chr2.14412_chr2_157342605_157346408_+_2.R fitVsDatCorrelation=0.912936336232076 cont.fitVsDatCorrelation=0.273934355241858 fstatistic=4016.18632672538,42,462 cont.fstatistic=714.130615658049,42,462 residuals=-0.675980829736588,-0.128865497933397,0.0026498756277306,0.124317363775147,0.793372951485111 cont.residuals=-0.926328999189773,-0.340564874593848,-0.138354437426319,0.186071299955414,2.17923445489333 predictedValues: Include Exclude Both chr2.14412_chr2_157342605_157346408_+_2.R.tl.Lung 71.5651291030753 80.2937118131445 61.9802833094327 chr2.14412_chr2_157342605_157346408_+_2.R.tl.cerebhem 142.894272994033 69.0533036479096 132.106623419737 chr2.14412_chr2_157342605_157346408_+_2.R.tl.cortex 170.845027126546 66.3930913196327 178.389737415108 chr2.14412_chr2_157342605_157346408_+_2.R.tl.heart 61.41947142507 69.3482330619943 59.2516915955643 chr2.14412_chr2_157342605_157346408_+_2.R.tl.kidney 70.5276079625204 85.7435079893618 61.1015098336778 chr2.14412_chr2_157342605_157346408_+_2.R.tl.liver 60.3262030413755 75.4008120064748 49.2152931395609 chr2.14412_chr2_157342605_157346408_+_2.R.tl.stomach 70.2893252346756 68.4579906252443 61.5472445134932 chr2.14412_chr2_157342605_157346408_+_2.R.tl.testicle 66.6774453295017 73.5041457552241 62.1558599093501 diffExp=-8.72858271006918,73.8409693461233,104.451935806913,-7.92876163692422,-15.2159000268414,-15.0746089650993,1.83133460943138,-6.82670042572241 diffExpScore=1.83666564777509 diffExp1.5=0,1,1,0,0,0,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,1,1,0,0,0,0,0 diffExp1.4Score=0.666666666666667 diffExp1.3=0,1,1,0,0,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=0,1,1,0,-1,-1,0,0 diffExp1.2Score=4 cont.predictedValues: Include Exclude Both Lung 73.3813578260381 69.8514663264682 85.4716209840037 cerebhem 80.2023001778943 113.517577106161 111.109652120248 cortex 101.028950917818 90.2227340646859 92.4465237103595 heart 83.6283166241591 87.3077496608812 102.062558545374 kidney 82.7528793470228 88.9972764928412 72.5786573417156 liver 87.8552114820998 103.640715807510 71.6236425563259 stomach 77.3462068518747 84.6090399851657 105.848786653359 testicle 83.7974923907472 72.0247554305752 70.4683235962208 cont.diffExp=3.52989149956984,-33.3152769282664,10.8062168531317,-3.67943303672209,-6.24439714581841,-15.7855043254106,-7.26283313329102,11.7727369601720 cont.diffExpScore=2.24379390145221 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,-1,0,0,0,0,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,-1,0,0,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,-1,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=-0.508195153395035 cont.tran.correlation=0.260877937609784 tran.covariance=-0.0177872309552046 cont.tran.covariance=0.00497193123067296 tran.mean=81.4212049022365 cont.tran.mean=86.2602519057464 weightedLogRatios: wLogRatio Lung -0.498098076973565 cerebhem 3.34414415157005 cortex 4.41219027535276 heart -0.507319352203311 kidney -0.850518566126775 liver -0.939335023381585 stomach 0.111919248750118 testicle -0.414132976827263 cont.weightedLogRatios: wLogRatio Lung 0.210556376797861 cerebhem -1.58356281140773 cortex 0.515722370626614 heart -0.191513918121707 kidney -0.323886358313239 liver -0.753215755997803 stomach -0.39428483034469 testicle 0.65897015442531 varWeightedLogRatios=4.31897883817503 cont.varWeightedLogRatios=0.526225113762278 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.84802603417219 0.132391713970945 29.0654597538989 2.24655226454086e-106 *** df.mm.trans1 -0.088837275356731 0.116660359276726 -0.761503529626573 0.446744901758103 df.mm.trans2 0.610768440583148 0.110300466094781 5.53731513752911 5.16104783406594e-08 *** df.mm.exp2 -0.21610853710849 0.151970871200969 -1.42203920659706 0.155689612501492 df.mm.exp3 -0.377103734148452 0.151970871200969 -2.48142115109522 0.0134406183546080 * df.mm.exp4 -0.254409670308616 0.151970871200969 -1.67406864419550 0.0947939126855384 . df.mm.exp5 0.0653451158244377 0.151970871200969 0.429984478657256 0.667407417274514 df.mm.exp6 -0.00310273062663568 0.151970871200969 -0.0204166140663402 0.983719844938547 df.mm.exp7 -0.170447777874895 0.151970871200969 -1.12158189610884 0.262622856458313 df.mm.exp8 -0.161919463361201 0.151970871200969 -1.06546380948935 0.287222594696725 df.mm.trans1:exp2 0.907605612590568 0.140697687137803 6.45075005178754 2.81226052995417e-10 *** df.mm.trans2:exp2 0.0652959508964487 0.128438828390298 0.508381707578554 0.611428337283197 df.mm.trans1:exp3 1.24725267399070 0.140697687137803 8.86477026995556 1.67371284307827e-17 *** df.mm.trans2:exp3 0.187005429618285 0.128438828390298 1.45598828611248 0.146075059724627 df.mm.trans1:exp4 0.101528647743301 0.140697687137803 0.721608505503448 0.470900242480123 df.mm.trans2:exp4 0.107859028978470 0.128438828390298 0.839769642328947 0.401471903838720 df.mm.trans1:exp5 -0.0799488119891044 0.140697687137803 -0.568231174339068 0.570154074201026 df.mm.trans2:exp5 0.000323949568421374 0.128438828390298 0.00252220899615310 0.997988659203626 df.mm.trans1:exp6 -0.167738647026281 0.140697687137803 -1.19219192894048 0.233797992110195 df.mm.trans2:exp6 -0.0597705343090815 0.128438828390298 -0.465361877386888 0.641891608255596 df.mm.trans1:exp7 0.152459787650353 0.140697687137803 1.08359839277976 0.279108082209015 df.mm.trans2:exp7 0.0109767502605468 0.128438828390298 0.0854628650706064 0.931930439805886 df.mm.trans1:exp8 0.0911782764828865 0.140697687137803 0.648043889972295 0.517278489846445 df.mm.trans2:exp8 0.0735699636139988 0.128438828390298 0.5728015782769 0.567057708023845 df.mm.trans1:probe2 0.105280221768673 0.0703488435689013 1.49654516588548 0.135194462638815 df.mm.trans1:probe3 0.0721205880446481 0.0703488435689013 1.02518512580824 0.305812315061842 df.mm.trans1:probe4 0.23538394045066 0.0703488435689013 3.34595323120158 0.000886887403030631 *** df.mm.trans1:probe5 0.414631076345386 0.0703488435689013 5.89392881688647 7.28062541324436e-09 *** df.mm.trans1:probe6 0.131185827506303 0.0703488435689013 1.86479010671748 0.0628446471352117 . df.mm.trans1:probe7 1.29686667385028 0.0703488435689013 18.4347973336633 2.76911571198952e-57 *** df.mm.trans1:probe8 1.14746290195001 0.0703488435689013 16.3110414292192 1.44351149059761e-47 *** df.mm.trans1:probe9 0.997307823118686 0.0703488435689013 14.1766057908528 3.91484884219298e-38 *** df.mm.trans1:probe10 1.03931015721033 0.0703488435689013 14.7736637090900 9.96535698812633e-41 *** df.mm.trans1:probe11 1.21666832012087 0.0703488435689013 17.2947877804023 4.88360591551856e-52 *** df.mm.trans1:probe12 1.01507006188181 0.0703488435689013 14.4290937901151 3.16559963779385e-39 *** df.mm.trans2:probe2 -0.108099217949116 0.0703488435689013 -1.53661684350563 0.125071712206416 df.mm.trans2:probe3 -0.150721854785929 0.0703488435689014 -2.14249228757127 0.0326758483170377 * df.mm.trans2:probe4 -0.101766569276644 0.0703488435689013 -1.44659903580322 0.148687355409433 df.mm.trans2:probe5 -0.217246735893496 0.0703488435689013 -3.08813514014228 0.00213546628251259 ** df.mm.trans2:probe6 -0.080094112018355 0.0703488435689013 -1.13852777039482 0.255490198050637 df.mm.trans3:probe2 -0.455311138437215 0.0703488435689013 -6.4721908042635 2.46953739057030e-10 *** df.mm.trans3:probe3 -0.274111489766686 0.0703488435689013 -3.89646049402667 0.000112039222373471 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.25094300395857 0.311999246810437 13.6248502117101 8.97789022133732e-36 *** df.mm.trans1 0.134558990024779 0.274926150098498 0.489436854139086 0.62476474303409 df.mm.trans2 0.0293043710212175 0.259938188820218 0.112735920621057 0.910288889582306 df.mm.exp2 0.312135715396384 0.358140218369210 0.871546113468333 0.383908712207169 df.mm.exp3 0.497201600918735 0.358140218369210 1.38828753492903 0.165718534105257 df.mm.exp4 0.176378865100795 0.358140218369209 0.492485501639375 0.622610122832381 df.mm.exp5 0.525937076596298 0.358140218369209 1.46852280090505 0.142642785813610 df.mm.exp6 0.751338576711257 0.358140218369210 2.09788942479701 0.0364575340995788 * df.mm.exp7 0.0304645207006722 0.358140218369210 0.0850631097490037 0.932248066714882 df.mm.exp8 0.356393072244576 0.358140218369210 0.995121614286747 0.320198023190233 df.mm.trans1:exp2 -0.223253443203076 0.331573412703145 -0.673315273932873 0.501083411920793 df.mm.trans2:exp2 0.173450895918738 0.302683729344137 0.573043342285281 0.56689414266018 df.mm.trans1:exp3 -0.177464405191244 0.331573412703145 -0.535219044688987 0.592755918738833 df.mm.trans2:exp3 -0.241291242966159 0.302683729344137 -0.797172822896674 0.425760159861115 df.mm.trans1:exp4 -0.0456666095515823 0.331573412703145 -0.137726994391035 0.890516188185377 df.mm.trans2:exp4 0.0466892862741823 0.302683729344137 0.154251060588390 0.877479141834746 df.mm.trans1:exp5 -0.405748190000323 0.331573412703145 -1.22370544336613 0.221687088312852 df.mm.trans2:exp5 -0.283702386523961 0.302683729344137 -0.937289847520693 0.349099189352233 df.mm.trans1:exp6 -0.57131836412251 0.331573412703145 -1.72305239875794 0.0855481725596795 . df.mm.trans2:exp6 -0.35677939235651 0.302683729344137 -1.17872008888482 0.239116363594628 df.mm.trans1:exp7 0.0221570935652012 0.331573412703145 0.0668240960110945 0.946750648458384 df.mm.trans2:exp7 0.161205517831921 0.302683729344138 0.532587325328737 0.59457533177239 df.mm.trans1:exp8 -0.223659911732617 0.331573412703145 -0.674541151865087 0.500304723750502 df.mm.trans2:exp8 -0.325754264885826 0.302683729344138 -1.07621993951138 0.282390578558024 df.mm.trans1:probe2 -0.055641004772812 0.165786706351572 -0.335618011825496 0.737311292180887 df.mm.trans1:probe3 -0.182051651455466 0.165786706351572 -1.09810765568502 0.272729441126291 df.mm.trans1:probe4 -0.0624347384611133 0.165786706351572 -0.376596772051869 0.706646183118657 df.mm.trans1:probe5 -0.311413404109185 0.165786706351572 -1.87839791840000 0.0609562503011432 . df.mm.trans1:probe6 -0.0672888695813564 0.165786706351572 -0.405876146900835 0.685021516207004 df.mm.trans1:probe7 -0.112390813632206 0.165786706351572 -0.677924159937565 0.498159152869275 df.mm.trans1:probe8 0.077150676660994 0.165786706351572 0.465361055532316 0.641892196264082 df.mm.trans1:probe9 -0.159122101413676 0.165786706351572 -0.959800124602492 0.337657846595122 df.mm.trans1:probe10 -0.20841437662101 0.165786706351572 -1.25712357285777 0.209344039559454 df.mm.trans1:probe11 -0.0454573793211776 0.165786706351572 -0.274191944104247 0.784059671771054 df.mm.trans1:probe12 -0.220417405189366 0.165786706351572 -1.3295240012908 0.184331242593480 df.mm.trans2:probe2 0.0465620897975689 0.165786706351572 0.280855388361645 0.77894704923832 df.mm.trans2:probe3 -0.0811537345331788 0.165786706351572 -0.489506887006257 0.624715211344574 df.mm.trans2:probe4 -0.150226868594927 0.165786706351572 -0.906145443750786 0.365331211253786 df.mm.trans2:probe5 -0.120573546127017 0.165786706351572 -0.727281148051308 0.467422118474464 df.mm.trans2:probe6 0.000505386527413783 0.165786706351572 0.00304841406488917 0.997569037066405 df.mm.trans3:probe2 -0.0160742151178834 0.165786706351572 -0.0969572016455647 0.92280242811945 df.mm.trans3:probe3 0.116208327693874 0.165786706351572 0.700950819587665 0.483686590196512