chr9.24724_chr9_120601745_120607092_+_2.R 

fitVsDatCorrelation=0.848381719871812
cont.fitVsDatCorrelation=0.266699306751151

fstatistic=7488.83518162801,53,715
cont.fstatistic=2250.02517685294,53,715

residuals=-0.514840232739334,-0.103371103085402,-0.0112114056622742,0.0787779000183725,1.18337291072578
cont.residuals=-0.727781603715557,-0.234784782011444,-0.0629804859826147,0.161437984937573,1.50904660057837

predictedValues:
Include	Exclude	Both
chr9.24724_chr9_120601745_120607092_+_2.R.tl.Lung	76.0382795135707	69.7830161396018	50.6604546784246
chr9.24724_chr9_120601745_120607092_+_2.R.tl.cerebhem	74.0373329399255	89.1070706002317	53.2231251113941
chr9.24724_chr9_120601745_120607092_+_2.R.tl.cortex	70.6563172101656	64.054492778989	56.1199287535227
chr9.24724_chr9_120601745_120607092_+_2.R.tl.heart	71.5169029087366	63.125695597277	51.5171949780145
chr9.24724_chr9_120601745_120607092_+_2.R.tl.kidney	97.417796201629	69.8789875398159	104.374469325781
chr9.24724_chr9_120601745_120607092_+_2.R.tl.liver	83.389200251619	69.9474299822373	71.6242832824283
chr9.24724_chr9_120601745_120607092_+_2.R.tl.stomach	73.8530537600992	66.820226660893	50.1769271368641
chr9.24724_chr9_120601745_120607092_+_2.R.tl.testicle	70.9122180139548	70.0871925797666	48.0785098546291


diffExp=6.25526337396894,-15.0697376603061,6.60182443117665,8.39120731145957,27.5388086618132,13.4417702693817,7.03282709920613,0.825025434188206
diffExpScore=1.52018996168761
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=0,0,0,0,1,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,-1,0,0,1,0,0,0
diffExp1.2Score=2

cont.predictedValues:
Include	Exclude	Both
Lung	69.5136266985761	65.2285022656725	64.5322173386301
cerebhem	72.192835086763	70.0345741540113	71.6530027529927
cortex	73.3342599061284	75.5846985712889	70.8375046331213
heart	74.4619672541155	78.1416349940277	93.2674680872408
kidney	77.0270085047168	77.1179943185884	71.7739602016162
liver	68.6193064434087	74.6621248649547	75.7677609569029
stomach	71.5458423871452	70.0342065786835	65.0482244337831
testicle	78.4864194271363	77.2287824272619	81.0141834041385
cont.diffExp=4.28512443290359,2.15826093275162,-2.25043866516056,-3.67966773991216,-0.0909858138715833,-6.04281842154609,1.51163580846166,1.25763699987441
cont.diffExpScore=5.52458427474182

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=0.0484654819806999
cont.tran.correlation=0.673505210578145

tran.covariance=0.00102905881845378
cont.tran.covariance=0.0019861851588605

tran.mean=73.789075792407
cont.tran.mean=73.3258614926549

weightedLogRatios:
wLogRatio
Lung	0.368135583126362
cerebhem	-0.814666577878476
cortex	0.412853412369429
heart	0.525124757275518
kidney	1.46615481470672
liver	0.762094947181213
stomach	0.425508307662135
testicle	0.0498017857822413

cont.weightedLogRatios:
wLogRatio
Lung	0.267848149871203
cerebhem	0.129424941603803
cortex	-0.130278189561999
heart	-0.209068002279387
kidney	-0.00512907099482104
liver	-0.360449021672371
stomach	0.0909633946126629
testicle	0.0703455814949759

varWeightedLogRatios=0.411905262578526
cont.varWeightedLogRatios=0.0413815603119337

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.39022632214224	0.0966590560451953	45.41971028653	6.63692461322901e-213	***
df.mm.trans1	-0.258276743206559	0.0858351124384876	-3.00898706682127	0.00271331126933241	** 
df.mm.trans2	-0.0342343573397271	0.0780781967989134	-0.438462448459151	0.661183531446875	   
df.mm.exp2	0.168433237799306	0.105261011931182	1.60014838076443	0.110007404755103	   
df.mm.exp3	-0.261411224277871	0.105261011931182	-2.48345726002308	0.0132395089015935	*  
df.mm.exp4	-0.178335832076399	0.105261011931182	-1.69422494430313	0.0906580329641481	.  
df.mm.exp5	-0.473693125788251	0.105261011931182	-4.50017643852733	7.92381987566745e-06	***
df.mm.exp6	-0.25165333125078	0.105261011931182	-2.39075538638472	0.0170714870619514	*  
df.mm.exp7	-0.0629540442899974	0.105261011931182	-0.598075613515436	0.549978870921926	   
df.mm.exp8	-0.0131344054329618	0.105261011931182	-0.12477939544747	0.900733272612402	   
df.mm.trans1:exp2	-0.195100663917264	0.099950269175431	-1.95197737361594	0.0513308838422868	.  
df.mm.trans2:exp2	0.0760147909330066	0.0841656587301499	0.903156846627002	0.366746824868928	   
df.mm.trans1:exp3	0.188001853689746	0.099950269175431	1.88095395080696	0.0603843338728025	.  
df.mm.trans2:exp3	0.175754736653031	0.08416565873015	2.08820009615242	0.0371330505674488	*  
df.mm.trans1:exp4	0.117032766861876	0.099950269175431	1.17090997180270	0.242025048564	   
df.mm.trans2:exp4	0.078073080595444	0.0841656587301499	0.927612066172502	0.353921855204154	   
df.mm.trans1:exp5	0.721465140995848	0.099950269175431	7.21824110077728	1.34865257713212e-12	***
df.mm.trans2:exp5	0.475067464016138	0.0841656587301499	5.64443350392218	2.39022891051507e-08	***
df.mm.trans1:exp6	0.343935247551244	0.099950269175431	3.44106374488672	0.000613110905834357	***
df.mm.trans2:exp6	0.254006632525858	0.08416565873015	3.0179367257167	0.00263543968530216	** 
df.mm.trans1:exp7	0.0337945119667359	0.099950269175431	0.338113266182609	0.73537708559214	   
df.mm.trans2:exp7	0.0195692149458245	0.08416565873015	0.232508308508187	0.816209771234863	   
df.mm.trans1:exp8	-0.0566597397507397	0.099950269175431	-0.566879311263199	0.570974091868117	   
df.mm.trans2:exp8	0.0174838222597360	0.0841656587301499	0.207731068983755	0.835498109933461	   
df.mm.trans1:probe2	0.504269204441171	0.0547450170560968	9.21123476725653	3.51822690075118e-19	***
df.mm.trans1:probe3	1.03573434240324	0.0547450170560968	18.9192441266743	4.96394600282925e-65	***
df.mm.trans1:probe4	0.370187233474351	0.0547450170560968	6.76202608714182	2.82930211969153e-11	***
df.mm.trans1:probe5	0.443798718074011	0.0547450170560968	8.10665046682246	2.25664193371058e-15	***
df.mm.trans1:probe6	0.402121273867515	0.0547450170560968	7.34534932111655	5.60900053164972e-13	***
df.mm.trans1:probe7	-0.316259235756471	0.0547450170560968	-5.77695017306147	1.13506492666326e-08	***
df.mm.trans1:probe8	0.321340398905119	0.0547450170560968	5.86976525326211	6.67828785132659e-09	***
df.mm.trans1:probe9	0.376517856153511	0.0547450170560968	6.87766442318753	1.32883591745103e-11	***
df.mm.trans1:probe10	0.45278706643694	0.0547450170560968	8.27083615615595	6.4850625658521e-16	***
df.mm.trans1:probe11	-0.147054964175384	0.0547450170560968	-2.68617989514365	0.00739519052607806	** 
df.mm.trans1:probe12	-0.0136743726910551	0.0547450170560968	-0.249782965215684	0.802826939378225	   
df.mm.trans1:probe13	0.130159974506116	0.0547450170560968	2.3775675213096	0.0176892535819836	*  
df.mm.trans1:probe14	0.309601080759592	0.0547450170560968	5.65532896706099	2.24952918207966e-08	***
df.mm.trans1:probe15	0.260132268112439	0.0547450170560968	4.7517067689628	2.43882932704456e-06	***
df.mm.trans1:probe16	0.504760440690891	0.0547450170560968	9.22020793552163	3.26478529560304e-19	***
df.mm.trans1:probe17	0.136203202394195	0.0547450170560968	2.48795615963784	0.0130746561939162	*  
df.mm.trans1:probe18	0.0631600564267122	0.0547450170560968	1.15371333909701	0.249003215496075	   
df.mm.trans1:probe19	-0.0350929363383383	0.0547450170560968	-0.641025215178558	0.521711706308184	   
df.mm.trans1:probe20	0.145106991719248	0.0547450170560968	2.65059725108054	0.00821272807687947	** 
df.mm.trans1:probe21	0.185595764453061	0.0547450170560968	3.39018552616181	0.000736816890998981	***
df.mm.trans1:probe22	0.0520757574434595	0.0547450170560968	0.951241962169779	0.341802996762728	   
df.mm.trans2:probe2	-0.282691020939634	0.0547450170560968	-5.16377628762016	3.14076097239824e-07	***
df.mm.trans2:probe3	-0.211393914892023	0.0547450170560968	-3.86142750993043	0.000122944353706170	***
df.mm.trans2:probe4	-0.184846961250770	0.0547450170560968	-3.37650751047092	0.000773833181426502	***
df.mm.trans2:probe5	-0.194902609123836	0.0547450170560968	-3.56018902915165	0.000395117871279139	***
df.mm.trans2:probe6	-0.232178558033125	0.0547450170560968	-4.24109024927718	2.51661306109895e-05	***
df.mm.trans3:probe2	-0.234312023269557	0.0547450170560968	-4.28006119770607	2.12308595137127e-05	***
df.mm.trans3:probe3	-0.179401839682587	0.0547450170560968	-3.27704418282956	0.00109968167862096	** 
df.mm.trans3:probe4	-0.276564544909804	0.0547450170560968	-5.05186699688868	5.56038977594362e-07	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.23516174447557	0.175974098261047	24.0669609125824	3.31247057552109e-94	***
df.mm.trans1	-0.051424760454849	0.156268404932859	-0.329079704095935	0.742191812150758	   
df.mm.trans2	-0.0618408147541044	0.142146435499153	-0.435050056211032	0.663657376197276	   
df.mm.exp2	0.00424004556371722	0.191634518424990	0.0221256879948633	0.982353868499822	   
df.mm.exp3	0.107638435673798	0.191634518424990	0.561686049874828	0.574505954819437	   
df.mm.exp4	-0.118914597585161	0.191634518424990	-0.620528068546827	0.535107915181618	   
df.mm.exp5	0.163716290888645	0.191634518424990	0.854315246721728	0.393216483158297	   
df.mm.exp6	-0.0383807541399072	0.191634518424990	-0.200281006028307	0.841317768135671	   
df.mm.exp7	0.0919385424766306	0.191634518424990	0.479759822146119	0.631544905114962	   
df.mm.exp8	0.062818849748484	0.191634518424990	0.327805503229694	0.743154688297557	   
df.mm.trans1:exp2	0.0335779574278823	0.181965965826021	0.184528778639773	0.853650977552738	   
df.mm.trans2:exp2	0.066852466311114	0.153229055875116	0.436291054130098	0.662757276514236	   
df.mm.trans1:exp3	-0.0541333439432174	0.181965965826021	-0.297491586943103	0.766177642943857	   
df.mm.trans2:exp3	0.0397189024515943	0.153229055875116	0.259212603149926	0.795545818304238	   
df.mm.trans1:exp4	0.1876802850042	0.181965965826021	1.03140323055600	0.302700516375219	   
df.mm.trans2:exp4	0.299541086175541	0.153229055875116	1.95485826408584	0.0509890906470478	.  
df.mm.trans1:exp5	-0.0610829716926994	0.181965965826021	-0.335683496721037	0.737208026586778	   
df.mm.trans2:exp5	0.00372382707193001	0.153229055875116	0.0243023560424793	0.980618214536804	   
df.mm.trans1:exp6	0.0254318833540300	0.181965965826021	0.139761758406765	0.888887588133455	   
df.mm.trans2:exp6	0.173457163051454	0.153229055875116	1.13201221570421	0.258008797904276	   
df.mm.trans1:exp7	-0.063122946916625	0.181965965826021	-0.346894248218799	0.728772839550761	   
df.mm.trans2:exp7	-0.0208512790993713	0.153229055875116	-0.136079146218622	0.89179701635716	   
df.mm.trans1:exp8	0.058583958187874	0.181965965826021	0.321950085126835	0.747584612278383	   
df.mm.trans2:exp8	0.106056842443520	0.153229055875116	0.692145767248985	0.489070499738777	   
df.mm.trans1:probe2	-0.0222363435329428	0.0996668641811257	-0.223106683606825	0.82351619962396	   
df.mm.trans1:probe3	0.100010153166846	0.0996668641811257	1.00344436426831	0.315985973063652	   
df.mm.trans1:probe4	0.0854611053028185	0.0996668641811257	0.857467584688017	0.391473838787787	   
df.mm.trans1:probe5	0.0483398213363029	0.0996668641811257	0.485013968619043	0.627814997909736	   
df.mm.trans1:probe6	0.0441099335427197	0.0996668641811257	0.442573706970034	0.658207957305263	   
df.mm.trans1:probe7	0.0700222305065751	0.0996668641811257	0.702562793380586	0.482556918131177	   
df.mm.trans1:probe8	0.0833086477890456	0.0996668641811257	0.835871063803591	0.403506681568272	   
df.mm.trans1:probe9	0.280162062146041	0.0996668641811257	2.8109850194233	0.00507418910031781	** 
df.mm.trans1:probe10	0.0546845458763914	0.0996668641811257	0.548673286008202	0.583400963637842	   
df.mm.trans1:probe11	0.184480064579896	0.0996668641811257	1.85096687946997	0.0645865412034412	.  
df.mm.trans1:probe12	0.0377069599015616	0.0996668641811257	0.378329951597918	0.705297796757091	   
df.mm.trans1:probe13	0.0688573293916003	0.0996668641811257	0.690874845489923	0.489868420306062	   
df.mm.trans1:probe14	0.0212935500122347	0.0996668641811257	0.213647235590132	0.830883067803203	   
df.mm.trans1:probe15	-0.00125758278348329	0.0996668641811257	-0.0126178624542443	0.989936189297223	   
df.mm.trans1:probe16	0.0544289006548431	0.0996668641811257	0.546108288868494	0.585161854271697	   
df.mm.trans1:probe17	0.0190025318259785	0.0996668641811257	0.190660476599775	0.84884572722145	   
df.mm.trans1:probe18	0.078588049203266	0.0996668641811257	0.788507292257605	0.430661386699841	   
df.mm.trans1:probe19	0.0194932661336998	0.0996668641811257	0.195584222438005	0.844991178648765	   
df.mm.trans1:probe20	0.0427886345640483	0.0996668641811257	0.429316552854397	0.667822204391622	   
df.mm.trans1:probe21	0.153893850884027	0.0996668641811257	1.54408240038890	0.123010831466566	   
df.mm.trans1:probe22	0.079293529852735	0.0996668641811257	0.79558567939525	0.426536929176752	   
df.mm.trans2:probe2	0.0837497302680391	0.0996668641811257	0.84029663174553	0.401022988594608	   
df.mm.trans2:probe3	-0.0569169027301576	0.0996668641811257	-0.571071470922591	0.568130641209194	   
df.mm.trans2:probe4	0.0168051990060076	0.0996668641811257	0.168613702699298	0.866148187669885	   
df.mm.trans2:probe5	0.0114368601134355	0.0996668641811257	0.114750877409479	0.908674802176152	   
df.mm.trans2:probe6	-0.00931893663388905	0.0996668641811257	-0.0935008511650737	0.925531867112975	   
df.mm.trans3:probe2	-0.103398014547504	0.0996668641811257	-1.03743621711221	0.299883322187523	   
df.mm.trans3:probe3	0.0741446382658484	0.0996668641811257	0.743924662173624	0.457166452369263	   
df.mm.trans3:probe4	0.210327070089143	0.0996668641811257	2.11030086897199	0.035179195434386	*