chr5.18864_chr5_88190915_88221440_+_2.R 

fitVsDatCorrelation=0.891880211426253
cont.fitVsDatCorrelation=0.286479541927241

fstatistic=3464.04408822267,43,485
cont.fstatistic=763.155449361058,43,485

residuals=-0.968974059097492,-0.119739478867341,0.000119769476553495,0.127362056402332,1.10091349504224
cont.residuals=-0.856892129666807,-0.32786822371756,-0.141446705905302,0.176908837498349,2.22097199116405

predictedValues:
Include	Exclude	Both
chr5.18864_chr5_88190915_88221440_+_2.R.tl.Lung	58.5563754467784	47.351146231846	62.4913354790811
chr5.18864_chr5_88190915_88221440_+_2.R.tl.cerebhem	58.1972930511804	94.801651204022	160.856709552309
chr5.18864_chr5_88190915_88221440_+_2.R.tl.cortex	55.7921903685039	125.804650096559	183.982908864421
chr5.18864_chr5_88190915_88221440_+_2.R.tl.heart	54.1594456382448	51.2180726913743	66.9037312082962
chr5.18864_chr5_88190915_88221440_+_2.R.tl.kidney	60.8930624306031	49.8865099066387	77.0589779695467
chr5.18864_chr5_88190915_88221440_+_2.R.tl.liver	56.8564211075353	51.4198372873349	65.4051001181102
chr5.18864_chr5_88190915_88221440_+_2.R.tl.stomach	56.3305385869485	56.8472824571886	66.4989404725796
chr5.18864_chr5_88190915_88221440_+_2.R.tl.testicle	52.6015055852464	59.7132287905261	69.9894916178477


diffExp=11.2052292149325,-36.6043581528415,-70.0124597280549,2.9413729468705,11.0065525239644,5.4365838202004,-0.51674387024012,-7.11172320527969
diffExpScore=1.71087459162715
diffExp1.5=0,-1,-1,0,0,0,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=0,-1,-1,0,0,0,0,0
diffExp1.4Score=0.666666666666667
diffExp1.3=0,-1,-1,0,0,0,0,0
diffExp1.3Score=0.666666666666667
diffExp1.2=1,-1,-1,0,1,0,0,0
diffExp1.2Score=4

cont.predictedValues:
Include	Exclude	Both
Lung	95.403370276997	75.6697517226953	97.0314090103954
cerebhem	78.8933680308781	86.5917823292794	77.8480904105119
cortex	72.3997435905318	62.4510838860973	68.09826879383
heart	64.6556703514851	71.4765848398108	70.2238340593632
kidney	68.8758672595549	68.7961026371278	79.5552786265556
liver	71.5371811022193	64.6652637983322	81.6521650420965
stomach	65.6958834803172	71.7741004511029	79.4112923857067
testicle	73.5875335864288	88.3618733671242	66.1896724438901
cont.diffExp=19.7336185543017,-7.69841429840135,9.94865970443447,-6.82091448832573,0.0797646224270494,6.87191730388706,-6.07821697078563,-14.7743397806955
cont.diffExpScore=31.831772582651

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,-1
cont.diffExp1.2Score=2

tran.correlation=-0.0947599343300651
cont.tran.correlation=0.310199647486448

tran.covariance=-0.00181667053637496
cont.tran.covariance=0.00511769615147502

tran.mean=61.9018256800331
cont.tran.mean=73.8021975443739

weightedLogRatios:
wLogRatio
Lung	0.841904924619146
cerebhem	-2.10198858971154
cortex	-3.60053895349316
heart	0.221350219420133
kidney	0.79935553918607
liver	0.401043246894686
stomach	-0.0368533469810609
testicle	-0.510551309089517

cont.weightedLogRatios:
wLogRatio
Lung	1.02942572747578
cerebhem	-0.411038225070639
cortex	0.622066384634837
heart	-0.423163165755071
kidney	0.0049035704611015
liver	0.42616290631742
stomach	-0.374238098482544
testicle	-0.803208461233821

varWeightedLogRatios=2.45936579657801
cont.varWeightedLogRatios=0.394415959578789

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	2.88103987122171	0.130547682517472	22.0688702829797	3.07276207598599e-75	***
df.mm.trans1	1.15059086970895	0.104510246917294	11.0093594039586	2.5814387761507e-25	***
df.mm.trans2	0.814210615663752	0.104510246917294	7.79072521288836	4.08142932412511e-14	***
df.mm.exp2	-0.257441381763539	0.139946340573452	-1.83957208676292	0.066442072960797	.  
df.mm.exp3	-0.151031742093224	0.139946340573452	-1.07921179985377	0.281029731031589	   
df.mm.exp4	-0.067782978790105	0.139946340573452	-0.484349776581179	0.62835630223483	   
df.mm.exp5	-0.118254287063065	0.139946340573452	-0.844997350973953	0.398528961955967	   
df.mm.exp6	0.00739987539976221	0.139946340573452	0.0528765194533853	0.957852064772042	   
df.mm.exp7	0.0818661311914041	0.139946340573452	0.584982292898442	0.558831667785953	   
df.mm.exp8	0.0114001299968370	0.139946340573452	0.0814607223748984	0.935109165140182	   
df.mm.trans1:exp2	0.251290251226641	0.109782941759990	2.28897356181271	0.022509880052036	*  
df.mm.trans2:exp2	0.951637181655742	0.109782941759990	8.66835198984042	6.60492061491304e-17	***
df.mm.trans1:exp3	0.102675671087314	0.109782941759990	0.935260701173288	0.350119388883303	   
df.mm.trans2:exp3	1.12817102289696	0.109782941759990	10.2763781404527	1.51934911735466e-22	***
df.mm.trans1:exp4	-0.0102746013334041	0.109782941759990	-0.0935901440486693	0.92547338840202	   
df.mm.trans2:exp4	0.146284403824362	0.109782941759990	1.33248755662034	0.183325726985868	   
df.mm.trans1:exp5	0.157383564849648	0.109782941759990	1.43358851864003	0.152334065940662	   
df.mm.trans2:exp5	0.170413883738043	0.109782941759990	1.55228017218381	0.121247467413936	   
df.mm.trans1:exp6	-0.036860686384292	0.109782941759990	-0.335759689013233	0.737197287062608	   
df.mm.trans2:exp6	0.0750331350671707	0.109782941759990	0.68346806766401	0.494637500236647	   
df.mm.trans1:exp7	-0.120619290094182	0.109782941759990	-1.09870703189829	0.272440987403087	   
df.mm.trans2:exp7	0.100911258897191	0.109782941759990	0.919188876517866	0.358453705626776	   
df.mm.trans1:exp8	-0.118645360413662	0.109782941759990	-1.08072673688275	0.280355781883224	   
df.mm.trans2:exp8	0.220562426654750	0.109782941759990	2.00907739507427	0.0450825373610398	*  
df.mm.trans1:probe2	0.244663767599934	0.0751632420390278	3.25509864879025	0.00121275882861179	** 
df.mm.trans1:probe3	0.131312398724484	0.0751632420390278	1.74702946762596	0.0812651891000293	.  
df.mm.trans1:probe4	0.0589980803163504	0.0751632420390278	0.784932617538187	0.43287631584604	   
df.mm.trans1:probe5	0.0371148621318133	0.0751632420390278	0.493790064464513	0.621677991335824	   
df.mm.trans1:probe6	0.141658605048992	0.0751632420390278	1.88467928213418	0.0600708395446073	.  
df.mm.trans2:probe2	1.14344537509657	0.0751632420390278	15.2128266966298	5.18911067951412e-43	***
df.mm.trans2:probe3	0.312857673590482	0.0751632420390278	4.162375984634	3.72695351681222e-05	***
df.mm.trans2:probe4	-0.000917319963775719	0.0751632420390278	-0.0122043693019443	0.990267582384107	   
df.mm.trans2:probe5	0.964208162910206	0.0751632420390278	12.8281875123155	1.21957987693420e-32	***
df.mm.trans2:probe6	0.177854749895587	0.0751632420390278	2.36624638680750	0.0183615851586681	*  
df.mm.trans3:probe2	-0.697439236607075	0.0751632420390278	-9.27899353044053	5.68248464090907e-19	***
df.mm.trans3:probe3	-0.309622580005642	0.0751632420390278	-4.11933508462652	4.46743185350981e-05	***
df.mm.trans3:probe4	-1.22266301073418	0.0751632420390278	-16.2667678717121	8.48112651484325e-48	***
df.mm.trans3:probe5	-0.837451697775044	0.0751632420390278	-11.1417718961644	7.93343590977959e-26	***
df.mm.trans3:probe6	-1.05833931744814	0.0751632420390278	-14.0805437436907	5.37487132945302e-38	***
df.mm.trans3:probe7	-0.805912734946806	0.0751632420390278	-10.7221656900902	3.24195559373678e-24	***
df.mm.trans3:probe8	-0.435724150413301	0.0751632420390278	-5.7970377353741	1.21720167104024e-08	***
df.mm.trans3:probe9	-0.796533869862306	0.0751632420390278	-10.5973857467286	9.61287259135975e-24	***
df.mm.trans3:probe10	-0.94444782017859	0.0751632420390278	-12.5652884915235	1.51652245928051e-31	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.0277269828069	0.276550477355215	14.5641657223881	4.03883081068580e-40	***
df.mm.trans1	0.491647633029118	0.221393119480469	2.22069969555892	0.0268325635115506	*  
df.mm.trans2	0.274158797836600	0.221393119480469	1.23833477065571	0.216191005983347	   
df.mm.exp2	0.165085043838358	0.296460469794428	0.556853478485114	0.577884403018415	   
df.mm.exp3	-0.113823116009223	0.296460469794428	-0.383940280767114	0.701190971795879	   
df.mm.exp4	-0.122699723800397	0.296460469794428	-0.413882241654275	0.679143310059752	   
df.mm.exp5	-0.222456828872675	0.296460469794428	-0.750376024928152	0.453392137000934	   
df.mm.exp6	-0.272484503929885	0.296460469794428	-0.91912592636324	0.35848659364853	   
df.mm.exp7	-0.225538294386705	0.296460469794428	-0.760770211769204	0.447164031134624	   
df.mm.exp8	0.27793409022391	0.296460469794428	0.937508094811546	0.348963870399353	   
df.mm.trans1:exp2	-0.355101780576165	0.232562726229334	-1.52690754160662	0.127435860204739	   
df.mm.trans2:exp2	-0.0302586246918529	0.232562726229334	-0.130109520052729	0.896533722875545	   
df.mm.trans1:exp3	-0.162088031853967	0.232562726229334	-0.69696479088454	0.486158752083836	   
df.mm.trans2:exp3	-0.0781717911551257	0.232562726229334	-0.336132072506061	0.73691664563189	   
df.mm.trans1:exp4	-0.266338372056267	0.232562726229334	-1.14523241266800	0.252677696808016	   
df.mm.trans2:exp4	0.065691135459898	0.232562726229334	0.282466311454910	0.777706477954997	   
df.mm.trans1:exp5	-0.103351217624599	0.232562726229334	-0.444401470950606	0.656950580160489	   
df.mm.trans2:exp5	0.127225424843539	0.232562726229334	0.54705853730868	0.584590134321286	   
df.mm.trans1:exp6	-0.0154120717970080	0.232562726229334	-0.06627060168623	0.947189696607439	   
df.mm.trans2:exp6	0.115330180601838	0.232562726229334	0.495909995861111	0.620182556526158	   
df.mm.trans1:exp7	-0.147539344078830	0.232562726229334	-0.634406667271945	0.526114579950973	   
df.mm.trans2:exp7	0.172683487767572	0.232562726229334	0.74252435275155	0.458129167452484	   
df.mm.trans1:exp8	-0.53757236513612	0.232562726229334	-2.31151558055787	0.0212226368994945	*  
df.mm.trans2:exp8	-0.122872010015224	0.232562726229334	-0.528339222743965	0.597505577268476	   
df.mm.trans1:probe2	0.110068185849972	0.159224813988381	0.691275330100272	0.489723273346425	   
df.mm.trans1:probe3	0.169369697779598	0.159224813988381	1.06371421348910	0.287987498624184	   
df.mm.trans1:probe4	0.0455706570059706	0.159224813988381	0.286203235943463	0.774844673113094	   
df.mm.trans1:probe5	-0.0191964415535224	0.159224813988381	-0.120561871436215	0.904087998858605	   
df.mm.trans1:probe6	0.314016538443301	0.159224813988381	1.97215829981259	0.0491592485101541	*  
df.mm.trans2:probe2	0.105665416911003	0.159224813988381	0.663624056227275	0.507246274179777	   
df.mm.trans2:probe3	-0.0286409842903399	0.159224813988381	-0.179877643270036	0.857323755395935	   
df.mm.trans2:probe4	0.140971567535629	0.159224813988381	0.885361797602198	0.37640026473864	   
df.mm.trans2:probe5	0.0951153507202337	0.159224813988381	0.597365123800205	0.550542417496405	   
df.mm.trans2:probe6	0.0787721531911555	0.159224813988381	0.494722846383125	0.621019797918303	   
df.mm.trans3:probe2	-0.275011388553465	0.159224813988381	-1.7271892594174	0.0847703458951297	.  
df.mm.trans3:probe3	-0.0997952212899717	0.159224813988381	-0.626756714548613	0.531113621706371	   
df.mm.trans3:probe4	-0.300764340052626	0.159224813988381	-1.88892882031926	0.0594977223089175	.  
df.mm.trans3:probe5	-0.215316287500122	0.159224813988381	-1.35227846782622	0.176916437402620	   
df.mm.trans3:probe6	-0.136853828790013	0.159224813988381	-0.85950063537207	0.390488993130243	   
df.mm.trans3:probe7	-0.4469584535191	0.159224813988381	-2.80709044227061	0.00520042835294564	** 
df.mm.trans3:probe8	-0.154721495750218	0.159224813988381	-0.97171723348038	0.331675602114268	   
df.mm.trans3:probe9	-0.353865186599354	0.159224813988381	-2.22242487044247	0.0267150543224355	*  
df.mm.trans3:probe10	-0.201700631461414	0.159224813988381	-1.26676631869787	0.205846850703807