chr6.19424_chr6_6626319_6628852_-_0.R fitVsDatCorrelation=0.898855643773538 cont.fitVsDatCorrelation=0.347849217046831 fstatistic=5401.49808150562,40,416 cont.fstatistic=1172.08021447694,40,416 residuals=-0.8928780553626,-0.117139957519164,0.000197836583604415,0.110091782049293,0.612465869680906 cont.residuals=-0.724609801413292,-0.287861455570594,-0.083967500412345,0.182218374791764,1.49821683832091 predictedValues: Include Exclude Both chr6.19424_chr6_6626319_6628852_-_0.R.tl.Lung 83.9149055314785 60.6553669349639 68.8433528140739 chr6.19424_chr6_6626319_6628852_-_0.R.tl.cerebhem 67.4332044962548 60.4228635800636 64.4932777223003 chr6.19424_chr6_6626319_6628852_-_0.R.tl.cortex 116.444501526565 70.0884151916435 65.0967768703438 chr6.19424_chr6_6626319_6628852_-_0.R.tl.heart 104.887001594262 72.6179529012615 67.3280181001741 chr6.19424_chr6_6626319_6628852_-_0.R.tl.kidney 79.7242124309738 68.268592565983 77.1652684050316 chr6.19424_chr6_6626319_6628852_-_0.R.tl.liver 88.7305616453866 72.9189275080433 75.5995037572563 chr6.19424_chr6_6626319_6628852_-_0.R.tl.stomach 149.966749509446 84.7966852178981 65.4104576658247 chr6.19424_chr6_6626319_6628852_-_0.R.tl.testicle 98.2425047754332 72.221262057077 66.2302994066317 diffExp=23.2595385965146,7.01034091619122,46.3560863349214,32.269048693,11.4556198649908,15.8116341373433,65.1700642915479,26.0212427183561 diffExpScore=0.995620826178969 diffExp1.5=0,0,1,0,0,0,1,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,0,1,1,0,0,1,0 diffExp1.4Score=0.75 diffExp1.3=1,0,1,1,0,0,1,1 diffExp1.3Score=0.833333333333333 diffExp1.2=1,0,1,1,0,1,1,1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 73.9570816689605 100.809376219669 84.4162841073113 cerebhem 90.3861203747281 84.74440540171 88.828068880255 cortex 76.6360157635843 74.4005914261625 74.135280319394 heart 102.0169098294 81.0318817199582 67.5767934858964 kidney 76.1407980881628 76.488942607225 90.2828961990816 liver 66.9196877464426 89.6409585529343 96.208335933484 stomach 74.214633102826 76.0840279844643 80.2212193894762 testicle 69.9931481634352 63.3865564839545 77.2322408268288 cont.diffExp=-26.8522945507087,5.64171497301817,2.23542433742179,20.9850281094417,-0.348144519062203,-22.7212708064917,-1.86939488163827,6.60659167948067 cont.diffExpScore=5.03741615467941 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=-1,0,0,0,0,-1,0,0 cont.diffExp1.3Score=0.666666666666667 cont.diffExp1.2=-1,0,0,1,0,-1,0,0 cont.diffExp1.2Score=1.5 tran.correlation=0.871023535164098 cont.tran.correlation=0.0541545106843405 tran.covariance=0.0232046795585895 cont.tran.covariance=0.00174940507042302 tran.mean=84.4583567166708 cont.tran.mean=79.8031959458511 weightedLogRatios: wLogRatio Lung 1.38521158198569 cerebhem 0.456231741419384 cortex 2.28627819775975 heart 1.64314117764989 kidney 0.667188049733267 liver 0.86106915966051 stomach 2.69418353693542 testicle 1.36423445228683 cont.weightedLogRatios: wLogRatio Lung -1.3809604869362 cerebhem 0.288216135610757 cortex 0.128012334158070 heart 1.03863236689110 kidney -0.0197754667541469 liver -1.27148672489891 stomach -0.107453790201777 testicle 0.416294804424196 varWeightedLogRatios=0.6051530903521 cont.varWeightedLogRatios=0.68342939123679 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.97347512830917 0.104263559777410 38.1099123873389 8.99253698269148e-138 *** df.mm.trans1 0.377745992731400 0.0845689141962184 4.46672392949195 1.02480041238132e-05 *** df.mm.trans2 0.0481135591197222 0.0845689141962184 0.568927242084346 0.569712537410416 df.mm.exp2 -0.157233585821575 0.114358044241128 -1.37492370444918 0.169895161259212 df.mm.exp3 0.528119556275522 0.114358044241128 4.61812336666028 5.16935431277247e-06 *** df.mm.exp4 0.425341602125508 0.114358044241128 3.71938506773219 0.000227093316247075 *** df.mm.exp5 -0.0471040180189244 0.114358044241128 -0.411899471799325 0.680625259490729 df.mm.exp6 0.146325200321333 0.114358044241128 1.27953570115978 0.201421642755698 df.mm.exp7 0.966810200243818 0.114358044241128 8.45423867345323 4.79362945689773e-16 *** df.mm.exp8 0.370857695102288 0.114358044241128 3.24295240936722 0.00127833190029035 ** df.mm.trans1:exp2 -0.0614321252542037 0.09219840282633 -0.666303573283375 0.505586415147759 df.mm.trans2:exp2 0.153393033482917 0.0921984028263301 1.66372766534640 0.0969199381395652 . df.mm.trans1:exp3 -0.200508034516910 0.09219840282633 -2.17474520566911 0.0302119734952705 * df.mm.trans2:exp3 -0.383570158813436 0.09219840282633 -4.16026901828169 3.86374895865142e-05 *** df.mm.trans1:exp4 -0.202261262748243 0.09219840282633 -2.19376102565717 0.0288051590936451 * df.mm.trans2:exp4 -0.245337547469830 0.09219840282633 -2.66097394259595 0.00809301831704013 ** df.mm.trans1:exp5 -0.00412590369924795 0.09219840282633 -0.0447502730282619 0.964327834360044 df.mm.trans2:exp5 0.165345711787514 0.09219840282633 1.79336850443026 0.0736402526234719 . df.mm.trans1:exp6 -0.0905240756640439 0.09219840282633 -0.981839954804423 0.326749365701491 df.mm.trans2:exp6 0.0378149198457205 0.0921984028263301 0.410147233428227 0.681909086742376 df.mm.trans1:exp7 -0.386199856652087 0.09219840282633 -4.18879118090098 3.42609620753923e-05 *** df.mm.trans2:exp7 -0.631761869368036 0.0921984028263301 -6.85219971280909 2.630955584662e-11 *** df.mm.trans1:exp8 -0.213221990530970 0.09219840282633 -2.31264299591617 0.0212295101996093 * df.mm.trans2:exp8 -0.196331325978 0.0921984028263301 -2.12944389446551 0.0338041373560201 * df.mm.trans1:probe2 -0.225252173702237 0.0585910624515133 -3.84448010118681 0.000139704119673900 *** df.mm.trans1:probe3 -0.209797499019621 0.0585910624515133 -3.58070822138168 0.00038312953192714 *** df.mm.trans1:probe4 0.228161439998603 0.0585910624515133 3.89413385680480 0.00011477855954167 *** df.mm.trans1:probe5 0.522816546771902 0.0585910624515133 8.92314501387572 1.45854419406171e-17 *** df.mm.trans1:probe6 0.70563944036008 0.0585910624515133 12.0434655190632 7.29173912998514e-29 *** df.mm.trans2:probe2 -0.0907181965336162 0.0585910624515133 -1.54832823877685 0.122303678880776 df.mm.trans2:probe3 0.0214440838873628 0.0585910624515133 0.365995818988754 0.71455424328604 df.mm.trans2:probe4 -0.245331681699239 0.0585910624515133 -4.18718609006726 3.44941537823106e-05 *** df.mm.trans2:probe5 0.372186984073445 0.0585910624515133 6.35228255813668 5.56995449398324e-10 *** df.mm.trans2:probe6 1.02947145640076 0.0585910624515133 17.5704521018491 4.28498405286210e-52 *** df.mm.trans3:probe2 0.00780383831204577 0.0585910624515133 0.133191616357935 0.894106245385562 df.mm.trans3:probe3 -0.231916896754632 0.0585910624515133 -3.95822992536709 8.87868101228233e-05 *** df.mm.trans3:probe4 -0.411327540620470 0.0585910624515133 -7.02031203071051 9.06066729943479e-12 *** df.mm.trans3:probe5 -0.328173361987515 0.0585910624515133 -5.60108228552935 3.87831638505763e-08 *** df.mm.trans3:probe6 -0.143692114869549 0.0585910624515133 -2.45245791520611 0.0145982234571807 * df.mm.trans3:probe7 -0.0652009629775666 0.0585910624515133 -1.11281414348005 0.266430882767045 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.54914366302145 0.223054203393583 20.3947901174245 1.35860504080418e-64 *** df.mm.trans1 -0.267320931735701 0.180920849318486 -1.47755735584194 0.140282956339972 df.mm.trans2 0.040984056117008 0.180920849318486 0.226530310195821 0.820900254972764 df.mm.exp2 -0.0239282342085937 0.244649640912985 -0.0978061284672162 0.92213334715733 df.mm.exp3 -0.138316493870632 0.244649640912985 -0.56536561163328 0.572129892283877 df.mm.exp4 0.325760634197769 0.244649640912985 1.33153939234120 0.183740746661004 df.mm.exp5 -0.314173603783186 0.244649640912985 -1.28417766161745 0.199794518757855 df.mm.exp6 -0.348166447978003 0.244649640912985 -1.42312266095594 0.155450092664372 df.mm.exp7 -0.226944351752387 0.244649640912985 -0.927630021877304 0.354137402975000 df.mm.exp8 -0.430123841359007 0.244649640912985 -1.75812169498336 0.0794621597740804 . df.mm.trans1:exp2 0.224534006635416 0.197242846306917 1.13836324530641 0.255623986030951 df.mm.trans2:exp2 -0.149663404032605 0.197242846306917 -0.758777349013325 0.448415447071686 df.mm.trans1:exp3 0.17389869229289 0.197242846306917 0.881647651861083 0.378476493104491 df.mm.trans2:exp3 -0.165450984409172 0.197242846306917 -0.838818682182898 0.402052802185008 df.mm.trans1:exp4 -0.00410699951845883 0.197242846306917 -0.0208220454904012 0.983397595072667 df.mm.trans2:exp4 -0.544149324848739 0.197242846306917 -2.75877850597442 0.00605779704126637 ** df.mm.trans1:exp5 0.343272889028253 0.197242846306917 1.74035659825203 0.0825358731803702 . df.mm.trans2:exp5 0.0380884237229495 0.197242846306917 0.193104208523145 0.846971599237835 df.mm.trans1:exp6 0.248174710507741 0.197242846306917 1.25821906930694 0.209018270548914 df.mm.trans2:exp6 0.230747420851529 0.197242846306917 1.16986458658418 0.242725269182798 df.mm.trans1:exp7 0.230420746604734 0.197242846306917 1.16820838331541 0.243391774233143 df.mm.trans2:exp7 -0.0544486567106105 0.197242846306917 -0.276048828791927 0.78264764489837 df.mm.trans1:exp8 0.375036247732265 0.197242846306917 1.90139340794492 0.0579411850297687 . df.mm.trans2:exp8 -0.0338557318855394 0.197242846306917 -0.171644916504899 0.863800156727035 df.mm.trans1:probe2 -0.0260197200559562 0.125345641267253 -0.207583764324752 0.83565556288644 df.mm.trans1:probe3 0.136248721076201 0.125345641267253 1.08698411607071 0.27767323586339 df.mm.trans1:probe4 0.246657184298596 0.125345641267253 1.96781620649011 0.0497530240156248 * df.mm.trans1:probe5 -0.0537063410496242 0.125345641267253 -0.42846596424614 0.668533669080273 df.mm.trans1:probe6 -0.0215710334096481 0.125345641267253 -0.172092409369512 0.863448567377237 df.mm.trans2:probe2 0.131651018923692 0.125345641267253 1.05030392435422 0.294188158680350 df.mm.trans2:probe3 0.101039529917298 0.125345641267253 0.806087303042866 0.420653060747657 df.mm.trans2:probe4 -0.040792986586629 0.125345641267253 -0.32544399768679 0.745008683466551 df.mm.trans2:probe5 0.057436773003918 0.125345641267253 0.458227126394093 0.647028545168817 df.mm.trans2:probe6 0.0510131176690169 0.125345641267253 0.406979589822757 0.68423229576055 df.mm.trans3:probe2 0.0480690166608544 0.125345641267253 0.383491728749987 0.701551108333867 df.mm.trans3:probe3 0.0237882721933074 0.125345641267253 0.189781407257615 0.849572992074645 df.mm.trans3:probe4 0.243618010395397 0.125345641267253 1.94356985956913 0.0526213719962282 . df.mm.trans3:probe5 0.0367559518304717 0.125345641267253 0.293236776794683 0.769487399054775 df.mm.trans3:probe6 0.256993994076664 0.125345641267253 2.05028265425457 0.0409630647353889 * df.mm.trans3:probe7 0.181449501584761 0.125345641267253 1.44759322901295 0.148484021522348