chr12.5790_chr12_16661536_16666933_-_2.R 

fitVsDatCorrelation=0.961475803503352
cont.fitVsDatCorrelation=0.225772912927846

fstatistic=8657.19094219403,50,646
cont.fstatistic=677.419649355028,50,646

residuals=-0.873444399704183,-0.109387051533265,0.0065299757169386,0.109032113961279,0.564722254029426
cont.residuals=-1.10325213097903,-0.547709222086818,-0.086507594118473,0.469416164030032,1.7914080290807

predictedValues:
Include	Exclude	Both
chr12.5790_chr12_16661536_16666933_-_2.R.tl.Lung	94.0972272650564	108.057274279489	74.2582220371684
chr12.5790_chr12_16661536_16666933_-_2.R.tl.cerebhem	90.2653593752999	85.5126986020727	62.5693635482589
chr12.5790_chr12_16661536_16666933_-_2.R.tl.cortex	90.7577357548148	115.255355606609	60.2119540549854
chr12.5790_chr12_16661536_16666933_-_2.R.tl.heart	125.702562274811	133.431742631267	146.702194130740
chr12.5790_chr12_16661536_16666933_-_2.R.tl.kidney	96.8021547638526	114.325012581340	70.7176751322022
chr12.5790_chr12_16661536_16666933_-_2.R.tl.liver	103.060961428242	125.619286725053	75.8666683542962
chr12.5790_chr12_16661536_16666933_-_2.R.tl.stomach	92.5429249653195	143.770458239570	57.0286027557317
chr12.5790_chr12_16661536_16666933_-_2.R.tl.testicle	96.428877708232	125.443861830723	69.6092392922173


diffExp=-13.9600470144322,4.75266077322721,-24.497619851794,-7.72918035645604,-17.5228578174876,-22.5583252968108,-51.2275332742509,-29.0149841224911
diffExpScore=1.0522575077945
diffExp1.5=0,0,0,0,0,0,-1,0
diffExp1.5Score=0.5
diffExp1.4=0,0,0,0,0,0,-1,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,0,0,-1,-1
diffExp1.3Score=0.666666666666667
diffExp1.2=0,0,-1,0,0,-1,-1,-1
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	114.115333561186	87.2831700254841	96.3811934951147
cerebhem	103.367466512670	107.061510252068	83.4833907681951
cortex	120.753212878787	95.467584575541	155.271296842471
heart	105.480214987391	101.294982745188	96.496520135039
kidney	109.236688290771	85.8949365739208	121.906169554514
liver	93.8674412863239	99.5806951859022	124.456983099304
stomach	107.45366878728	103.270516513816	95.0637856171818
testicle	118.635141309786	102.584925688476	92.4757986248
cont.diffExp=26.8321635357019,-3.69404373939855,25.2856283032457,4.18523224220311,23.3417517168499,-5.71325389957836,4.18315227346352,16.0502156213103
cont.diffExpScore=1.19475708432254

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=1,0,0,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=1,0,1,0,1,0,0,0
cont.diffExp1.2Score=0.75

tran.correlation=0.432339906354281
cont.tran.correlation=-0.294264362257197

tran.covariance=0.00767512997272493
cont.tran.covariance=-0.00191316150518266

tran.mean=108.817093376985
cont.tran.mean=103.459218073412

weightedLogRatios:
wLogRatio
Lung	-0.638197789087521
cerebhem	0.242086118821529
cortex	-1.10581200218824
heart	-0.290227788176147
kidney	-0.77462350171934
liver	-0.937081944517543
stomach	-2.09168544320454
testicle	-1.23643467591717

cont.weightedLogRatios:
wLogRatio
Lung	1.23389246274287
cerebhem	-0.163481944697509
cortex	1.09874588982314
heart	0.187787813844234
kidney	1.09939021606749
liver	-0.270101488607663
stomach	0.184927618844349
testicle	0.683690342319833

varWeightedLogRatios=0.47436407728017
cont.varWeightedLogRatios=0.359963018697271

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.30467344787183	0.100866359967711	42.6769980521734	3.78670032897730e-190	***
df.mm.trans1	-0.182679311467139	0.09038209575964	-2.02118915180892	0.0436721187711236	*  
df.mm.trans2	0.117659468242295	0.0834024094689957	1.41074423378660	0.158801403102956	   
df.mm.exp2	-0.104298580052630	0.114325312919963	-0.912296475633938	0.361952991821689	   
df.mm.exp3	0.238031479091834	0.114325312919963	2.08205403521156	0.0377305483452132	*  
df.mm.exp4	-0.180337564471445	0.114325312919963	-1.57740713640290	0.115191410307788	   
df.mm.exp5	0.133577611835389	0.114325312919963	1.16839926717632	0.243076751324774	   
df.mm.exp6	0.220157556599544	0.114325312919963	1.92571138426423	0.0545790084668137	.  
df.mm.exp7	0.532896155369216	0.114325312919963	4.66122630027074	3.81990728722435e-06	***
df.mm.exp8	0.238325275248122	0.114325312919963	2.0846238611651	0.0374956447638546	*  
df.mm.trans1:exp2	0.0627237694458027	0.109004908872981	0.575421511694416	0.565206630528679	   
df.mm.trans2:exp2	-0.129697937329550	0.0954441570838429	-1.35888818438217	0.174656271666901	   
df.mm.trans1:exp3	-0.274166347426098	0.109004908872981	-2.51517431885176	0.0121389474143465	*  
df.mm.trans2:exp3	-0.173542732781402	0.0954441570838429	-1.81826460711422	0.0694866764850833	.  
df.mm.trans1:exp4	0.469927483584129	0.109004908872981	4.31106716608255	1.87834619262291e-05	***
df.mm.trans2:exp4	0.391266216447988	0.0954441570838429	4.09942555314602	4.66990950597395e-05	***
df.mm.trans1:exp5	-0.105236938167041	0.109004908872981	-0.965433018155809	0.334689240301407	   
df.mm.trans2:exp5	-0.077193636200692	0.0954441570838429	-0.808783256715038	0.418937587051159	   
df.mm.trans1:exp6	-0.129165465246055	0.109004908872981	-1.18495090341818	0.236472594737625	   
df.mm.trans2:exp6	-0.0695631615842594	0.0954441570838429	-0.728836250532881	0.466365971300855	   
df.mm.trans1:exp7	-0.549552145134905	0.109004908872981	-5.04153575115847	6.00520939042012e-07	***
df.mm.trans2:exp7	-0.247339571588027	0.0954441570838428	-2.5914584941093	0.00977292427399028	** 
df.mm.trans1:exp8	-0.213848137526021	0.109004908872981	-1.96182116692754	0.0502123024020707	.  
df.mm.trans2:exp8	-0.0891283368001393	0.0954441570838428	-0.933827062057289	0.350742013076778	   
df.mm.trans1:probe2	-0.139578161315353	0.0545024544364905	-2.56095184626957	0.0106646334204892	*  
df.mm.trans1:probe3	0.394905777210795	0.0545024544364905	7.2456512517425	1.23092962551085e-12	***
df.mm.trans1:probe4	-0.151390710321557	0.0545024544364905	-2.77768610398943	0.00563365972376374	** 
df.mm.trans1:probe5	0.529423528622547	0.0545024544364905	9.7137557215788	6.53290036217688e-21	***
df.mm.trans1:probe6	-0.162977747354571	0.0545024544364905	-2.99028271368003	0.00289322785166905	** 
df.mm.trans1:probe7	0.437687345635532	0.0545024544364905	8.03059880808766	4.60247319097579e-15	***
df.mm.trans1:probe8	0.565898733404875	0.0545024544364905	10.3829953945339	1.84153897359824e-23	***
df.mm.trans1:probe9	-0.0268529520193888	0.0545024544364905	-0.492692527282041	0.62239727215881	   
df.mm.trans1:probe10	-0.146908970231471	0.0545024544364905	-2.69545604414307	0.00721220043396225	** 
df.mm.trans1:probe11	-0.225662946352614	0.0545024544364905	-4.14041805430193	3.92672906244113e-05	***
df.mm.trans1:probe12	-0.0992821305706323	0.0545024544364905	-1.82160843208120	0.0689767416636722	.  
df.mm.trans1:probe13	0.0627295542515427	0.0545024544364905	1.15094916183342	0.250178980808191	   
df.mm.trans1:probe14	-0.168097084012963	0.0545024544364905	-3.08421126628049	0.00212801010057163	** 
df.mm.trans1:probe15	1.63894294515698	0.0545024544364905	30.0709933543777	6.56522842753486e-125	***
df.mm.trans1:probe16	1.92831606238518	0.0545024544364905	35.3803527258056	2.62509736321925e-153	***
df.mm.trans1:probe17	1.46269976792002	0.0545024544364905	26.8373192187967	3.67104747941223e-107	***
df.mm.trans1:probe18	1.20832042948877	0.0545024544364905	22.1700186162583	2.03981519766497e-81	***
df.mm.trans1:probe19	1.46383621222693	0.0545024544364905	26.8581704688673	2.81658741190735e-107	***
df.mm.trans1:probe20	1.14168255601009	0.0545024544364905	20.9473604044832	9.5592247214236e-75	***
df.mm.trans2:probe2	0.504550860914048	0.0545024544364905	9.25739704992517	3.04131482115428e-19	***
df.mm.trans2:probe3	0.904454748162252	0.0545024544364905	16.5947526127686	8.8682784990245e-52	***
df.mm.trans2:probe4	0.46596653770989	0.0545024544364905	8.54945969915653	8.93002996860233e-17	***
df.mm.trans2:probe5	0.0325908851786585	0.0545024544364905	0.597970963245983	0.550068878349981	   
df.mm.trans2:probe6	0.435393358632845	0.0545024544364905	7.98850919897913	6.28324561699518e-15	***
df.mm.trans3:probe2	0.148128016122572	0.0545024544364905	2.71782285135764	0.0067475377863288	** 
df.mm.trans3:probe3	0.0555566881150134	0.0545024544364905	1.01934286610434	0.308421811488690	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.61944449033453	0.357459848515106	12.9229744530016	3.82893031127679e-34	***
df.mm.trans1	0.0992829996315771	0.320304710798139	0.309964219334091	0.756688130737769	   
df.mm.trans2	-0.140664204192866	0.295569431316106	-0.47590917493233	0.634299983923258	   
df.mm.exp2	0.248989906136890	0.405156972561460	0.614551699709721	0.53906720436862	   
df.mm.exp3	-0.330694429491025	0.40515697256146	-0.816213102295459	0.414679128939644	   
df.mm.exp4	0.0689971325332405	0.405156972561460	0.170297285264600	0.864829665821535	   
df.mm.exp5	-0.294665986469355	0.40515697256146	-0.727288449724645	0.467312757359036	   
df.mm.exp6	-0.319164430199869	0.405156972561460	-0.78775499822221	0.431128970812815	   
df.mm.exp7	0.121807390488191	0.405156972561460	0.300642463877909	0.763783877002724	   
df.mm.exp8	0.241740567234554	0.40515697256146	0.596659032439294	0.550944082700138	   
df.mm.trans1:exp2	-0.347909265657673	0.386302016109355	-0.900614677504521	0.368128846022013	   
df.mm.trans2:exp2	-0.0447440357233255	0.338244127613646	-0.132283259546885	0.894801438857767	   
df.mm.trans1:exp3	0.387233694483327	0.386302016109355	1.00241178750076	0.316520075793529	   
df.mm.trans2:exp3	0.420323529783198	0.338244127613646	1.24266319935436	0.214442841693143	   
df.mm.trans1:exp4	-0.147683367746892	0.386302016109355	-0.382300276955027	0.70236438635873	   
df.mm.trans2:exp4	0.0798820877722232	0.338244127613646	0.236166961229456	0.813377973676135	   
df.mm.trans1:exp5	0.250973331834237	0.386302016109355	0.649681651579036	0.516128817916363	   
df.mm.trans2:exp5	0.278633207086146	0.338244127613646	0.823763620234703	0.410377897882789	   
df.mm.trans1:exp6	0.123838383243477	0.386302016109355	0.320574001892914	0.748636912023523	   
df.mm.trans2:exp6	0.450975091522271	0.338244127613646	1.33328284131333	0.182908964557280	   
df.mm.trans1:exp7	-0.181957258726027	0.386302016109355	-0.471023321489781	0.637783094291397	   
df.mm.trans2:exp7	0.0463868677216615	0.338244127613646	0.137140201217761	0.89096270689223	   
df.mm.trans1:exp8	-0.202897458343328	0.386302016109355	-0.525230130525364	0.599603437084189	   
df.mm.trans2:exp8	-0.0802072294536571	0.338244127613646	-0.237128224574153	0.81263249476448	   
df.mm.trans1:probe2	0.0992676737434406	0.193151008054677	0.513938160319307	0.607470974387091	   
df.mm.trans1:probe3	-0.0052614284519853	0.193151008054677	-0.0272399740750817	0.978276745438342	   
df.mm.trans1:probe4	0.185162886210497	0.193151008054677	0.958643126304991	0.338097198172584	   
df.mm.trans1:probe5	0.111641528536029	0.193151008054677	0.578001272995816	0.563464679509519	   
df.mm.trans1:probe6	0.217659916107734	0.193151008054677	1.12688987906353	0.260207452997161	   
df.mm.trans1:probe7	0.0340673490596523	0.193151008054677	0.176376760353269	0.860053238972002	   
df.mm.trans1:probe8	-0.00858509711297566	0.193151008054677	-0.0444475915473627	0.964561361886223	   
df.mm.trans1:probe9	0.0173878059817660	0.193151008054677	0.0900218236336816	0.92829777582925	   
df.mm.trans1:probe10	-0.185827021997679	0.193151008054677	-0.962081554060928	0.336368612477875	   
df.mm.trans1:probe11	0.0393110794680233	0.193151008054677	0.20352510641257	0.838788717286418	   
df.mm.trans1:probe12	-0.124459630254496	0.193151008054677	-0.644364383639475	0.519567901641635	   
df.mm.trans1:probe13	-0.111089545572852	0.193151008054677	-0.575143493641023	0.565394513449327	   
df.mm.trans1:probe14	0.0392997405828009	0.193151008054677	0.203466401644023	0.838834577868117	   
df.mm.trans1:probe15	0.0343560498814875	0.193151008054677	0.177871450050946	0.858879693117782	   
df.mm.trans1:probe16	-0.0597755847455987	0.193151008054677	-0.309475913937127	0.757059326181002	   
df.mm.trans1:probe17	0.158053515159637	0.193151008054677	0.8182898797758	0.413493415290544	   
df.mm.trans1:probe18	-0.157854679885732	0.193151008054677	-0.817260450647226	0.414080905054513	   
df.mm.trans1:probe19	-0.128703815748210	0.193151008054677	-0.66633778950704	0.505433104827244	   
df.mm.trans1:probe20	0.270438592016909	0.193151008054677	1.40014072274659	0.161951261442449	   
df.mm.trans2:probe2	-0.0717622780899857	0.193151008054677	-0.371534577079045	0.710361231745662	   
df.mm.trans2:probe3	0.0376699632711432	0.193151008054677	0.195028561593008	0.845431909440347	   
df.mm.trans2:probe4	0.0318793126946714	0.193151008054677	0.165048647769143	0.86895732510147	   
df.mm.trans2:probe5	-0.0136087590316215	0.193151008054677	-0.070456577828313	0.943852065549409	   
df.mm.trans2:probe6	-0.0707818646940038	0.193151008054677	-0.366458686428221	0.714142824451387	   
df.mm.trans3:probe2	0.0381183507104078	0.193151008054677	0.197349996224805	0.84361573474903	   
df.mm.trans3:probe3	-0.0673749249520438	0.193151008054677	-0.348819949896255	0.727338143657103