chr12.5875_chr12_78480844_78486456_-_2.R 

fitVsDatCorrelation=0.926381310830731
cont.fitVsDatCorrelation=0.287778242996636

fstatistic=9017.27467618996,54,738
cont.fstatistic=1382.72432402048,54,738

residuals=-0.684194370503059,-0.0908055533073936,-0.00135328404220484,0.0799238035004437,0.963415844359081
cont.residuals=-0.75337712177564,-0.323594360855309,-0.098341908460005,0.2676375720746,1.87671653857947

predictedValues:
Include	Exclude	Both
chr12.5875_chr12_78480844_78486456_-_2.R.tl.Lung	71.0833911204567	71.946446038385	128.672842514914
chr12.5875_chr12_78480844_78486456_-_2.R.tl.cerebhem	70.7765748325473	69.27466226811	66.2618452027112
chr12.5875_chr12_78480844_78486456_-_2.R.tl.cortex	63.1642704187782	64.3707963595926	94.487636622307
chr12.5875_chr12_78480844_78486456_-_2.R.tl.heart	62.9091683384254	60.6067567204513	84.398738315374
chr12.5875_chr12_78480844_78486456_-_2.R.tl.kidney	74.8157965930526	69.1706045607948	88.2448541031962
chr12.5875_chr12_78480844_78486456_-_2.R.tl.liver	69.402192969521	67.6869397613643	88.6245776400912
chr12.5875_chr12_78480844_78486456_-_2.R.tl.stomach	71.7789010195956	63.1843035103686	85.476970468341
chr12.5875_chr12_78480844_78486456_-_2.R.tl.testicle	73.7817503637738	64.8546389123237	83.0127133027668


diffExp=-0.863054917928253,1.50191256443736,-1.20652594081437,2.30241161797411,5.64519203225777,1.71525320815668,8.59459750922707,8.9271114514501
diffExpScore=1.11366815242989
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	74.8992038227567	73.753225442491	70.220349434641
cerebhem	68.2219126466362	59.9668763975256	75.0070668841651
cortex	76.2295904384135	78.4469467362103	79.1205911629323
heart	72.7306404130766	61.8086606954516	67.5428028913232
kidney	59.6374351424615	69.8965516102595	66.989029142817
liver	75.0924002995218	69.7807196570133	68.0331032386157
stomach	73.0298512425752	81.2250236007697	95.281153135202
testicle	78.9961395240718	78.4340305751482	65.299248370929
cont.diffExp=1.14597838026570,8.25503624911061,-2.21735629779673,10.9219797176250,-10.259116467798,5.31168064250856,-8.1951723581945,0.562108948923637
cont.diffExpScore=7.1827481979443

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=0.547388148629046
cont.tran.correlation=0.440879132500999

tran.covariance=0.0020904726899303
cont.tran.covariance=0.00403052965774309

tran.mean=68.0504496117213
cont.tran.mean=72.0093255152739

weightedLogRatios:
wLogRatio
Lung	-0.0515304013273951
cerebhem	0.0911320222582254
cortex	-0.0786215994815853
heart	0.153730071633372
kidney	0.335449809604962
liver	0.105791753615534
stomach	0.536898405573196
testicle	0.546368398802981

cont.weightedLogRatios:
wLogRatio
Lung	0.0664297253508546
cerebhem	0.536307654529087
cortex	-0.124672001016464
heart	0.684300102259769
kidney	-0.661542869281244
liver	0.314137243706481
stomach	-0.462011399587939
testicle	0.0311767644430304

varWeightedLogRatios=0.0593416954795624
cont.varWeightedLogRatios=0.215450317594115

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.34981729194288	0.086138640978767	38.8886712615841	7.72349008666363e-181	***
df.mm.trans1	0.679374822506016	0.0758804729185002	8.95322335742032	2.76951974857416e-18	***
df.mm.trans2	1.00744466462833	0.0684692678822212	14.7138226504964	3.66438708939964e-43	***
df.mm.exp2	0.621490383690118	0.0911806845263281	6.81603112455978	1.94612420651717e-11	***
df.mm.exp3	0.0794271914278153	0.0911806845263281	0.87109667842953	0.383984639027106	   
df.mm.exp4	0.128043175488188	0.0911806845263281	1.40427960322250	0.160656303807438	   
df.mm.exp5	0.388986976786046	0.0911806845263281	4.26611160912843	2.24795294018847e-05	***
df.mm.exp6	0.287899825320355	0.0911806845263281	3.15746505760466	0.00165625157145619	** 
df.mm.exp7	0.288896825497822	0.0911806845263281	3.16839939290436	0.00159600928708875	** 
df.mm.exp8	0.371763419335009	0.0911806845263281	4.07721680601842	5.05300073223977e-05	***
df.mm.trans1:exp2	-0.625816012337397	0.086005471137249	-7.27646746261885	8.78026404870387e-13	***
df.mm.trans2:exp2	-0.659333205421172	0.0703681127486582	-9.36977246748378	8.65100550081712e-20	***
df.mm.trans1:exp3	-0.197542102268106	0.086005471137249	-2.29685506812543	0.0219062162963204	*  
df.mm.trans2:exp3	-0.190689171077892	0.0703681127486582	-2.70988042210252	0.00688697673361178	** 
df.mm.trans1:exp4	-0.250204972508854	0.086005471137249	-2.90917506991587	0.00373276515735735	** 
df.mm.trans2:exp4	-0.299558828824526	0.0703681127486582	-4.25702519398942	2.33895867512174e-05	***
df.mm.trans1:exp5	-0.337811640355131	0.086005471137249	-3.92779245190164	9.37692661640542e-05	***
df.mm.trans2:exp5	-0.428333031228389	0.0703681127486582	-6.08703309634457	1.84822309450603e-09	***
df.mm.trans1:exp6	-0.31183506997471	0.086005471137249	-3.62575852270001	0.000307919000922933	***
df.mm.trans2:exp6	-0.348928614667238	0.0703681127486582	-4.95861834341849	8.81570661292269e-07	***
df.mm.trans1:exp7	-0.279159960946396	0.086005471137249	-3.24583956410061	0.00122390424128614	** 
df.mm.trans2:exp7	-0.418762954603139	0.0703681127486582	-5.95103290746026	4.11625134024459e-09	***
df.mm.trans1:exp8	-0.334505714004615	0.086005471137249	-3.88935389320529	0.000109581788718786	***
df.mm.trans2:exp8	-0.475537015406379	0.0703681127486582	-6.75784807679736	2.84413239586559e-11	***
df.mm.trans1:probe2	0.484602163732696	0.050216376354347	9.6502814204105	7.83207010535864e-21	***
df.mm.trans1:probe3	0.0674242640294325	0.050216376354347	1.34267481894073	0.179790115648029	   
df.mm.trans1:probe4	-0.0372465334540742	0.050216376354347	-0.741720852003492	0.458492453781188	   
df.mm.trans1:probe5	0.0763557968083999	0.050216376354347	1.52053577640893	0.128804679279595	   
df.mm.trans1:probe6	-0.113883511612190	0.050216376354347	-2.26785602387123	0.0236262394115116	*  
df.mm.trans1:probe7	-0.033955455718131	0.050216376354347	-0.676182914484463	0.499136364914437	   
df.mm.trans1:probe8	0.326574400884239	0.050216376354347	6.503344617696	1.44763564439259e-10	***
df.mm.trans1:probe9	-0.0345255856457183	0.050216376354347	-0.687536380604046	0.491960795504396	   
df.mm.trans1:probe10	0.555221508199702	0.050216376354347	11.0565825037202	2.11174566648338e-26	***
df.mm.trans1:probe11	0.867474077947691	0.050216376354347	17.2747247198094	2.07670529394973e-56	***
df.mm.trans1:probe12	0.878531150151112	0.050216376354347	17.4949132918680	1.36168801239526e-57	***
df.mm.trans1:probe13	0.737159546716573	0.050216376354347	14.6796642894915	5.41294257237125e-43	***
df.mm.trans1:probe14	1.07130804599488	0.050216376354347	21.3338381574031	4.90624909404248e-79	***
df.mm.trans1:probe15	1.25808995738398	0.050216376354347	25.0533799672520	1.0136221905283e-100	***
df.mm.trans1:probe16	1.04198406068678	0.050216376354347	20.7498855220880	1.08007800931634e-75	***
df.mm.trans1:probe17	-0.16549008097572	0.050216376354347	-3.29554008054972	0.00102927290140268	** 
df.mm.trans1:probe18	-0.166891387757401	0.050216376354347	-3.32344545491989	0.000932992747665873	***
df.mm.trans1:probe19	-0.0337775862310681	0.050216376354347	-0.672640853109747	0.501386352672506	   
df.mm.trans1:probe20	-0.195536740237488	0.050216376354347	-3.89388391662715	0.000107595021975934	***
df.mm.trans1:probe21	-0.137526798361037	0.050216376354347	-2.73868423700253	0.00631732435477958	** 
df.mm.trans1:probe22	-0.110028195050077	0.050216376354347	-2.19108193457994	0.0287578161749941	*  
df.mm.trans2:probe2	-0.111086295996744	0.050216376354347	-2.21215276890698	0.0272616263219536	*  
df.mm.trans2:probe3	-0.207330297221589	0.050216376354347	-4.12873871580424	4.0641345744758e-05	***
df.mm.trans2:probe4	-0.217302056013486	0.050216376354347	-4.32731454934372	1.71739076114712e-05	***
df.mm.trans2:probe5	-0.285705701302371	0.050216376354347	-5.68949259274139	1.83748883159701e-08	***
df.mm.trans2:probe6	-0.0733147621815654	0.050216376354347	-1.45997715295558	0.144721894368765	   
df.mm.trans3:probe2	-0.274496225621702	0.050216376354347	-5.46626908490461	6.29213901892364e-08	***
df.mm.trans3:probe3	-0.0716942190476315	0.050216376354347	-1.42770594480430	0.153799516323095	   
df.mm.trans3:probe4	-0.121891269702010	0.050216376354347	-2.42732109624749	0.0154490624035508	*  
df.mm.trans3:probe5	-0.428736788687869	0.050216376354347	-8.5377882637833	7.76663790031715e-17	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24680847024773	0.21905895280573	19.3866008024514	5.4659848801493e-68	***
df.mm.trans1	-0.00493340096158902	0.192971432414723	-0.0255654471745146	0.979610857285697	   
df.mm.trans2	0.0251307594892876	0.174124016251331	0.144326785186334	0.885281830929317	   
df.mm.exp2	-0.366254014094623	0.231881360577428	-1.57948880920218	0.114652468112411	   
df.mm.exp3	-0.0400307298457317	0.231881360577428	-0.172634530632595	0.862986040272864	   
df.mm.exp4	-0.167185101656930	0.231881360577428	-0.720994137866913	0.471141448250762	   
df.mm.exp5	-0.234458906360286	0.231881360577428	-1.01111579549318	0.312292395685489	   
df.mm.exp6	-0.0211471335476870	0.231881360577428	-0.0911980742868967	0.927359952291909	   
df.mm.exp7	-0.23397021942102	0.231881360577428	-1.00900830855223	0.313301350518387	   
df.mm.exp8	0.187446512646436	0.231881360577428	0.808372489188693	0.419136683834180	   
df.mm.trans1:exp2	0.272876566545422	0.218720288929719	1.24760518505490	0.212571408276693	   
df.mm.trans2:exp2	0.159321634757206	0.178952963669770	0.890298944985394	0.373595520952901	   
df.mm.trans1:exp3	0.0576371825258126	0.218720288929719	0.263520054805401	0.792223327518055	   
df.mm.trans2:exp3	0.101728559320499	0.178952963669770	0.568465351086465	0.569891955917922	   
df.mm.trans1:exp4	0.137804600537276	0.218720288929719	0.630049462770949	0.528857243360058	   
df.mm.trans2:exp4	-0.00949613207214288	0.178952963669770	-0.053064961190956	0.957694509450112	   
df.mm.trans1:exp5	0.00659912907551608	0.218720288929719	0.0301715451630396	0.975938399139632	   
df.mm.trans2:exp5	0.180750492119543	0.178952963669770	1.01004469785195	0.312804912984653	   
df.mm.trans1:exp6	0.0237232321865127	0.218720288929719	0.108463793197236	0.913657282016547	   
df.mm.trans2:exp6	-0.0342198465964176	0.178952963669770	-0.191222575444825	0.848403812255924	   
df.mm.trans1:exp7	0.20869523751818	0.218720288929719	0.954164968139925	0.340312564040481	   
df.mm.trans2:exp7	0.330468862459530	0.178952963669770	1.8466800196132	0.0651937055784143	.  
df.mm.trans1:exp8	-0.134190788754275	0.218720288929719	-0.613526936211184	0.539717023706131	   
df.mm.trans2:exp8	-0.12591334508687	0.178952963669770	-0.703611398798757	0.481896734006239	   
df.mm.trans1:probe2	0.206296600566554	0.127705135498867	1.61541350518660	0.106648574947917	   
df.mm.trans1:probe3	0.0669310370015932	0.127705135498867	0.524106072478088	0.600362129324979	   
df.mm.trans1:probe4	0.156538559036777	0.127705135498867	1.22578123757729	0.220672018929451	   
df.mm.trans1:probe5	-0.0052398615269438	0.127705135498867	-0.0410309382349803	0.96728232900851	   
df.mm.trans1:probe6	0.0218888919945888	0.127705135498867	0.171401814884594	0.863954812859672	   
df.mm.trans1:probe7	0.119180650226294	0.127705135498867	0.933248688556862	0.350996805442454	   
df.mm.trans1:probe8	0.0975383298928841	0.127705135498867	0.763777662596424	0.445243854882323	   
df.mm.trans1:probe9	0.130627379163218	0.127705135498867	1.02288274197381	0.306698462762372	   
df.mm.trans1:probe10	0.0914368996183225	0.127705135498867	0.716000176979052	0.474217725787153	   
df.mm.trans1:probe11	0.154107733100371	0.127705135498867	1.20674656111804	0.227916425822614	   
df.mm.trans1:probe12	0.168858545574740	0.127705135498867	1.32225336839518	0.186493440553438	   
df.mm.trans1:probe13	-0.0328832473138361	0.127705135498867	-0.257493539201701	0.796869580900668	   
df.mm.trans1:probe14	-0.0195670221878068	0.127705135498867	-0.15322032361009	0.87826641470014	   
df.mm.trans1:probe15	-0.0686088646198962	0.127705135498867	-0.537244366500085	0.591260768827461	   
df.mm.trans1:probe16	0.201230001118271	0.127705135498867	1.57573930235607	0.115514444272221	   
df.mm.trans1:probe17	0.255797447865521	0.127705135498867	2.00303180342963	0.0455391267845416	*  
df.mm.trans1:probe18	-0.0292159923805079	0.127705135498867	-0.228776957687556	0.819105656605583	   
df.mm.trans1:probe19	0.295833631057808	0.127705135498867	2.31653668352619	0.0208019802265222	*  
df.mm.trans1:probe20	0.0308182190557567	0.127705135498867	0.241323255602592	0.809371620173017	   
df.mm.trans1:probe21	-0.0246286147329052	0.127705135498867	-0.192855319691695	0.84712533724468	   
df.mm.trans1:probe22	0.188300842880797	0.127705135498867	1.47449702899745	0.140774259409761	   
df.mm.trans2:probe2	0.0278187045267716	0.127705135498867	0.217835441136339	0.827617544745849	   
df.mm.trans2:probe3	0.155411232349342	0.127705135498867	1.21695366237422	0.224010866834182	   
df.mm.trans2:probe4	0.000181412661270966	0.127705135498867	0.00142055885663718	0.99886694229	   
df.mm.trans2:probe5	0.0311749627799286	0.127705135498867	0.244116751124744	0.807208248340685	   
df.mm.trans2:probe6	0.102054180422814	0.127705135498867	0.79913920473245	0.424466813389997	   
df.mm.trans3:probe2	0.0724532369062492	0.127705135498867	0.567347872293609	0.570650391611254	   
df.mm.trans3:probe3	-0.0312663439806954	0.127705135498867	-0.244832315149713	0.806654329725651	   
df.mm.trans3:probe4	-0.0425152324825767	0.127705135498867	-0.332917171392485	0.739291357177669	   
df.mm.trans3:probe5	-0.0755100692621122	0.127705135498867	-0.591284516218866	0.554510858373078