chr15.8561_chr15_82756573_82758078_-_0.R 

fitVsDatCorrelation=0.865035852338714
cont.fitVsDatCorrelation=0.238213461103782

fstatistic=6861.96547387307,42,462
cont.fstatistic=1823.09128872061,42,462

residuals=-0.707898442487404,-0.100092373080236,-0.00211564224800060,0.0897152471892038,1.47070517078474
cont.residuals=-0.696931571966584,-0.255870524519068,-0.0338161955712387,0.173219783595380,1.87008216306385

predictedValues:
Include	Exclude	Both
chr15.8561_chr15_82756573_82758078_-_0.R.tl.Lung	69.9251350264232	83.3235467464414	64.5152619523145
chr15.8561_chr15_82756573_82758078_-_0.R.tl.cerebhem	65.9129694309873	123.971683970215	93.7271738090867
chr15.8561_chr15_82756573_82758078_-_0.R.tl.cortex	60.1277435842085	148.485726692378	80.5399523554281
chr15.8561_chr15_82756573_82758078_-_0.R.tl.heart	64.0097049426291	80.7588371903512	64.4283634843627
chr15.8561_chr15_82756573_82758078_-_0.R.tl.kidney	74.7147492482595	76.5475606594222	60.1251877378082
chr15.8561_chr15_82756573_82758078_-_0.R.tl.liver	69.2832284003879	84.1151961436398	60.5130509408555
chr15.8561_chr15_82756573_82758078_-_0.R.tl.stomach	64.1606934219754	81.0036229500768	63.2402344128579
chr15.8561_chr15_82756573_82758078_-_0.R.tl.testicle	67.6538685295339	108.858442562345	74.9973028197273


diffExp=-13.3984117200182,-58.0587145392281,-88.3579831081695,-16.7491322477221,-1.83281141116268,-14.8319677432519,-16.8429295281014,-41.2045740328111
diffExpScore=0.996036095698345
diffExp1.5=0,-1,-1,0,0,0,0,-1
diffExp1.5Score=0.75
diffExp1.4=0,-1,-1,0,0,0,0,-1
diffExp1.4Score=0.75
diffExp1.3=0,-1,-1,0,0,0,0,-1
diffExp1.3Score=0.75
diffExp1.2=0,-1,-1,-1,0,-1,-1,-1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	84.7236924543776	72.0885627713197	80.9592452651915
cerebhem	73.138131407298	68.2912655025573	72.6702519140416
cortex	65.0359900502543	79.104471199165	70.5030375299152
heart	77.4492603820536	73.9825837686863	75.602184680828
kidney	72.4653885511068	75.3122568311586	78.6960281179369
liver	60.6945773112264	72.809675097633	73.0138133037646
stomach	72.3916961232662	73.3094844386679	71.36917441897
testicle	68.2658954796217	81.3707203969808	74.6185553015787
cont.diffExp=12.6351296830578,4.84686590474067,-14.0684811489107,3.46667661336726,-2.84686828005177,-12.1150977864065,-0.917788315401694,-13.1048249173591
cont.diffExpScore=2.77011154613477

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

tran.correlation=-0.622391873519463
cont.tran.correlation=-0.372596395120898

tran.covariance=-0.0100186778204043
cont.tran.covariance=-0.00202537283281336

tran.mean=82.6782943437047
cont.tran.mean=73.1521032353358

weightedLogRatios:
wLogRatio
Lung	-0.759965271851234
cerebhem	-2.84538036416405
cortex	-4.11190550842987
heart	-0.99370807458006
kidney	-0.104834499423089
liver	-0.840960122387398
stomach	-0.997201661744737
testicle	-2.11767394176473

cont.weightedLogRatios:
wLogRatio
Lung	0.70392071262356
cerebhem	0.291967018483873
cortex	-0.836747187538987
heart	0.198135105114783
kidney	-0.165787094452256
liver	-0.763803858055097
stomach	-0.054026837757694
testicle	-0.757071406094708

varWeightedLogRatios=1.76811467478638
cont.varWeightedLogRatios=0.323983008882899

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.35051657363574	0.0909907389986505	47.8127403020681	5.32689574506475e-181	***
df.mm.trans1	-0.106884132472899	0.0731021287732541	-1.46212065594462	0.144388017566302	   
df.mm.trans2	0.121751503339169	0.0731021287732541	1.66549873967164	0.096491184532946	.  
df.mm.exp2	-0.0352542826531358	0.0981535099493102	-0.359174956365211	0.719628305742493	   
df.mm.exp3	0.204952293806170	0.0981535099493103	2.08807911109867	0.0373377604467429	*  
df.mm.exp4	-0.118306394461489	0.0981535099493103	-1.20532005959427	0.22869675871057	   
df.mm.exp5	0.0519063856855855	0.0981535099493103	0.528828624797948	0.597178301772562	   
df.mm.exp6	0.0642765065654249	0.0981535099493102	0.6548569337828	0.512885764284665	   
df.mm.exp7	-0.0943106045341455	0.0981535099493102	-0.960848008215404	0.3371311910627	   
df.mm.exp8	0.0837461949455774	0.0981535099493102	0.853216507375302	0.393981379425286	   
df.mm.trans1:exp2	-0.0238356605868416	0.0775971629449546	-0.307171804770105	0.75885101353435	   
df.mm.trans2:exp2	0.432576283847345	0.0775971629449546	5.57464045630384	4.22419513216472e-08	***
df.mm.trans1:exp3	-0.355906105187146	0.0775971629449546	-4.58658656682611	5.81022572826604e-06	***
df.mm.trans2:exp3	0.372805360012521	0.0775971629449547	4.80436843131725	2.10186643235096e-06	***
df.mm.trans1:exp4	0.0299159359495889	0.0775971629449546	0.385528733451382	0.700023169074817	   
df.mm.trans2:exp4	0.0870426062111254	0.0775971629449546	1.12172407994956	0.262562441851823	   
df.mm.trans1:exp5	0.0143459632883724	0.0775971629449546	0.184877420048836	0.85340631070127	   
df.mm.trans2:exp5	-0.136725313322056	0.0775971629449546	-1.76198855902818	0.0787325189173984	.  
df.mm.trans1:exp6	-0.073498814188211	0.0775971629449546	-0.947184296420078	0.344040023211249	   
df.mm.trans2:exp6	-0.0548204478010334	0.0775971629449546	-0.706474898314537	0.480248987190311	   
df.mm.trans1:exp7	0.00827620562910939	0.0775971629449546	0.106656033739021	0.915108159947874	   
df.mm.trans2:exp7	0.0660733027301239	0.0775971629449546	0.851491217236828	0.39493767219941	   
df.mm.trans1:exp8	-0.116766827595714	0.0775971629449546	-1.50478217455637	0.133063408615326	   
df.mm.trans2:exp8	0.183570967908651	0.0775971629449546	2.36569174621593	0.0184083962379168	*  
df.mm.trans1:probe2	0.460013261175068	0.0520537593618139	8.83727259692464	2.06622291667779e-17	***
df.mm.trans1:probe3	-0.0779086158372528	0.0520537593618139	-1.49669527796691	0.135155390816296	   
df.mm.trans1:probe4	-0.0235605026515598	0.0520537593618139	-0.452618656950328	0.651035824813105	   
df.mm.trans1:probe5	-0.0162279727152178	0.0520537593618139	-0.31175409642214	0.755368049610517	   
df.mm.trans1:probe6	-0.285425235853454	0.0520537593618139	-5.48327804471389	6.88387222386289e-08	***
df.mm.trans2:probe2	-0.126465502185705	0.0520537593618139	-2.42951717102068	0.0154991058919836	*  
df.mm.trans2:probe3	-0.147026370271041	0.0520537593618139	-2.82451012325726	0.00494015869521123	** 
df.mm.trans2:probe4	-0.0589139692648494	0.0520537593618139	-1.13179086365985	0.258309473254201	   
df.mm.trans2:probe5	-0.251018526660258	0.0520537593618139	-4.82229390802468	1.92974068268311e-06	***
df.mm.trans2:probe6	-0.15962903741778	0.0520537593618139	-3.06661880668857	0.00229195768231618	** 
df.mm.trans3:probe2	-0.165390265214927	0.0520537593618139	-3.17729722584178	0.00158617956327696	** 
df.mm.trans3:probe3	-0.284478934622844	0.0520537593618139	-5.46509873850793	7.58038537570206e-08	***
df.mm.trans3:probe4	-0.50748905194489	0.0520537593618139	-9.7493256619075	1.51278690612264e-20	***
df.mm.trans3:probe5	-0.512039308395458	0.0520537593618139	-9.83674022151578	7.39221135893478e-21	***
df.mm.trans3:probe6	-0.206709516212131	0.0520537593618139	-3.97107756954383	8.29616221189491e-05	***
df.mm.trans3:probe7	-0.534989077680071	0.0520537593618139	-10.2776261357318	1.87843174059973e-22	***
df.mm.trans3:probe8	0.247818927987559	0.0520537593618139	4.76082671118959	2.58379380417779e-06	***
df.mm.trans3:probe9	0.176938062612172	0.0520537593618139	3.39914090320193	0.000734549448950787	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.36865341600184	0.176140327424374	24.8021193095461	5.85172578685771e-87	***
df.mm.trans1	0.0687269237579021	0.1415114663233	0.485663286117658	0.627436159619288	   
df.mm.trans2	-0.0946422675518014	0.1415114663233	-0.668795752109442	0.50395980770174	   
df.mm.exp2	-0.0931451758422686	0.190006055237989	-0.490222144371142	0.624209433351003	   
df.mm.exp3	-0.0332903885989553	0.190006055237989	-0.175206987783931	0.860993753715184	   
df.mm.exp4	0.00462274455783029	0.190006055237989	0.0243294591429739	0.9806003197222	   
df.mm.exp5	-0.0841855450577484	0.190006055237989	-0.443067695670557	0.657924158996188	   
df.mm.exp6	-0.220290245346776	0.190006055237989	-1.15938539469626	0.246897980019128	   
df.mm.exp7	-0.0144292573264291	0.190006055237989	-0.0759410393966446	0.939498879552232	   
df.mm.exp8	-0.0133081941045888	0.190006055237989	-0.0700408946858027	0.944191416499595	   
df.mm.trans1:exp2	-0.0539002444813218	0.150212975943953	-0.358825488561208	0.71988956360522	   
df.mm.trans2:exp2	0.039031648315701	0.150212975943953	0.259842054725448	0.795101364216403	   
df.mm.trans1:exp3	-0.231164086210668	0.150212975943953	-1.53890890422755	0.124511127702556	   
df.mm.trans2:exp3	0.126164386052001	0.150212975943953	0.839903378913653	0.401396986669742	   
df.mm.trans1:exp4	-0.0943950119136102	0.150212975943953	-0.628407841069806	0.530047333232201	   
df.mm.trans2:exp4	0.0213115648398782	0.150212975943953	0.141875658250922	0.887240067552912	   
df.mm.trans1:exp5	-0.0721006909226683	0.150212975943953	-0.479989764330149	0.631461836171286	   
df.mm.trans2:exp5	0.127933038310577	0.150212975943953	0.85167767635674	0.394834253937317	   
df.mm.trans1:exp6	-0.113250681027230	0.150212975943953	-0.753934074706605	0.451272881786365	   
df.mm.trans2:exp6	0.230243689782757	0.150212975943953	1.53278162779136	0.126014128960178	   
df.mm.trans1:exp7	-0.142874428844476	0.150212975943953	-0.951145717915774	0.342027724219178	   
df.mm.trans2:exp7	0.0312238482887042	0.150212975943953	0.207863855252787	0.835426869586538	   
df.mm.trans1:exp8	-0.202676782701847	0.150212975943953	-1.34926281453521	0.177913417502114	   
df.mm.trans2:exp8	0.134428300493590	0.150212975943953	0.894918029876109	0.371296902101901	   
df.mm.trans1:probe2	-0.0315479670317866	0.100765927593966	-0.313081691252906	0.754359883018933	   
df.mm.trans1:probe3	-0.0420679430820441	0.100765927593966	-0.417481822343322	0.676519958047738	   
df.mm.trans1:probe4	0.054002598577378	0.100765927593966	0.535921217288649	0.592270911780402	   
df.mm.trans1:probe5	-0.00259030269154174	0.100765927593966	-0.0257061365224494	0.97950282866198	   
df.mm.trans1:probe6	0.0524277861515639	0.100765927593966	0.520292795426055	0.603108746022256	   
df.mm.trans2:probe2	-0.0182804724303505	0.100765927593966	-0.181415215111316	0.856121239455991	   
df.mm.trans2:probe3	0.0703549260575151	0.100765927593966	0.698201542301171	0.485402429165127	   
df.mm.trans2:probe4	-0.0273918530728138	0.100765927593966	-0.271836460268482	0.785869202294882	   
df.mm.trans2:probe5	0.0511834015588773	0.100765927593966	0.507943535885659	0.611735359587392	   
df.mm.trans2:probe6	-0.0176022044281706	0.100765927593966	-0.174684090629308	0.861404393635635	   
df.mm.trans3:probe2	0.0346268071538096	0.100765927593966	0.343636068069929	0.731276325727888	   
df.mm.trans3:probe3	-0.0277032133425193	0.100765927593966	-0.27492639629289	0.783495689661476	   
df.mm.trans3:probe4	0.0670008533578371	0.100765927593966	0.664915760293655	0.506436138181957	   
df.mm.trans3:probe5	0.154158502436433	0.100765927593966	1.52986734819344	0.126733950048599	   
df.mm.trans3:probe6	0.0632094969632524	0.100765927593966	0.627290379521477	0.530778793393404	   
df.mm.trans3:probe7	0.0719678086317737	0.100765927593966	0.714207771914396	0.4754593900138	   
df.mm.trans3:probe8	0.108340652358026	0.100765927593966	1.07517148846763	0.282859131287092	   
df.mm.trans3:probe9	-0.0107306088244184	0.100765927593966	-0.106490448514077	0.915239457007764