chr9.24614_chr9_120693406_120694872_+_0.R 

fitVsDatCorrelation=0.91562640912521
cont.fitVsDatCorrelation=0.282455946412722

fstatistic=9677.90170359747,36,324
cont.fstatistic=1692.41875541424,36,324

residuals=-0.346724936647534,-0.0854777950619574,0.00199114023349122,0.0850514244173333,0.351637446910683
cont.residuals=-0.615563458510257,-0.218679005249049,-0.0669641152913779,0.195406079200759,0.864789842396632

predictedValues:
Include	Exclude	Both
chr9.24614_chr9_120693406_120694872_+_0.R.tl.Lung	71.761821733732	49.6322028097195	85.8787123055128
chr9.24614_chr9_120693406_120694872_+_0.R.tl.cerebhem	73.0765932341655	53.7612780530933	80.3047469602108
chr9.24614_chr9_120693406_120694872_+_0.R.tl.cortex	74.1709304207331	55.1305822777012	80.5903096171117
chr9.24614_chr9_120693406_120694872_+_0.R.tl.heart	77.1173521202312	49.4400105732231	74.8883259950448
chr9.24614_chr9_120693406_120694872_+_0.R.tl.kidney	68.2701779507247	49.3163117152354	89.6731514865915
chr9.24614_chr9_120693406_120694872_+_0.R.tl.liver	70.2001712285127	50.6074118316904	96.8195230893424
chr9.24614_chr9_120693406_120694872_+_0.R.tl.stomach	105.221382098047	48.6398901060363	80.56797662751
chr9.24614_chr9_120693406_120694872_+_0.R.tl.testicle	79.1769923838054	50.5161955011587	86.0520493293194


diffExp=22.1296189240124,19.3153151810723,19.0403481430319,27.677341547008,18.9538662354892,19.5927593968223,56.5814919920104,28.6607968826467
diffExpScore=0.995304095908519
diffExp1.5=0,0,0,1,0,0,1,1
diffExp1.5Score=0.75
diffExp1.4=1,0,0,1,0,0,1,1
diffExp1.4Score=0.8
diffExp1.3=1,1,1,1,1,1,1,1
diffExp1.3Score=0.888888888888889
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	66.5008719787084	69.8044910223912	59.7300842239604
cerebhem	62.276498707565	57.716642824834	65.8964644948881
cortex	69.4128748636935	73.0075303158518	63.3019483274179
heart	63.6897207855519	61.9446432625149	63.1389362999125
kidney	71.5149642509332	68.4973699145287	64.1321723435211
liver	66.660039624761	71.1921776810394	56.4185506603185
stomach	65.1896961217506	66.1604617955408	68.1563219075169
testicle	71.4206228062732	76.6933505441923	68.715180552044
cont.diffExp=-3.30361904368273,4.55985588273104,-3.59465545215834,1.74507752303698,3.01759433640449,-4.53213805627837,-0.970765673790254,-5.27272773791913
cont.diffExpScore=2.88689357505419

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=-0.341911435112703
cont.tran.correlation=0.83679476957845

tran.covariance=-0.00203043558448139
cont.tran.covariance=0.00395888172013936

tran.mean=64.127456502363
cont.tran.mean=67.6051222812581

weightedLogRatios:
wLogRatio
Lung	1.50766496875378
cerebhem	1.27018776943274
cortex	1.23355572618310
heart	1.83297468916293
kidney	1.32066664689416
liver	1.33771886929168
stomach	3.29502526267046
testicle	1.86362311280746

cont.weightedLogRatios:
wLogRatio
Lung	-0.204670105219828
cerebhem	0.311268766975759
cortex	-0.215356833942933
heart	0.115021337096486
kidney	0.183152228633348
liver	-0.278401967594092
stomach	-0.0618564849858871
testicle	-0.306581114231682

varWeightedLogRatios=0.471790265955963
cont.varWeightedLogRatios=0.0544432229491902

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.49725853047634	0.0764486075034938	45.7465301812923	2.00576666805814e-143	***
df.mm.trans1	0.787991658457425	0.0647511719625963	12.1695350767181	2.57247118127832e-28	***
df.mm.trans2	0.376052702690582	0.0647511719625963	5.80765863060842	1.51242748903803e-08	***
df.mm.exp2	0.165176349822840	0.0901738578850646	1.83175427664826	0.0679059659306647	.  
df.mm.exp3	0.201641981966214	0.0901738578850646	2.23614678018131	0.0260225896661554	*  
df.mm.exp4	0.205033826642213	0.0901738578850646	2.27376128127454	0.0236342185636541	*  
df.mm.exp5	-0.0994999773496345	0.0901738578850646	-1.10342376031485	0.270662042196132	   
df.mm.exp6	-0.122456362497118	0.0901738578850646	-1.35800292201317	0.175407679867526	   
df.mm.exp7	0.426352753228211	0.0901738578850646	4.72811924905819	3.38581173204706e-06	***
df.mm.exp8	0.113970907956523	0.0901738578850646	1.26390187388667	0.207173814515741	   
df.mm.trans1:exp2	-0.147020840245006	0.0780928516857136	-1.88264145912733	0.0606448157312673	.  
df.mm.trans2:exp2	-0.0852627538366117	0.0780928516857136	-1.09181252824207	0.275726716205037	   
df.mm.trans1:exp3	-0.168622285768868	0.0780928516857137	-2.15925378736958	0.0315640521714962	*  
df.mm.trans2:exp3	-0.0965772607727113	0.0780928516857137	-1.23669783710023	0.217094956627503	   
df.mm.trans1:exp4	-0.133058115377232	0.0780928516857137	-1.70384500636149	0.0893688498634538	.  
df.mm.trans2:exp4	-0.208913672888221	0.0780928516857136	-2.67519585184312	0.00784779706208386	** 
df.mm.trans1:exp5	0.0496204114419265	0.0780928516857136	0.635402733679452	0.525614284912132	   
df.mm.trans2:exp5	0.0931149968537344	0.0780928516857137	1.19236261506338	0.233991628920704	   
df.mm.trans1:exp6	0.100454508771218	0.0780928516857136	1.28634704205065	0.199240390977173	   
df.mm.trans2:exp6	0.141914533695604	0.0780928516857137	1.81725382838806	0.070101906613433	.  
df.mm.trans1:exp7	-0.0436388256021878	0.0780928516857137	-0.558806915872571	0.576679505405421	   
df.mm.trans2:exp7	-0.446548648161099	0.0780928516857136	-5.71817571675118	2.4466513939025e-08	***
df.mm.trans1:exp8	-0.0156377554512734	0.0780928516857136	-0.200245670553918	0.841414080169438	   
df.mm.trans2:exp8	-0.0963167933512923	0.0780928516857137	-1.23336248161255	0.218334580530775	   
df.mm.trans1:probe2	-0.0969235481333591	0.0390464258428568	-2.48226428005037	0.0135612359337160	*  
df.mm.trans1:probe3	-0.225706638176098	0.0390464258428568	-5.78046859101673	1.75150233849725e-08	***
df.mm.trans1:probe4	0.0445800571286896	0.0390464258428568	1.14171927817678	0.254413811579348	   
df.mm.trans1:probe5	-0.0673242413783415	0.0390464258428568	-1.72421008901786	0.0856237305945699	.  
df.mm.trans1:probe6	0.238296105320826	0.0390464258428568	6.10289162649236	2.97254907537546e-09	***
df.mm.trans2:probe2	0.0276257564024806	0.0390464258428568	0.707510503359797	0.479757880761732	   
df.mm.trans2:probe3	0.0942120663989519	0.0390464258428568	2.41282177216707	0.0163844387330726	*  
df.mm.trans2:probe4	0.0423059070743451	0.0390464258428568	1.08347707020884	0.279402349290151	   
df.mm.trans2:probe5	0.0898328491974134	0.0390464258428568	2.30066766056764	0.0220451727427116	*  
df.mm.trans2:probe6	0.0279811817204682	0.0390464258428568	0.716613137219757	0.47412906286621	   
df.mm.trans3:probe2	-0.700368484217646	0.0390464258428568	-17.9368141667126	1.88969821994682e-50	***
df.mm.trans3:probe3	0.0752677456978979	0.0390464258428568	1.92764751377795	0.0547728732884652	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.31307158302357	0.182413265368863	23.6445061947769	1.59401887403745e-72	***
df.mm.trans1	-0.0735634943086743	0.154502130252905	-0.47613255680202	0.634300844753484	   
df.mm.trans2	-0.101029369190179	0.154502130252905	-0.653902758653253	0.513638286960057	   
df.mm.exp2	-0.354032686819333	0.215162949396701	-1.64541659152754	0.100853657217402	   
df.mm.exp3	0.0296412577640576	0.215162949396701	0.137761904859406	0.890514165911009	   
df.mm.exp4	-0.218150912481469	0.215162949396701	-1.01388697772152	0.311393217076217	   
df.mm.exp5	-0.0173216717104075	0.215162949396701	-0.080504899932707	0.935885402768834	   
df.mm.exp6	0.079113006611295	0.215162949396701	0.367688799735834	0.713345364822145	   
df.mm.exp7	-0.205497058477123	0.215162949396701	-0.955076415587908	0.340251087037181	   
df.mm.exp8	0.0253539369760334	0.215162949396701	0.117835979880011	0.906270636111438	   
df.mm.trans1:exp2	0.288401753598866	0.186336580130728	1.54774630615487	0.122659570743663	   
df.mm.trans2:exp2	0.163879906922032	0.186336580130728	0.879483281313089	0.379791110699296	   
df.mm.trans1:exp3	0.0132160492728888	0.186336580130729	0.0709256833178797	0.943500660433159	   
df.mm.trans2:exp3	0.0152229840823726	0.186336580130729	0.0816961654640899	0.934938771440444	   
df.mm.trans1:exp4	0.17495903285695	0.186336580130729	0.938940881786087	0.348460525980535	   
df.mm.trans2:exp4	0.0986936990999295	0.186336580130728	0.529652841276194	0.596715382774496	   
df.mm.trans1:exp5	0.0900133296974454	0.186336580130728	0.483068486253717	0.629373362271128	   
df.mm.trans2:exp5	-0.00158132816039305	0.186336580130729	-0.00848640754962675	0.993234130550447	   
df.mm.trans1:exp6	-0.076722399338641	0.186336580130728	-0.411740943645176	0.680801559236795	   
df.mm.trans2:exp6	-0.0594284072527217	0.186336580130729	-0.31893043873097	0.749984771187216	   
df.mm.trans1:exp7	0.185583419940795	0.186336580130729	0.995958065832243	0.32001374634528	   
df.mm.trans2:exp7	0.151881740155650	0.186336580130728	0.815093526183073	0.415617519241734	   
df.mm.trans1:exp8	0.0460176654488898	0.186336580130728	0.246959912093509	0.805095654591047	   
df.mm.trans2:exp8	0.0687627243064055	0.186336580130729	0.369024290658139	0.712350653272365	   
df.mm.trans1:probe2	-0.0183606066260097	0.0931682900653642	-0.197069266948319	0.843896898061425	   
df.mm.trans1:probe3	-0.0242609602117116	0.0931682900653643	-0.260399328942184	0.794721172452873	   
df.mm.trans1:probe4	-0.0795168779392208	0.0931682900653642	-0.853475768240825	0.394026046705064	   
df.mm.trans1:probe5	-0.0869664251526728	0.0931682900653642	-0.93343373686111	0.351291160265034	   
df.mm.trans1:probe6	-0.171532388165832	0.0931682900653643	-1.84110267608743	0.0665206144139056	.  
df.mm.trans2:probe2	0.128973679021644	0.0931682900653642	1.38430874851475	0.167216624696960	   
df.mm.trans2:probe3	-0.00459598433948277	0.0931682900653642	-0.0493299204724951	0.960686770584833	   
df.mm.trans2:probe4	0.0503271202223479	0.0931682900653642	0.540174346733635	0.589447895900069	   
df.mm.trans2:probe5	0.0463134844241653	0.0931682900653642	0.497094927809376	0.619459252355146	   
df.mm.trans2:probe6	0.0818869171124687	0.0931682900653643	0.87891402809925	0.380099245114676	   
df.mm.trans3:probe2	-0.053512852613184	0.0931682900653642	-0.574367658520306	0.566117584330802	   
df.mm.trans3:probe3	-0.0924158554972287	0.0931682900653643	-0.991923919955946	0.321974838601195