chr8.23293_chr8_40351344_40357303_-_2.R 

fitVsDatCorrelation=0.834955175052804
cont.fitVsDatCorrelation=0.242619462091245

fstatistic=5733.8305151488,62,922
cont.fstatistic=1835.01447976277,62,922

residuals=-0.583605760623742,-0.112988629321710,-0.0123370477610126,0.0796559282196932,1.55603653458657
cont.residuals=-0.719913273945783,-0.248756179900383,-0.0913750270128118,0.16133973528656,2.21027771832732

predictedValues:
Include	Exclude	Both
chr8.23293_chr8_40351344_40357303_-_2.R.tl.Lung	60.3429800211832	42.8707485239953	68.116126492374
chr8.23293_chr8_40351344_40357303_-_2.R.tl.cerebhem	68.9273811126695	52.8420338026281	79.0348270144645
chr8.23293_chr8_40351344_40357303_-_2.R.tl.cortex	59.070465771296	44.6993098637844	64.1851991854988
chr8.23293_chr8_40351344_40357303_-_2.R.tl.heart	60.6610394604045	47.2055185894635	66.7992055913422
chr8.23293_chr8_40351344_40357303_-_2.R.tl.kidney	60.2962376018202	44.1457742661528	65.5419505795425
chr8.23293_chr8_40351344_40357303_-_2.R.tl.liver	97.9067891114545	54.2520997733209	86.0238322444397
chr8.23293_chr8_40351344_40357303_-_2.R.tl.stomach	64.1799813687126	48.464829288247	72.2435739628198
chr8.23293_chr8_40351344_40357303_-_2.R.tl.testicle	61.8023582509932	49.972710182208	70.309773472048


diffExp=17.4722314971879,16.0853473100413,14.3711559075116,13.455520870941,16.1504633356674,43.6546893381337,15.7151520804656,11.8296480687852
diffExpScore=0.993321499404663
diffExp1.5=0,0,0,0,0,1,0,0
diffExp1.5Score=0.5
diffExp1.4=1,0,0,0,0,1,0,0
diffExp1.4Score=0.666666666666667
diffExp1.3=1,1,1,0,1,1,1,0
diffExp1.3Score=0.857142857142857
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	58.4087605774575	53.8380088818548	66.4545448541402
cerebhem	64.4012201768385	57.5278814419354	57.684993868684
cortex	60.5824515367261	70.166561436853	58.9101404120721
heart	60.2109516729786	59.2424739454351	52.2891160759403
kidney	59.2971861823028	53.4170770424878	66.8654024335245
liver	64.449431105292	50.8130023022878	59.8614722368387
stomach	60.333992100161	53.7958910835407	59.9172862899966
testicle	58.1587981119279	55.4595908634275	63.7430397132662
cont.diffExp=4.57075169560267,6.87333873490314,-9.58410990012682,0.968477727543508,5.88010913981498,13.6364288030043,6.53810101662028,2.69920724850043
cont.diffExpScore=1.5576100309077

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

tran.correlation=0.750856390163397
cont.tran.correlation=-0.0630961176276667

tran.covariance=0.0109257688401672
cont.tran.covariance=-0.000261953661758667

tran.mean=57.3525160617709
cont.tran.mean=58.7564549038442

weightedLogRatios:
wLogRatio
Lung	1.34318787779555
cerebhem	1.08960868642105
cortex	1.09818291856904
heart	0.99812399628771
kidney	1.22943851042190
liver	2.53201385801821
stomach	1.12938421729675
testicle	0.853620447394005

cont.weightedLogRatios:
wLogRatio
Lung	0.328122282499369
cerebhem	0.463719741795622
cortex	-0.613526166715424
heart	0.0663173143570122
kidney	0.420894550875939
liver	0.962091707988676
stomach	0.463674292452937
testicle	0.191963162219776

varWeightedLogRatios=0.275313158005125
cont.varWeightedLogRatios=0.200924458095345

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.33221536636078	0.114611531879680	37.7991227873016	1.38052488024582e-189	***
df.mm.trans1	0.382858380408744	0.103696815905144	3.69209388993161	0.000235476315446629	***
df.mm.trans2	-0.6383017767624	0.0943385460180487	-6.76607604955328	2.34950014177614e-11	***
df.mm.exp2	0.193451498607117	0.128912057300073	1.50064705085587	0.133789227736447	   
df.mm.exp3	0.0798961174649655	0.128912057300073	0.619772262876766	0.535560862991398	   
df.mm.exp4	0.121100885584906	0.128912057300073	0.939406973414561	0.347767866627619	   
df.mm.exp5	0.0670561427156197	0.128912057300073	0.520169673186822	0.603070192836477	   
df.mm.exp6	0.486012845455194	0.128912057300073	3.7701116220951	0.000173559899976417	***
df.mm.exp7	0.125465960331782	0.128912057300073	0.973267845999315	0.330675465862435	   
df.mm.exp8	0.145487399574529	0.128912057300073	1.12857868085895	0.259369176193510	   
df.mm.trans1:exp2	-0.0604426155347966	0.125063065567971	-0.483297089035023	0.628999552513726	   
df.mm.trans2:exp2	0.0156657293572499	0.106792922959581	0.146692579649487	0.883406743762747	   
df.mm.trans1:exp3	-0.101209670773896	0.125063065567971	-0.809269070082795	0.418569180777292	   
df.mm.trans2:exp3	-0.0381277960328190	0.106792922959581	-0.357025493601757	0.72115441798331	   
df.mm.trans1:exp4	-0.115843867296078	0.125063065567971	-0.926283605555129	0.354541003799465	   
df.mm.trans2:exp4	-0.0247798213388775	0.106792922959581	-0.232036174796490	0.816561407521764	   
df.mm.trans1:exp5	-0.0678310552626831	0.125063065567971	-0.542374800702589	0.587691400331825	   
df.mm.trans2:exp5	-0.0377486741366145	0.106792922959581	-0.353475427869893	0.723812852963233	   
df.mm.trans1:exp6	-0.00204157058355229	0.125063065567971	-0.0163243286439569	0.986979180371294	   
df.mm.trans2:exp6	-0.250560889063912	0.106792922959581	-2.34623121195721	0.0191752877216719	*  
df.mm.trans1:exp7	-0.063819234618078	0.125063065567971	-0.5102964198762	0.609965951582091	   
df.mm.trans2:exp7	-0.00281733554454196	0.106792922959581	-0.0263812944384738	0.97895892253363	   
df.mm.trans1:exp8	-0.121590496108312	0.125063065567971	-0.972233453227068	0.331189410295818	   
df.mm.trans2:exp8	0.00779991971747735	0.106792922959581	0.0730377959635906	0.941791882248282	   
df.mm.trans1:probe2	-0.66999862446256	0.0625315327839855	-10.7145722267366	2.50496200037541e-25	***
df.mm.trans1:probe3	-0.130933442235082	0.0625315327839855	-2.09387866258437	0.0365433908548528	*  
df.mm.trans1:probe4	-0.560508892734767	0.0625315327839855	-8.96361991750688	1.71381030059108e-18	***
df.mm.trans1:probe5	-0.405054085687409	0.0625315327839855	-6.47759726419411	1.51424854044475e-10	***
df.mm.trans1:probe6	-0.932811146821505	0.0625315327839855	-14.9174521284148	3.06837145142926e-45	***
df.mm.trans1:probe7	-0.691085361045109	0.0625315327839855	-11.0517898774760	9.43428876195565e-27	***
df.mm.trans1:probe8	-0.901701211006412	0.0625315327839855	-14.4199441603539	1.17032504453791e-42	***
df.mm.trans1:probe9	-0.898069847757781	0.0625315327839855	-14.3618716473840	2.32325263327589e-42	***
df.mm.trans1:probe10	-0.528397077643849	0.0625315327839855	-8.45008996451744	1.12511326299655e-16	***
df.mm.trans1:probe11	-0.888856322918884	0.0625315327839855	-14.2145295876471	1.31301616459177e-41	***
df.mm.trans1:probe12	-0.776389785977024	0.0625315327839855	-12.4159724128154	7.67450849747398e-33	***
df.mm.trans1:probe13	-0.870784789325017	0.0625315327839855	-13.9255308570979	3.79572578057991e-40	***
df.mm.trans1:probe14	-0.669628881885848	0.0625315327839855	-10.7086593287114	2.65138545748178e-25	***
df.mm.trans1:probe15	-0.77276633372407	0.0625315327839855	-12.3580264119478	1.42566562903096e-32	***
df.mm.trans1:probe16	-0.763756748629679	0.0625315327839855	-12.2139457426714	6.59096386007333e-32	***
df.mm.trans1:probe17	-0.955500173427272	0.0625315327839855	-15.2802934917338	3.72449475314323e-47	***
df.mm.trans1:probe18	-0.717914205691038	0.0625315327839855	-11.4808349280525	1.30390315935756e-28	***
df.mm.trans1:probe19	-1.00718615599729	0.0625315327839855	-16.1068521937021	1.28158716207178e-51	***
df.mm.trans1:probe20	-0.746271946585041	0.0625315327839855	-11.9343299829708	1.24030052924753e-30	***
df.mm.trans1:probe21	-0.942495456919922	0.0625315327839855	-15.0723229538569	4.7046481890696e-46	***
df.mm.trans1:probe22	-0.936614050834798	0.0625315327839855	-14.9782679095733	1.47133772173714e-45	***
df.mm.trans1:probe23	-0.0401432343553974	0.0625315327839855	-0.6419678611441	0.521053623760327	   
df.mm.trans1:probe24	-0.115759239089216	0.0625315327839855	-1.85121384260810	0.0644584148143851	.  
df.mm.trans1:probe25	-0.778697201905053	0.0625315327839855	-12.4528724506891	5.16788252018685e-33	***
df.mm.trans1:probe26	-0.563463362008646	0.0625315327839855	-9.01086758827941	1.15440416332395e-18	***
df.mm.trans1:probe27	-0.408082300674404	0.0625315327839855	-6.52602427137233	1.11299456734587e-10	***
df.mm.trans1:probe28	-0.689818959082429	0.0625315327839855	-11.0315376638120	1.15126199995669e-26	***
df.mm.trans1:probe29	-0.491980273268514	0.0625315327839855	-7.86771491701722	1.00859174085765e-14	***
df.mm.trans1:probe30	-0.935925865302955	0.0625315327839855	-14.9672624935663	1.68086496410935e-45	***
df.mm.trans1:probe31	-0.884842107225165	0.0625315327839855	-14.1503345245325	2.78261458634653e-41	***
df.mm.trans1:probe32	-0.850582364241485	0.0625315327839855	-13.6024550554328	1.54762096760676e-38	***
df.mm.trans2:probe2	0.00075614671602035	0.0625315327839855	0.0120922466211159	0.99035463418705	   
df.mm.trans2:probe3	0.00897673927896008	0.0625315327839855	0.143555401240045	0.885882928860853	   
df.mm.trans2:probe4	0.0880980517567276	0.0625315327839855	1.40885802465552	0.159214300943645	   
df.mm.trans2:probe5	0.333912753660367	0.0625315327839855	5.33990994293815	1.17162816315623e-07	***
df.mm.trans2:probe6	0.146741669215771	0.0625315327839855	2.34668274840932	0.0191522098619395	*  
df.mm.trans3:probe2	0.647632038140765	0.0625315327839855	10.3568873064091	7.45472652154287e-24	***
df.mm.trans3:probe3	-0.21430597463186	0.0625315327839855	-3.42716650449267	0.000636881350911863	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.68769700111135	0.202041590164027	18.2521677745533	8.90844399885953e-64	***
df.mm.trans1	0.313937424174402	0.182800711558555	1.71737528534642	0.0862464278442651	.  
df.mm.trans2	0.230304162479609	0.166303595621236	1.38484175053038	0.166435861772026	   
df.mm.exp2	0.30547782353585	0.227251103105101	1.34423032214972	0.179204564841835	   
df.mm.exp3	0.421936485173179	0.227251103105101	1.85669719269983	0.0636730318432709	.  
df.mm.exp4	0.365777350312180	0.227251103105101	1.60957348639585	0.10783330592597	   
df.mm.exp5	0.00108325099523683	0.227251103105101	0.00476675791860004	0.996197722999035	   
df.mm.exp6	0.145072665234522	0.227251103105101	0.63838046659526	0.523384572148491	   
df.mm.exp7	0.135200289293484	0.227251103105101	0.594937879051594	0.552030973016328	   
df.mm.exp8	0.0670444206420954	0.227251103105101	0.295023521232758	0.768042329913681	   
df.mm.trans1:exp2	-0.207811132231507	0.220465953327167	-0.942599658111922	0.346132628412636	   
df.mm.trans2:exp2	-0.239187801131284	0.188258647442819	-1.27052756609193	0.204217268183236	   
df.mm.trans1:exp3	-0.385397101107563	0.220465953327167	-1.74810257679852	0.0807791074996087	.  
df.mm.trans2:exp3	-0.157044322949964	0.188258647442819	-0.8341944717183	0.404387478933989	   
df.mm.trans1:exp4	-0.335388981536853	0.220465953327167	-1.52127335978786	0.128534113977436	   
df.mm.trans2:exp4	-0.270118302900568	0.188258647442819	-1.43482547319699	0.151675942348567	   
df.mm.trans1:exp5	0.0140127148594504	0.220465953327167	0.0635595412714626	0.949334724634501	   
df.mm.trans2:exp5	-0.00893246386708045	0.188258647442819	-0.0474478277009483	0.962166586218514	   
df.mm.trans1:exp6	-0.0466576512756384	0.220465953327167	-0.211632002907947	0.832440910607626	   
df.mm.trans2:exp6	-0.202900095085152	0.188258647442819	-1.07777304172325	0.281416950048289	   
df.mm.trans1:exp7	-0.102770516439972	0.220465953327167	-0.466151416529437	0.641217229434655	   
df.mm.trans2:exp7	-0.135982901471939	0.188258647442819	-0.722319549827013	0.470281197257403	   
df.mm.trans1:exp8	-0.0713331413028427	0.220465953327167	-0.323556269012593	0.74634737454918	   
df.mm.trans2:exp8	-0.0373694601463495	0.188258647442819	-0.198500630138119	0.842697151850632	   
df.mm.trans1:probe2	-0.00638066592428401	0.110232976663584	-0.0578834584478015	0.953854001356801	   
df.mm.trans1:probe3	0.148233595858717	0.110232976663584	1.34473004671829	0.179043132418951	   
df.mm.trans1:probe4	0.0418443026637864	0.110232976663584	0.379598772801805	0.704330685712544	   
df.mm.trans1:probe5	0.0916652538343234	0.110232976663584	0.831559272086733	0.405873064145631	   
df.mm.trans1:probe6	0.108034497545955	0.110232976663584	0.980056066848872	0.32731553118847	   
df.mm.trans1:probe7	0.0489145859804407	0.110232976663584	0.443738230255012	0.657335965793161	   
df.mm.trans1:probe8	0.0752386725532218	0.110232976663584	0.682542328352796	0.495067531589015	   
df.mm.trans1:probe9	-0.00661181342168831	0.110232976663584	-0.0599803581632988	0.952184276464497	   
df.mm.trans1:probe10	0.166011826336192	0.110232976663584	1.50600874040477	0.132407438329964	   
df.mm.trans1:probe11	0.0300269181948147	0.110232976663584	0.272395059116047	0.785379261381295	   
df.mm.trans1:probe12	0.0911128143349183	0.110232976663584	0.826547709157692	0.408707309149913	   
df.mm.trans1:probe13	-0.0104191077423963	0.110232976663584	-0.094518972976608	0.924717448400767	   
df.mm.trans1:probe14	-0.148776493636092	0.110232976663584	-1.34965505005039	0.177457936333633	   
df.mm.trans1:probe15	0.0233818042743182	0.110232976663584	0.212112608967064	0.832066064078925	   
df.mm.trans1:probe16	0.0765287773758773	0.110232976663584	0.694245766486312	0.487702981772765	   
df.mm.trans1:probe17	0.184871774118400	0.110232976663584	1.67710044411306	0.093861799140355	.  
df.mm.trans1:probe18	0.149923912419123	0.110232976663584	1.36006408387819	0.174142095973310	   
df.mm.trans1:probe19	0.101636908809323	0.110232976663584	0.92201908980019	0.356759817946574	   
df.mm.trans1:probe20	0.0589736011004191	0.110232976663584	0.53499055260386	0.592785388005282	   
df.mm.trans1:probe21	-0.0106024986921587	0.110232976663584	-0.096182639833052	0.923396419764233	   
df.mm.trans1:probe22	0.04439165989568	0.110232976663584	0.402707621977382	0.687256678867814	   
df.mm.trans1:probe23	0.0434270533949089	0.110232976663584	0.393957005510634	0.693703875687866	   
df.mm.trans1:probe24	0.091510695632301	0.110232976663584	0.830157167138645	0.406664825187492	   
df.mm.trans1:probe25	0.0535307554854935	0.110232976663584	0.485614714450307	0.627355738150003	   
df.mm.trans1:probe26	0.135248910820265	0.110232976663584	1.22693693769177	0.220159499641440	   
df.mm.trans1:probe27	0.131255423094064	0.110232976663584	1.19070923299693	0.234074214688818	   
df.mm.trans1:probe28	-0.00350874528203322	0.110232976663584	-0.0318302688381667	0.97461429672474	   
df.mm.trans1:probe29	0.234164852522702	0.110232976663584	2.12427224239206	0.0339129731402929	*  
df.mm.trans1:probe30	0.125468557218858	0.110232976663584	1.13821254779113	0.255327411613717	   
df.mm.trans1:probe31	0.207735702515241	0.110232976663584	1.88451504080510	0.0598097013691945	.  
df.mm.trans1:probe32	0.0272676802309543	0.110232976663584	0.24736409245458	0.80468153274721	   
df.mm.trans2:probe2	0.079959542575462	0.110232976663584	0.725368623760274	0.468409977583021	   
df.mm.trans2:probe3	0.0596988036444539	0.110232976663584	0.541569369270021	0.588246036755483	   
df.mm.trans2:probe4	0.0755239384766514	0.110232976663584	0.685130173950944	0.493433986103558	   
df.mm.trans2:probe5	0.190602477984925	0.110232976663584	1.72908764467659	0.0841281399961095	.  
df.mm.trans2:probe6	0.206022087658995	0.110232976663584	1.86896964859932	0.0619439079977526	.  
df.mm.trans3:probe2	0.0045854840747282	0.110232976663584	0.0415981153146439	0.96682808184762	   
df.mm.trans3:probe3	-0.110846713621054	0.110232976663584	-1.00556763480445	0.314887425692098