chr3.15550_chr3_19694527_19703905_+_2.R 

fitVsDatCorrelation=0.92268801172531
cont.fitVsDatCorrelation=0.250362615832916

fstatistic=9334.67198140307,56,784
cont.fstatistic=1468.58078030991,56,784

residuals=-0.720956204064691,-0.0945777105153471,-0.00257400099697492,0.0851298474118678,0.832580910565657
cont.residuals=-0.844699009051784,-0.280664004240698,-0.105136569658395,0.170059164202912,1.76723357912668

predictedValues:
Include	Exclude	Both
chr3.15550_chr3_19694527_19703905_+_2.R.tl.Lung	81.3593559717253	67.3590009969931	133.395719513626
chr3.15550_chr3_19694527_19703905_+_2.R.tl.cerebhem	57.0242598971402	53.9595567750258	61.6053711098908
chr3.15550_chr3_19694527_19703905_+_2.R.tl.cortex	54.8965904399784	54.5337866045436	69.8446653971985
chr3.15550_chr3_19694527_19703905_+_2.R.tl.heart	71.5901929227992	60.5750249337321	109.803872207985
chr3.15550_chr3_19694527_19703905_+_2.R.tl.kidney	60.3251753771398	74.6476826672019	69.3484073556687
chr3.15550_chr3_19694527_19703905_+_2.R.tl.liver	156.571388105651	69.4532284346006	240.392772817499
chr3.15550_chr3_19694527_19703905_+_2.R.tl.stomach	54.9807609351393	58.2091537673486	65.4320069914547
chr3.15550_chr3_19694527_19703905_+_2.R.tl.testicle	57.940229314418	63.6499386713462	70.8856746684119


diffExp=14.0003549747322,3.06470312211444,0.362803835434796,11.0151679890670,-14.3225072900621,87.11815967105,-3.22839283220938,-5.70970935692822
diffExpScore=1.4878985629368
diffExp1.5=0,0,0,0,0,1,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,0,0,0,1,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,0,1,0,0
diffExp1.3Score=0.5
diffExp1.2=1,0,0,0,-1,1,0,0
diffExp1.2Score=1.5

cont.predictedValues:
Include	Exclude	Both
Lung	73.0038730723412	64.9247374139051	71.7308137129384
cerebhem	70.441626676788	71.9370818400336	65.2260095967069
cortex	76.2921697040737	69.3379812557419	75.8093939580842
heart	75.6665981414545	72.8165464736206	71.2998655616134
kidney	78.5754697855432	87.3855079063443	75.0507870632011
liver	73.8938793575152	67.5100541282117	79.462924648341
stomach	72.546231432136	67.9065495847975	84.2948422105183
testicle	77.2252042773171	74.369415718297	81.5527411790927
cont.diffExp=8.07913565843612,-1.49545516324559,6.95418844833176,2.85005166783387,-8.81003812080114,6.38382522930348,4.63968184733851,2.85578855902018
cont.diffExpScore=1.87326138920362

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=0.454723701365931
cont.tran.correlation=0.661459323914208

tran.covariance=0.0208555639601903
cont.tran.covariance=0.00214951797437984

tran.mean=68.5672078634239
cont.tran.mean=73.3645579230075

weightedLogRatios:
wLogRatio
Lung	0.812850479998484
cerebhem	0.221843794517492
cortex	0.0265373398784210
heart	0.699615002641005
kidney	-0.896060367205122
liver	3.77742078836960
stomach	-0.230263548369201
testicle	-0.3859462841383

cont.weightedLogRatios:
wLogRatio
Lung	0.496329791263858
cerebhem	-0.0896030283328367
cortex	0.4097197871379
heart	0.165366641599660
kidney	-0.469414792201188
liver	0.384675652299551
stomach	0.280966936687421
testicle	0.163079504862876

varWeightedLogRatios=2.06397601383255
cont.varWeightedLogRatios=0.099803688762355

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.12703821342519	0.0834152066540028	37.4876277223146	5.26140678761801e-177	***
df.mm.trans1	1.06216695116707	0.0727038303080804	14.6095047078836	6.2535686499027e-43	***
df.mm.trans2	1.013838660902	0.0648803228380346	15.6262887814680	4.03372230803557e-48	***
df.mm.exp2	0.195370217208119	0.0848836097694028	2.30162475110174	0.0216177011167749	*  
df.mm.exp3	0.0424056488530240	0.0848836097694028	0.499574051671746	0.617515199675183	   
df.mm.exp4	-0.0394473514915586	0.0848836097694028	-0.46472283163643	0.642258988698412	   
df.mm.exp5	0.45779348881244	0.0848836097694028	5.39319062957024	9.1698297676675e-08	***
df.mm.exp6	0.0962991452280855	0.0848836097694028	1.13448456645157	0.256938089647472	   
df.mm.exp7	0.174422074590491	0.0848836097694028	2.05483809023121	0.0402255277436468	*  
df.mm.exp8	0.236149618704955	0.0848836097694028	2.78204024718654	0.00553161359793469	** 
df.mm.trans1:exp2	-0.55076926361412	0.0792628957989068	-6.94863918435991	7.76003753542987e-12	***
df.mm.trans2:exp2	-0.417171938875961	0.0618246323478427	-6.74766550213893	2.91994399819338e-11	***
df.mm.trans1:exp3	-0.435830243108442	0.0792628957989068	-5.49854050518367	5.18409563019545e-08	***
df.mm.trans2:exp3	-0.253621740587129	0.0618246323478427	-4.10227656769848	4.51877935006149e-05	***
df.mm.trans1:exp4	-0.0884703901989904	0.0792628957989067	-1.1161639920833	0.264693918907734	   
df.mm.trans2:exp4	-0.0667065092077618	0.0618246323478427	-1.07896329787215	0.280935923483078	   
df.mm.trans1:exp5	-0.75691980602449	0.0792628957989068	-9.5494846408946	1.61565283048257e-20	***
df.mm.trans2:exp5	-0.35505054696471	0.0618246323478427	-5.74286548065658	1.33127303596933e-08	***
df.mm.trans1:exp6	0.55833707885133	0.0792628957989067	7.04411658473662	4.08740507771576e-12	***
df.mm.trans2:exp6	-0.0656821303881315	0.0618246323478427	-1.06239419295833	0.288383903646339	   
df.mm.trans1:exp7	-0.566314587655896	0.0792628957989068	-7.14476277895095	2.06295666226484e-12	***
df.mm.trans2:exp7	-0.320415990013932	0.0618246323478427	-5.18265904455657	2.78505234932330e-07	***
df.mm.trans1:exp8	-0.57561350450434	0.0792628957989067	-7.26208017891115	9.20180422531146e-13	***
df.mm.trans2:exp8	-0.292787796250880	0.0618246323478427	-4.73577901124544	2.58979908442417e-06	***
df.mm.trans1:probe2	0.122543238214543	0.0503706911993846	2.43282820419268	0.0152040564161145	*  
df.mm.trans1:probe3	0.0123378961182365	0.0503706911993846	0.244941965743510	0.806565463266674	   
df.mm.trans1:probe4	0.221158373844346	0.0503706911993845	4.39061622102672	1.28530817361446e-05	***
df.mm.trans1:probe5	0.147875922193389	0.0503706911993846	2.93575328573605	0.00342468948180346	** 
df.mm.trans1:probe6	0.183355888873381	0.0503706911993845	3.64013049071721	0.000290379163484121	***
df.mm.trans1:probe7	0.0077639249254681	0.0503706911993846	0.154135763091592	0.87754235787495	   
df.mm.trans1:probe8	-0.0288044789110466	0.0503706911993845	-0.571849983098872	0.567587526887352	   
df.mm.trans1:probe9	0.116615738526370	0.0503706911993846	2.31515065109520	0.0208620468835624	*  
df.mm.trans1:probe10	0.182935124061641	0.0503706911993846	3.63177712486653	0.000299782038603182	***
df.mm.trans1:probe11	0.298471793631405	0.0503706911993846	5.9255052198897	4.66049233525529e-09	***
df.mm.trans1:probe12	0.29286277955943	0.0503706911993845	5.81415050272346	8.86793048153702e-09	***
df.mm.trans1:probe13	0.268773558314781	0.0503706911993846	5.33591165646075	1.24531892877788e-07	***
df.mm.trans1:probe14	0.373231209810848	0.0503706911993846	7.40969005832123	3.28040276617469e-13	***
df.mm.trans1:probe15	0.278533853054123	0.0503706911993845	5.52968097959169	4.37181760730698e-08	***
df.mm.trans1:probe16	0.262474040405340	0.0503706911993845	5.21084849454173	2.40547990803013e-07	***
df.mm.trans1:probe17	0.512303830094112	0.0503706911993846	10.1706730222588	6.57936857687073e-23	***
df.mm.trans1:probe18	0.467603285518302	0.0503706911993846	9.28324139264572	1.57495756993278e-19	***
df.mm.trans1:probe19	0.657032959502918	0.0503706911993846	13.0439536138616	2.45267826070922e-35	***
df.mm.trans1:probe20	0.792036912937502	0.0503706911993846	15.7241620886707	1.24843718292396e-48	***
df.mm.trans1:probe21	0.440622628902171	0.0503706911993845	8.74759941566089	1.31870051281652e-17	***
df.mm.trans1:probe22	0.470720989039795	0.0503706911993846	9.3451365830284	9.31764171285996e-20	***
df.mm.trans2:probe2	0.120084075733801	0.0503706911993845	2.38400690708149	0.0173622705000587	*  
df.mm.trans2:probe3	0.22212636051606	0.0503706911993846	4.40983348107746	1.17889631550372e-05	***
df.mm.trans2:probe4	0.112467201749296	0.0503706911993846	2.23279051907610	0.0258443393945490	*  
df.mm.trans2:probe5	0.228131912408797	0.0503706911993845	4.52906059013111	6.84612252617588e-06	***
df.mm.trans2:probe6	0.216266090590200	0.0503706911993845	4.29349062799523	1.97932170373994e-05	***
df.mm.trans3:probe2	0.076388769682529	0.0503706911993846	1.51653209165139	0.129787947098028	   
df.mm.trans3:probe3	-0.569663992144626	0.0503706911993846	-11.3094336920988	1.41197623728657e-27	***
df.mm.trans3:probe4	-0.289840417547656	0.0503706911993846	-5.75414810966893	1.24872248686533e-08	***
df.mm.trans3:probe5	-0.372414260625844	0.0503706911993846	-7.39347131751081	3.67717512789972e-13	***
df.mm.trans3:probe6	-0.66414638986069	0.0503706911993845	-13.1851752288205	5.32389335292942e-36	***
df.mm.trans3:probe7	-0.348390170424654	0.0503706911993846	-6.91652550578681	9.61138404241698e-12	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.06669025410759	0.209464779119501	19.4146732983091	7.34130691359043e-69	***
df.mm.trans1	0.151402992456030	0.182567332354537	0.829299472711864	0.407187386970098	   
df.mm.trans2	0.0481522191523711	0.162921642678909	0.295554466310353	0.767648609509628	   
df.mm.exp2	0.161897146075356	0.213152101210561	0.759538119286128	0.447759034636209	   
df.mm.exp3	0.0545201237960609	0.213152101210561	0.255780372261982	0.798187523066773	   
df.mm.exp4	0.156564802977354	0.213152101210561	0.734521508763793	0.462850585201435	   
df.mm.exp5	0.325403177326691	0.213152101210561	1.52662430010598	0.127257767080958	   
df.mm.exp6	-0.0512048126390316	0.213152101210561	-0.240226637918287	0.810217362400014	   
df.mm.exp7	-0.122784951078503	0.213152101210561	-0.576043822139994	0.564750879493266	   
df.mm.exp8	0.063699925880513	0.213152101210561	0.298847280973259	0.765135768330944	   
df.mm.trans1:exp2	-0.197625265157166	0.199037868835554	-0.99290283961212	0.321063646550339	   
df.mm.trans2:exp2	-0.059333985521196	0.155248467016341	-0.382187255446141	0.702426049118216	   
df.mm.trans1:exp3	-0.0104623114088819	0.199037868835554	-0.052564426408353	0.95809235150967	   
df.mm.trans2:exp3	0.0112439892447946	0.155248467016341	0.0724257666493485	0.94228155209943	   
df.mm.trans1:exp4	-0.120740475310494	0.199037868835554	-0.606620619567882	0.544278327694586	   
df.mm.trans2:exp4	-0.041850299962753	0.155248467016341	-0.269569811329267	0.787562160743274	   
df.mm.trans1:exp5	-0.251856111370444	0.199037868835554	-1.26536780585472	0.206115445461100	   
df.mm.trans2:exp5	-0.0283024349302041	0.155248467016341	-0.182304118514903	0.855391193940597	   
df.mm.trans1:exp6	0.0633223183283497	0.199037868835554	0.318142063612362	0.75046190115002	   
df.mm.trans2:exp6	0.0902526363852575	0.155248467016341	0.58134317278481	0.561176282554936	   
df.mm.trans1:exp7	0.116496489110402	0.199037868835554	0.585298113328635	0.55851570460613	   
df.mm.trans2:exp7	0.167688727178743	0.155248467016341	1.08013129148059	0.280415880607399	   
df.mm.trans1:exp8	-0.00748653738322154	0.199037868835554	-0.0376136331594615	0.970005313098399	   
df.mm.trans2:exp8	0.0721161392993447	0.155248467016341	0.464520781978182	0.642403642564573	   
df.mm.trans1:probe2	0.104402705034583	0.126486358176149	0.825406838650445	0.409391735423756	   
df.mm.trans1:probe3	-0.0354777816204829	0.126486358176149	-0.280487019565188	0.779177879025357	   
df.mm.trans1:probe4	-0.0337270195826273	0.126486358176149	-0.266645510780364	0.789812227105599	   
df.mm.trans1:probe5	0.0626398751550077	0.126486358176149	0.495230284579571	0.620576342867551	   
df.mm.trans1:probe6	0.154517018092569	0.126486358176149	1.22161014294825	0.222222287013893	   
df.mm.trans1:probe7	0.0891067856271848	0.126486358176149	0.704477438611142	0.481344701024074	   
df.mm.trans1:probe8	0.0712381874783071	0.126486358176149	0.563208463786257	0.573453973280181	   
df.mm.trans1:probe9	0.226775168753732	0.126486358176149	1.79288242640299	0.0733771109864483	.  
df.mm.trans1:probe10	0.126350967884785	0.126486358176149	0.998929605585011	0.318137000650472	   
df.mm.trans1:probe11	0.154455748022624	0.126486358176149	1.22112574233123	0.222405507536542	   
df.mm.trans1:probe12	0.132403770185504	0.126486358176149	1.04678300565121	0.295522280612198	   
df.mm.trans1:probe13	0.0709631634946643	0.126486358176149	0.561034126667152	0.574934582528106	   
df.mm.trans1:probe14	0.112558000386633	0.126486358176149	0.889882529702379	0.37380194148874	   
df.mm.trans1:probe15	0.0512089434617792	0.126486358176149	0.404857442337489	0.685692739063221	   
df.mm.trans1:probe16	0.127838239890517	0.126486358176149	1.01068796456678	0.312477615980331	   
df.mm.trans1:probe17	0.0246598719253564	0.126486358176149	0.194960723677523	0.845474206712446	   
df.mm.trans1:probe18	0.145551093722861	0.126486358176149	1.15072562623838	0.250195975637322	   
df.mm.trans1:probe19	0.0407098099840170	0.126486358176149	0.321851388331722	0.747651075715821	   
df.mm.trans1:probe20	0.0429452527413751	0.126486358176149	0.339524778486928	0.734305364579009	   
df.mm.trans1:probe21	0.238542410522050	0.126486358176149	1.88591413304704	0.0596759643816493	.  
df.mm.trans1:probe22	0.192496008762678	0.126486358176149	1.52187169856375	0.128444442386272	   
df.mm.trans2:probe2	0.0760341870764044	0.126486358176149	0.601125593089785	0.547930093719355	   
df.mm.trans2:probe3	0.185547941987657	0.126486358176149	1.46694034568738	0.142793288484052	   
df.mm.trans2:probe4	0.00563485801274662	0.126486358176149	0.0445491363179209	0.964478029651025	   
df.mm.trans2:probe5	0.112920872036823	0.126486358176149	0.89275138967608	0.372264259339882	   
df.mm.trans2:probe6	0.378883258649407	0.126486358176149	2.99544760488528	0.00282672643490355	** 
df.mm.trans3:probe2	0.0219328121462832	0.126486358176149	0.173400613809585	0.862381301672223	   
df.mm.trans3:probe3	0.102362020642015	0.126486358176149	0.809273206360028	0.418603544445569	   
df.mm.trans3:probe4	-0.144141340869873	0.126486358176149	-1.13958013297479	0.254809311400487	   
df.mm.trans3:probe5	0.0405364748983633	0.126486358176149	0.320481002717391	0.74868912744756	   
df.mm.trans3:probe6	-0.152251266327970	0.126486358176149	-1.20369713005683	0.229069973379652	   
df.mm.trans3:probe7	0.178285938780257	0.126486358176149	1.40952701422529	0.159075930458468