chr4.16700_chr4_59721559_59725398_-_2.R 

fitVsDatCorrelation=0.926406788583338
cont.fitVsDatCorrelation=0.253240978406722

fstatistic=10528.6193100103,59,853
cont.fstatistic=1582.66427566087,59,853

residuals=-0.725190945046509,-0.090827492324829,-0.0116057209041612,0.0783671553859462,0.845621586399829
cont.residuals=-0.782436919184224,-0.242888800175132,-0.0952814570779634,0.105567930147076,2.04043035810832

predictedValues:
Include	Exclude	Both
chr4.16700_chr4_59721559_59725398_-_2.R.tl.Lung	54.9471783402176	143.231589162471	67.8462399643854
chr4.16700_chr4_59721559_59725398_-_2.R.tl.cerebhem	60.930161148048	67.7563880955328	71.4681624949799
chr4.16700_chr4_59721559_59725398_-_2.R.tl.cortex	54.706786410991	89.0382614298924	63.1340279878179
chr4.16700_chr4_59721559_59725398_-_2.R.tl.heart	53.8069060959252	118.341574098108	61.6668069314391
chr4.16700_chr4_59721559_59725398_-_2.R.tl.kidney	56.7761084755229	161.608050436275	69.033953518426
chr4.16700_chr4_59721559_59725398_-_2.R.tl.liver	54.8988651713533	133.053022970880	62.2100163653554
chr4.16700_chr4_59721559_59725398_-_2.R.tl.stomach	54.9333901744876	101.320306651804	64.9378397020151
chr4.16700_chr4_59721559_59725398_-_2.R.tl.testicle	54.8400508646506	106.304395903763	63.5924818806914


diffExp=-88.2844108222536,-6.82622694748472,-34.3314750189013,-64.5346680021826,-104.831941960752,-78.1541577995263,-46.3869164773163,-51.464345039112
diffExpScore=0.99789833905387
diffExp1.5=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.875
diffExp1.4=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.4Score=0.875
diffExp1.3=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.3Score=0.875
diffExp1.2=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	70.6511093778634	64.5360578161143	70.4091512560686
cerebhem	69.4594330317751	73.721946078401	62.0526935635774
cortex	64.7657710793673	67.4523899566391	68.7038249470541
heart	68.4773024085336	61.3312430322143	59.594166256018
kidney	65.3494437944055	59.8715303527022	67.8691810685715
liver	68.9720409247165	70.1011096054185	75.3332383341233
stomach	64.2937360776391	63.6431477965809	67.885078698055
testicle	64.5797225093667	69.0344744550256	67.6764963369507
cont.diffExp=6.11505156174913,-4.26251304662593,-2.68661887727184,7.14605937631924,5.47791344170331,-1.12906868070198,0.65058828105824,-4.45475194565897
cont.diffExpScore=4.06312157606723

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=-0.406601336850432
cont.tran.correlation=0.243866218468014

tran.covariance=-0.00564482968460675
cont.tran.covariance=0.00064032055302295

tran.mean=85.4058147143701
cont.tran.mean=66.6400286435477

weightedLogRatios:
wLogRatio
Lung	-4.29743594687931
cerebhem	-0.442052043157046
cortex	-2.06790454235568
heart	-3.45179594870484
kidney	-4.7722696486272
liver	-3.93772082459824
stomach	-2.63978253258353
testicle	-2.86951592058819

cont.weightedLogRatios:
wLogRatio
Lung	0.381355395046079
cerebhem	-0.254342219791069
cortex	-0.170346302710301
heart	0.459741849083201
kidney	0.36209560868061
liver	-0.0688761450966609
stomach	0.0422929579333958
testicle	-0.280246870763105

varWeightedLogRatios=1.91968350000799
cont.varWeightedLogRatios=0.091268130199076

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.90621337493255	0.0749712840446828	65.4412344332858	0	***
df.mm.trans1	-0.99101016776716	0.0647433670416599	-15.3067443515794	6.533660845519e-47	***
df.mm.trans2	0.0713035868051651	0.057200472146507	1.24655591342910	0.21290257945041	   
df.mm.exp2	-0.697196204124897	0.0735780964678637	-9.4755944716429	2.53880258355464e-20	***
df.mm.exp3	-0.407797133187692	0.0735780964678637	-5.54237134098465	3.9781444206534e-08	***
df.mm.exp4	-0.116360034291425	0.0735780964678637	-1.58144936981683	0.114146024359293	   
df.mm.exp5	0.136099923175072	0.0735780964678637	1.84973422402298	0.0646975856311432	.  
df.mm.exp6	0.012133186612631	0.0735780964678637	0.164902154242742	0.86906006642356	   
df.mm.exp7	-0.30261347182084	0.0735780964678637	-4.11282006939403	4.28685876193888e-05	***
df.mm.exp8	-0.235359020480759	0.0735780964678637	-3.19876473813854	0.00143111830214946	** 
df.mm.trans1:exp2	0.800552183243487	0.0680097646205447	11.7711359201154	9.55833889671715e-30	***
df.mm.trans2:exp2	-0.0513478762363904	0.0502285399697779	-1.02228486568166	0.306935927197968	   
df.mm.trans1:exp3	0.403412570989919	0.0680097646205447	5.93168603421477	4.35446088988775e-09	***
df.mm.trans2:exp3	-0.0675995106647385	0.0502285399697779	-1.34583865478496	0.178712144898351	   
df.mm.trans1:exp4	0.095389529371587	0.0680097646205447	1.40258578902317	0.161104231306584	   
df.mm.trans2:exp4	-0.0745276519694433	0.0502285399697779	-1.48377101970884	0.138239071921502	   
df.mm.trans1:exp5	-0.103356641311210	0.0680097646205447	-1.51973237795897	0.128948808182834	   
df.mm.trans2:exp5	-0.0153887861818506	0.0502285399697779	-0.306375343402574	0.759393644307227	   
df.mm.trans1:exp6	-0.0130128390868601	0.0680097646205447	-0.191337805085258	0.848306477631093	   
df.mm.trans2:exp6	-0.085848293793351	0.0502285399697779	-1.70915367727203	0.0877862224463113	.  
df.mm.trans1:exp7	0.302362505412698	0.0680097646205447	4.44586901748164	9.90946843841588e-06	***
df.mm.trans2:exp7	-0.0435625013920195	0.0502285399697779	-0.867285838255117	0.386029320969373	   
df.mm.trans1:exp8	0.233407472739863	0.0680097646205447	3.43197001257309	0.000628033892964729	***
df.mm.trans2:exp8	-0.0627971661841915	0.0502285399697779	-1.25022877873767	0.211558855874672	   
df.mm.trans1:probe2	-0.0086184749673869	0.0465631027666114	-0.185092368319726	0.853200586540425	   
df.mm.trans1:probe3	-0.0864645333926677	0.0465631027666114	-1.85693238326609	0.063665312590097	.  
df.mm.trans1:probe4	-0.0603848695160983	0.0465631027666114	-1.29683947005778	0.195037107519351	   
df.mm.trans1:probe5	0.266471162205970	0.0465631027666114	5.72279651426163	1.45045432181231e-08	***
df.mm.trans1:probe6	0.0790245859580211	0.0465631027666114	1.69715034571722	0.0900330311824108	.  
df.mm.trans1:probe7	-0.0218704273818069	0.0465631027666114	-0.469694373491995	0.638693432756467	   
df.mm.trans1:probe8	0.223869773286183	0.0465631027666114	4.80787920015311	1.80261851975614e-06	***
df.mm.trans1:probe9	0.62662927418698	0.0465631027666114	13.4576357019814	1.41158096649537e-37	***
df.mm.trans1:probe10	0.0133954711938207	0.0465631027666114	0.287684247782261	0.77365832700782	   
df.mm.trans1:probe11	0.130994854449263	0.0465631027666114	2.81327589155408	0.00501667784429976	** 
df.mm.trans1:probe12	0.232249325999061	0.0465631027666114	4.98784041869301	7.39897803854509e-07	***
df.mm.trans1:probe13	0.103805621001694	0.0465631027666114	2.22935360476298	0.0260500752865343	*  
df.mm.trans1:probe14	0.113026616093226	0.0465631027666114	2.42738583508385	0.0154141304176761	*  
df.mm.trans1:probe15	0.228135804256117	0.0465631027666114	4.89949747119739	1.14966959078951e-06	***
df.mm.trans1:probe16	0.118760010229129	0.0465631027666114	2.55051753798262	0.0109299857108497	*  
df.mm.trans1:probe17	0.132975728678018	0.0465631027666114	2.85581760615339	0.00439683532154731	** 
df.mm.trans1:probe18	0.173344140397246	0.0465631027666114	3.72277898373955	0.000209974005740634	***
df.mm.trans1:probe19	0.199832480182361	0.0465631027666114	4.29164871559318	1.97675378181053e-05	***
df.mm.trans1:probe20	0.0424147308303072	0.0465631027666114	0.910908601664776	0.362600869269956	   
df.mm.trans1:probe21	0.260882104105916	0.0465631027666114	5.60276460556199	2.84692679783083e-08	***
df.mm.trans1:probe22	0.148938551140081	0.0465631027666114	3.19863888552716	0.00143173563780393	** 
df.mm.trans2:probe2	-0.0131507114355168	0.0465631027666114	-0.28242773041634	0.777684068292818	   
df.mm.trans2:probe3	0.359195125750710	0.0465631027666114	7.7141578719766	3.39577959470412e-14	***
df.mm.trans2:probe4	-0.177175673682644	0.0465631027666114	-3.80506588168539	0.000151890883969336	***
df.mm.trans2:probe5	-0.475633347265822	0.0465631027666114	-10.2148121367651	3.45260685890658e-23	***
df.mm.trans2:probe6	0.0978984173755316	0.0465631027666114	2.10248912891885	0.0358029936184848	*  
df.mm.trans3:probe2	1.62309645201054	0.0465631027666114	34.8579960434768	3.24913099611264e-166	***
df.mm.trans3:probe3	0.180156794918048	0.0465631027666114	3.86908913310717	0.000117566333755433	***
df.mm.trans3:probe4	-0.045506661678897	0.0465631027666114	-0.977311626052722	0.328691982559921	   
df.mm.trans3:probe5	-0.132890497150134	0.0465631027666114	-2.85398715408254	0.00442200380514435	** 
df.mm.trans3:probe6	-0.187510487565521	0.0465631027666114	-4.02701874283124	6.15207186410616e-05	***
df.mm.trans3:probe7	0.253806346708522	0.0465631027666114	5.45080399776358	6.56689941287225e-08	***
df.mm.trans3:probe8	0.269344912050296	0.0465631027666114	5.78451383277303	1.02049089412461e-08	***
df.mm.trans3:probe9	0.187317775746679	0.0465631027666114	4.02288001909094	6.25916317489991e-05	***
df.mm.trans3:probe10	0.159557103862834	0.0465631027666114	3.42668538783988	0.000640212245405064	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.2727345443873	0.192623648326071	22.1817756102017	1.99180605770207e-86	***
df.mm.trans1	0.0402076788418126	0.166345070961379	0.241712475214537	0.809061057073684	   
df.mm.trans2	-0.116249561168533	0.146965118328068	-0.791001038144513	0.429163258933775	   
df.mm.exp2	0.242404824375992	0.189044132818647	1.28226579033021	0.200097789347814	   
df.mm.exp3	-0.0182602898242607	0.189044132818647	-0.096592734997907	0.92307251531707	   
df.mm.exp4	0.0845793675390548	0.189044132818647	0.447405408874515	0.654695959470963	   
df.mm.exp5	-0.116286680553193	0.189044132818647	-0.615129804979183	0.538633064706091	   
df.mm.exp6	-0.00893627906628443	0.189044132818647	-0.0472708617455859	0.962308415903869	   
df.mm.exp7	-0.0717170530007418	0.189044132818647	-0.379366722105790	0.70450997842486	   
df.mm.exp8	0.0171128613766755	0.189044132818647	0.0905231023122637	0.927892787908673	   
df.mm.trans1:exp2	-0.259415751061424	0.174737423133888	-1.48460327735664	0.138018376829220	   
df.mm.trans2:exp2	-0.1093283971889	0.129052139660621	-0.847164545093245	0.397141034691792	   
df.mm.trans1:exp3	-0.0687162819148502	0.174737423133888	-0.393254522599878	0.694229769064802	   
df.mm.trans2:exp3	0.0624582013538757	0.129052139660621	0.483976488248293	0.628526781176795	   
df.mm.trans1:exp4	-0.115830840334231	0.174737423133888	-0.6628851350605	0.507583201842412	   
df.mm.trans2:exp4	-0.135514083683569	0.129052139660621	-1.05007235091136	0.293982254880967	   
df.mm.trans1:exp5	0.0382817979534753	0.174737423133888	0.219081850166365	0.826638698200904	   
df.mm.trans2:exp5	0.0412636829167581	0.129052139660621	0.319744275649149	0.749240489085853	   
df.mm.trans1:exp6	-0.0151163138974041	0.174737423133888	-0.0865087376607448	0.93108231251566	   
df.mm.trans2:exp6	0.0916507983667125	0.129052139660621	0.710184260468164	0.477783984615887	   
df.mm.trans1:exp7	-0.0225745490990808	0.174737423133888	-0.129191267069239	0.897236761560987	   
df.mm.trans2:exp7	0.0577846142873933	0.129052139660621	0.447761768532890	0.654438828680073	   
df.mm.trans1:exp8	-0.106966204360723	0.174737423133888	-0.612153953299192	0.54059903970105	   
df.mm.trans2:exp8	0.0502690447220487	0.129052139660621	0.389525077648811	0.696984992644728	   
df.mm.trans1:probe2	0.0504674227495162	0.119634535363445	0.421846606385007	0.673243276043901	   
df.mm.trans1:probe3	-0.165053899927115	0.119634535363445	-1.37965094632322	0.168055686958235	   
df.mm.trans1:probe4	-0.0940242938710415	0.119634535363445	-0.785929360492768	0.432127132584854	   
df.mm.trans1:probe5	-0.112873684695415	0.119634535363445	-0.943487466662614	0.345698768583488	   
df.mm.trans1:probe6	-0.218899766392865	0.119634535363445	-1.82973725544933	0.0676381180025268	.  
df.mm.trans1:probe7	-0.114849777027562	0.119634535363445	-0.96000520818385	0.337324626387496	   
df.mm.trans1:probe8	-0.087591176922336	0.119634535363445	-0.732156284606595	0.464274295395284	   
df.mm.trans1:probe9	-0.0725431569662905	0.119634535363445	-0.606373040576515	0.544428401279463	   
df.mm.trans1:probe10	-0.126991098430368	0.119634535363445	-1.06149196839002	0.288766823497628	   
df.mm.trans1:probe11	-0.15578626592544	0.119634535363445	-1.30218473664120	0.193204741992138	   
df.mm.trans1:probe12	-0.102018749050332	0.119634535363445	-0.852753335317456	0.394035479387084	   
df.mm.trans1:probe13	-0.0707876342965534	0.119634535363445	-0.591698994621441	0.554208949380681	   
df.mm.trans1:probe14	-0.186230515495655	0.119634535363445	-1.55666183623227	0.119921716204447	   
df.mm.trans1:probe15	0.240836925664805	0.119634535363445	2.01310537072889	0.0444172776898105	*  
df.mm.trans1:probe16	-0.0989783966884528	0.119634535363445	-0.827339667327337	0.408275952998435	   
df.mm.trans1:probe17	-0.074144846139118	0.119634535363445	-0.619761224581757	0.535580512205492	   
df.mm.trans1:probe18	-0.0382076830127019	0.119634535363445	-0.319370012150994	0.749524144583893	   
df.mm.trans1:probe19	-0.141418100306929	0.119634535363445	-1.18208425248868	0.237501687824621	   
df.mm.trans1:probe20	0.0805769731528557	0.119634535363445	0.673526025809071	0.500795146088809	   
df.mm.trans1:probe21	-0.169037392251739	0.119634535363445	-1.41294812353482	0.158035750425730	   
df.mm.trans1:probe22	-0.108474060970616	0.119634535363445	-0.906711934317932	0.364815208426457	   
df.mm.trans2:probe2	0.162230743314795	0.119634535363445	1.35605277206907	0.175441232443904	   
df.mm.trans2:probe3	-0.0353485333464715	0.119634535363445	-0.295470979505075	0.767706025166246	   
df.mm.trans2:probe4	0.0182041343191808	0.119634535363445	0.152164542319468	0.87909314201683	   
df.mm.trans2:probe5	0.0177763151661864	0.119634535363445	0.148588491710882	0.881913473425543	   
df.mm.trans2:probe6	0.00896326517579535	0.119634535363445	0.0749220544767054	0.940294295582729	   
df.mm.trans3:probe2	-0.0388458691274051	0.119634535363445	-0.324704476089559	0.745484360392578	   
df.mm.trans3:probe3	0.0658025732010104	0.119634535363445	0.5500299140303	0.582442845044195	   
df.mm.trans3:probe4	0.101850941206596	0.119634535363445	0.851350664732197	0.394813522167833	   
df.mm.trans3:probe5	0.126945074508146	0.119634535363445	1.06110726407297	0.288941497931504	   
df.mm.trans3:probe6	-0.035744410739907	0.119634535363445	-0.298780035642024	0.765180656910583	   
df.mm.trans3:probe7	0.256872237638137	0.119634535363445	2.14714118174798	0.0320633141973673	*  
df.mm.trans3:probe8	0.00413187792742514	0.119634535363445	0.0345375013567167	0.972456618520382	   
df.mm.trans3:probe9	0.0394813360441951	0.119634535363445	0.330016210822841	0.741468742853971	   
df.mm.trans3:probe10	0.0558120602249277	0.119634535363445	0.466521310551114	0.640961517505614