	0.525549940048205	   
df.mm.trans3:probe4	0.023084665793972	0.115368824332431	0.200094487636056	0.84145312549361	   
df.mm.trans3:probe5	-0.0172656125027231	0.115368824332431	-0.149655789617591	0.881070637910857	   
df.mm.trans3:probe6	-0.00359791880374487	0.115368824332431	-0.0311862309819296	0.975128124409595	   
df.mm.trans3:probe7	0.0422839709345413	0.115368824332431	0.366511240616455	0.714072130755827	   
df.mm.trans3:probe8	-0.0672261377813002	0.115368824332431	-0.582706274162858	0.560241006515045	   
df.mm.trans3:probe9	-0.00719606899536428	0.115368824332431	-0.0623744675999216	0.950278855861457	   
df.mm.trans3:probe10	-0.151062160018491	0.115368824332431	-1.30938458368276	0.190747435642312	   
df.mm.trans3:probe11	0.0394573897535754	0.115368824332431	0.342010850694641	0.732424759697418	   
df.mm.trans3:probe12	0.0519481134900866	0.115368824332431	0.450278606813223	0.65262097480384	   
df.mm.trans3:probe13	0.099242977788928	0.115368824332431	0.860223534071585	0.389901196241073