chr14.7453_chr14_27189999_27195910_+_1.R 

fitVsDatCorrelation=0.875238715061062
cont.fitVsDatCorrelation=0.245023670835087

fstatistic=11193.8991871596,45,531
cont.fstatistic=2777.30211861193,45,531

residuals=-0.389194737179261,-0.0761955388284667,-0.00692276809193369,0.0707263424900016,0.902263340735443
cont.residuals=-0.525315523622724,-0.183989899667917,-0.0669135665175126,0.115671544161035,1.04008264991714

predictedValues:
Include	Exclude	Both
chr14.7453_chr14_27189999_27195910_+_1.R.tl.Lung	72.702940436292	64.4617337697655	69.292660057859
chr14.7453_chr14_27189999_27195910_+_1.R.tl.cerebhem	68.266600688494	61.2256454324489	76.9523260792368
chr14.7453_chr14_27189999_27195910_+_1.R.tl.cortex	63.1971274581675	64.6021429561569	68.1084918066078
chr14.7453_chr14_27189999_27195910_+_1.R.tl.heart	74.2482855348405	69.6852170436093	86.086040843177
chr14.7453_chr14_27189999_27195910_+_1.R.tl.kidney	72.8032251564045	64.4167776348811	81.1171995490958
chr14.7453_chr14_27189999_27195910_+_1.R.tl.liver	70.906535031491	66.5977075867028	78.5505962370067
chr14.7453_chr14_27189999_27195910_+_1.R.tl.stomach	73.6150998614577	65.9182942326755	70.4064498161937
chr14.7453_chr14_27189999_27195910_+_1.R.tl.testicle	65.5498496746193	65.6452380019767	75.0006692015903


diffExp=8.24120666652648,7.04095525604507,-1.40501549798934,4.56306849123119,8.38644752152334,4.30882744478821,7.69680562878217,-0.0953883273573553
diffExpScore=1.05035136835012
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	59.7086051703081	68.693097845798	66.2884239567264
cerebhem	68.0039125179534	66.2160053541407	64.9735771027293
cortex	76.5057131779567	65.7741927841395	66.3643999224552
heart	69.1237572676031	66.0257146668763	64.6445917967502
kidney	65.7134666890152	79.4578805884644	69.6052252052727
liver	67.2646598717987	67.1989490581572	73.2701239964271
stomach	72.7312228631721	67.4237659377264	67.7667762971628
testicle	65.344292707784	62.0837039948576	68.7500121364873
cont.diffExp=-8.98449267548992,1.78790716381273,10.7315203938172,3.0980426007268,-13.7444138994492,0.0657108136414593,5.30745692544572,3.26058871292634
cont.diffExpScore=18.6257622051833

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

tran.correlation=0.404543937139215
cont.tran.correlation=-0.221041211514348

tran.covariance=0.00084321246675252
cont.tran.covariance=-0.00113247136403037

tran.mean=67.740151281249
cont.tran.mean=67.9543087809845

weightedLogRatios:
wLogRatio
Lung	0.508457587497757
cerebhem	0.453813663030135
cortex	-0.0914127369008797
heart	0.271192716804142
kidney	0.517273219827509
liver	0.265190071199444
stomach	0.468642042248713
testicle	-0.0060834710908026

cont.weightedLogRatios:
wLogRatio
Lung	-0.583056581683346
cerebhem	0.112067094990965
cortex	0.6441188248753
heart	0.193182429498742
kidney	-0.81292171808073
liver	0.00411294537315902
stomach	0.321951556749263
testicle	0.212632915133567

varWeightedLogRatios=0.0559532462375437
cont.varWeightedLogRatios=0.230483815384883

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.99955301609744	0.0707997320585838	56.491075598817	1.08757612222393e-226	***
df.mm.trans1	0.339514452279732	0.0563648942637129	6.023509078031	3.19052157509270e-09	***
df.mm.trans2	0.232438781758884	0.0563648942637129	4.1238218361837	4.32408001757599e-05	***
df.mm.exp2	-0.219313923130008	0.0751531923516172	-2.91822497844017	0.00366949575737508	** 
df.mm.exp3	-0.120710087700614	0.0751531923516172	-1.60618709496532	0.108827285457337	   
df.mm.exp4	-0.118059000480501	0.0751531923516172	-1.57091131841934	0.116798899958248	   
df.mm.exp5	-0.156875257271500	0.0751531923516172	-2.08740643428069	0.0373275559905611	*  
df.mm.exp6	-0.117824814701797	0.0751531923516172	-1.56779520623067	0.117524630134419	   
df.mm.exp7	0.0188666814905895	0.0751531923516172	0.251042981678256	0.801877992787556	   
df.mm.exp8	-0.164535674928978	0.0751531923516172	-2.18933713632774	0.0290068757114727	*  
df.mm.trans1:exp2	0.156352731261769	0.0582134124784272	2.68585407735220	0.00746089711098463	** 
df.mm.trans2:exp2	0.167808295030970	0.0582134124784272	2.88263971972364	0.00410333074023003	** 
df.mm.trans1:exp3	-0.0194128936786794	0.0582134124784272	-0.333478022541171	0.738905116392093	   
df.mm.trans2:exp3	0.122885897777709	0.0582134124784272	2.11095506251670	0.0352429850059260	*  
df.mm.trans1:exp4	0.139091857568987	0.0582134124784272	2.38934382382294	0.0172264674831827	*  
df.mm.trans2:exp4	0.195975428828801	0.0582134124784272	3.36649958291701	0.000816417898674383	***
df.mm.trans1:exp5	0.158253683203939	0.0582134124784272	2.71850895637813	0.00677212232960944	** 
df.mm.trans2:exp5	0.156177605875346	0.0582134124784272	2.68284574337955	0.0075274170625355	** 
df.mm.trans1:exp6	0.0928055866218799	0.0582134124784272	1.59423031000411	0.111479470675431	   
df.mm.trans2:exp6	0.150423198178471	0.0582134124784272	2.58399553941655	0.0100322394597511	*  
df.mm.trans1:exp7	-0.00639834552519735	0.0582134124784272	-0.109911878599600	0.912520787727723	   
df.mm.trans2:exp7	0.00347755459393925	0.0582134124784272	0.0597380302216086	0.952386757389632	   
df.mm.trans1:exp8	0.0609647619548064	0.0582134124784272	1.04726315395784	0.295454679163405	   
df.mm.trans2:exp8	0.182728964043137	0.0582134124784272	3.138949535227	0.00178978591301587	** 
df.mm.trans1:probe2	-0.102739902549390	0.0411630987195055	-2.49592245835239	0.0128652452564830	*  
df.mm.trans1:probe3	-0.115555030629424	0.0411630987195055	-2.80724809900346	0.00518034036600958	** 
df.mm.trans1:probe4	-0.289014333972474	0.0411630987195055	-7.0211996415013	6.7548246961038e-12	***
df.mm.trans1:probe5	-0.300643769375894	0.0411630987195055	-7.3037205343686	1.03093993216744e-12	***
df.mm.trans1:probe6	-0.140388456280217	0.0411630987195055	-3.41054149583963	0.000697681123608148	***
df.mm.trans2:probe2	-0.197100671313705	0.0411630987195055	-4.78828556267819	2.18461090329653e-06	***
df.mm.trans2:probe3	-0.247978278174402	0.0411630987195055	-6.02428597186478	3.17621230260124e-09	***
df.mm.trans2:probe4	-0.264983768739305	0.0411630987195055	-6.43741061733384	2.72081542613804e-10	***
df.mm.trans2:probe5	-0.222194928400805	0.0411630987195055	-5.39791549501388	1.01793471632010e-07	***
df.mm.trans2:probe6	-0.254302803356309	0.0411630987195055	-6.17793147909454	1.29351112770730e-09	***
df.mm.trans3:probe2	-0.153972363115458	0.0411630987195055	-3.74054354276534	0.000203603320239935	***
df.mm.trans3:probe3	-0.339246854044779	0.0411630987195055	-8.24152856801387	1.33767431319807e-15	***
df.mm.trans3:probe4	0.381386010199633	0.0411630987195055	9.26524052036225	4.82426583465383e-19	***
df.mm.trans3:probe5	-0.386326732131726	0.0411630987195055	-9.38526846008953	1.82412362454788e-19	***
df.mm.trans3:probe6	-0.652324243596421	0.0411630987195055	-15.8473065412666	1.34943966255230e-46	***
df.mm.trans3:probe7	-0.464996844766839	0.0411630987195055	-11.2964489854234	1.14564943669073e-26	***
df.mm.trans3:probe8	-0.543165548462678	0.0411630987195055	-13.1954484807844	1.37793283342063e-34	***
df.mm.trans3:probe9	-0.497455161875916	0.0411630987195055	-12.0849784722401	7.12340098774309e-30	***
df.mm.trans3:probe10	-0.310087423222961	0.0411630987195055	-7.5331409167217	2.14680183845906e-13	***
df.mm.trans3:probe11	-0.560758076382073	0.0411630987195055	-13.6228343789957	1.86129249193079e-36	***
df.mm.trans3:probe12	-0.471059942848606	0.0411630987195055	-11.4437434863326	2.94908200933697e-27	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.17577535164908	0.141911923379438	29.4251198363654	1.31490027802151e-113	***
df.mm.trans1	-0.0784882615168219	0.112978542763742	-0.69471830311137	0.487535713756945	   
df.mm.trans2	0.0579463337151947	0.112978542763742	0.512896805868446	0.608236806936894	   
df.mm.exp2	0.113397170485918	0.150638057018322	0.75277903028267	0.45191630220741	   
df.mm.exp3	0.203322612252302	0.150638057018322	1.34974266315431	0.177673658601687	   
df.mm.exp4	0.131928720428664	0.150638057018322	0.87579940315227	0.381535090081952	   
df.mm.exp5	0.192581719589483	0.150638057018322	1.27844001311076	0.201652825034197	   
df.mm.exp6	-0.00296994208466759	0.150638057018322	-0.0197157487520325	0.98427753348301	   
df.mm.exp7	0.156586688784096	0.150638057018322	1.03948956779926	0.299050188748364	   
df.mm.exp8	-0.0474328674624359	0.150638057018322	-0.314879708363914	0.752976682194207	   
df.mm.trans1:exp2	0.0166919198462026	0.116683737227401	0.143052667345341	0.886302852826266	   
df.mm.trans2:exp2	-0.15012369018729	0.116683737227401	-1.28658623518991	0.19879917560732	   
df.mm.trans1:exp3	0.044566657638896	0.116683737227401	0.381944036914429	0.702655678271269	   
df.mm.trans2:exp3	-0.246743783925431	0.116683737227401	-2.11463730755007	0.0349262050397448	*  
df.mm.trans1:exp4	0.0144936109891827	0.116683737227401	0.124212776635159	0.90119381165362	   
df.mm.trans2:exp4	-0.171533164261293	0.116683737227401	-1.47006916591125	0.142135278042544	   
df.mm.trans1:exp5	-0.096753992884874	0.116683737227401	-0.829198611425288	0.407364615021057	   
df.mm.trans2:exp5	-0.0470033683867466	0.116683737227401	-0.402827073451919	0.68723757084321	   
df.mm.trans1:exp6	0.122128777251301	0.116683737227401	1.04666494366124	0.295730333359128	   
df.mm.trans2:exp6	-0.0190211756672147	0.116683737227401	-0.163014796399133	0.870568804115006	   
df.mm.trans1:exp7	0.0407079287615841	0.116683737227401	0.348874056735514	0.72732215354155	   
df.mm.trans2:exp7	-0.175237848809410	0.116683737227401	-1.50181895929417	0.133738280871739	   
df.mm.trans1:exp8	0.137626819266920	0.116683737227401	1.17948586955784	0.238732937092429	   
df.mm.trans2:exp8	-0.0537323197200369	0.116683737227401	-0.460495361194335	0.645349223093495	   
df.mm.trans1:probe2	-0.0256733415973728	0.0825078618476844	-0.311162367105909	0.755799306892234	   
df.mm.trans1:probe3	0.00688711844012653	0.0825078618476844	0.0834722690165048	0.933507484267033	   
df.mm.trans1:probe4	-0.0242957248306523	0.0825078618476845	-0.29446557317779	0.768517245274207	   
df.mm.trans1:probe5	-0.0911450497278963	0.0825078618476844	-1.10468321062733	0.269797184377540	   
df.mm.trans1:probe6	-0.00636992074939395	0.0825078618476845	-0.0772038034527339	0.93849049686976	   
df.mm.trans2:probe2	-0.076088919907819	0.0825078618476844	-0.922202056917735	0.356842006414756	   
df.mm.trans2:probe3	0.00839332632689	0.0825078618476844	0.101727594667096	0.91901129961994	   
df.mm.trans2:probe4	-0.0183859791070383	0.0825078618476844	-0.222839117331391	0.823746413167462	   
df.mm.trans2:probe5	-0.0161076701420551	0.0825078618476844	-0.195225882495792	0.845290794459444	   
df.mm.trans2:probe6	0.0288759768503649	0.0825078618476845	0.349978489367135	0.726493611549476	   
df.mm.trans3:probe2	0.0449840891080634	0.0825078618476844	0.545209730329787	0.585838205478011	   
df.mm.trans3:probe3	0.107514878222071	0.0825078618476844	1.30308646733024	0.193110008597950	   
df.mm.trans3:probe4	0.0311420149970534	0.0825078618476844	0.377443001183861	0.705995225089927	   
df.mm.trans3:probe5	0.099794216437053	0.0825078618476844	1.20951160534593	0.227004571432496	   
df.mm.trans3:probe6	0.0124506756041399	0.0825078618476844	0.150902899739721	0.880109620712112	   
df.mm.trans3:probe7	0.0216694013894572	0.0825078618476844	0.262634383005349	0.792934259970926	   
df.mm.trans3:probe8	0.00170186310310998	0.0825078618476845	0.020626678052229	0.983551207251144	   
df.mm.trans3:probe9	-0.0147617175234421	0.0825078618476844	-0.178912859851989	0.858074367563106	   
df.mm.trans3:probe10	0.0217645774131387	0.0825078618476845	0.263787921850619	0.792045680122684	   
df.mm.trans3:probe11	-0.00572909155126829	0.0825078618476844	-0.069436916955194	0.944667984911708	   
df.mm.trans3:probe12	0.144851378546544	0.0825078618476845	1.75560698462833	0.0797320983550336	.