chr11.4122_chr11_95778415_95780734_-_2.R fitVsDatCorrelation=0.91773117205437 cont.fitVsDatCorrelation=0.263526419918297 fstatistic=6814.70098545234,55,761 cont.fstatistic=1143.89880952764,55,761 residuals=-0.820540252874027,-0.125878050323381,0.00098422438774584,0.133824156111102,0.789553528346978 cont.residuals=-1.25253155028964,-0.43003755558139,-0.0477055392281475,0.382363038556006,1.40773631611700 predictedValues: Include Exclude Both chr11.4122_chr11_95778415_95780734_-_2.R.tl.Lung 85.2673554709658 243.81363190503 73.6127966895614 chr11.4122_chr11_95778415_95780734_-_2.R.tl.cerebhem 129.568320037043 155.158252390700 106.256553300913 chr11.4122_chr11_95778415_95780734_-_2.R.tl.cortex 95.3884444720143 175.953313241468 83.8954969431673 chr11.4122_chr11_95778415_95780734_-_2.R.tl.heart 178.323383640891 236.662624087467 172.280206044246 chr11.4122_chr11_95778415_95780734_-_2.R.tl.kidney 118.460752031496 243.925522286332 101.798570706134 chr11.4122_chr11_95778415_95780734_-_2.R.tl.liver 94.069962828472 217.000723273631 77.4416910957268 chr11.4122_chr11_95778415_95780734_-_2.R.tl.stomach 87.4343235263221 238.23690544772 73.582837628859 chr11.4122_chr11_95778415_95780734_-_2.R.tl.testicle 84.2030357493596 218.526779392720 71.7536873602719 diffExp=-158.546276434064,-25.5899323536578,-80.5648687694533,-58.3392404465764,-125.464770254837,-122.930760445159,-150.802581921398,-134.323743643361 diffExpScore=0.998833903791462 diffExp1.5=-1,0,-1,0,-1,-1,-1,-1 diffExp1.5Score=0.857142857142857 diffExp1.4=-1,0,-1,0,-1,-1,-1,-1 diffExp1.4Score=0.857142857142857 diffExp1.3=-1,0,-1,-1,-1,-1,-1,-1 diffExp1.3Score=0.875 diffExp1.2=-1,0,-1,-1,-1,-1,-1,-1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 130.703568583266 132.699060058623 113.898661623908 cerebhem 122.590116922657 116.280266572631 141.467036232274 cortex 123.650288844642 132.909282120147 125.586979450465 heart 111.087533040284 115.630605833322 99.160818509585 kidney 133.295049090363 156.396414889209 118.318699424614 liver 120.623436649878 114.923886549324 127.850253552644 stomach 120.684209339615 90.1211123928736 127.972243602832 testicle 115.118634109444 100.913025079781 113.571934603237 cont.diffExp=-1.99549147535694,6.30985035002595,-9.2589932755053,-4.54307279303788,-23.1013657988462,5.69955010055419,30.5630969467411,14.2056090296625 cont.diffExpScore=5.06785856902953 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=0,0,0,0,0,0,1,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,0,0,0,0,0,1,0 cont.diffExp1.2Score=0.5 tran.correlation=-0.0299738216884815 cont.tran.correlation=0.725072500201986 tran.covariance=-0.00465437762165592 cont.tran.covariance=0.0069656659547895 tran.mean=162.624583111352 cont.tran.mean=121.101655629754 weightedLogRatios: wLogRatio Lung -5.2226973538115 cerebhem -0.892954359993866 cortex -2.97809264218892 heart -1.50720483632184 kidney -3.70943590118192 liver -4.14752143249021 stomach -4.9838986413984 testicle -4.68262351835058 cont.weightedLogRatios: wLogRatio Lung -0.0739491345687943 cerebhem 0.252717868134896 cortex -0.350473174737463 heart -0.189603223603808 kidney -0.794745528998547 liver 0.230810945447308 stomach 1.35707855351362 testicle 0.616390239822914 varWeightedLogRatios=2.58139409293275 cont.varWeightedLogRatios=0.428180219905527 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.27853615597726 0.107333715346957 49.1787332518433 1.72653071209757e-238 *** df.mm.trans1 -1.13129472821027 0.0934220078630716 -12.1095098905218 5.42893831910079e-31 *** df.mm.trans2 0.390046030392812 0.0835591840705392 4.66790137710705 3.59573672246211e-06 *** df.mm.exp2 -0.400579524687248 0.109404653146284 -3.66144869680851 0.000268141821433273 *** df.mm.exp3 -0.344772731925848 0.109404653146284 -3.15135345719578 0.00168882330295316 ** df.mm.exp4 -0.142264922038515 0.109404653146284 -1.30035531348282 0.193872885534067 df.mm.exp5 0.00507164782055922 0.109404653146284 0.0463567835069864 0.963038043160497 df.mm.exp6 -0.0689627325699287 0.109404653146284 -0.63034551627086 0.528657781012402 df.mm.exp7 0.00236475896420432 0.109404653146284 0.0216147933035574 0.982760898937902 df.mm.exp8 -0.0964766330686858 0.109404653146284 -0.881832996076389 0.378145566190573 df.mm.trans1:exp2 0.818996155884951 0.101850189229333 8.0411844306037 3.40083381454936e-15 *** df.mm.trans2:exp2 -0.0513790258551726 0.0798978618989978 -0.64305883329047 0.520379635100384 df.mm.trans1:exp3 0.456938497235367 0.101850189229333 4.48637848091272 8.36314629591678e-06 *** df.mm.trans2:exp3 0.0185872963227054 0.0798978618989977 0.23263821935814 0.816104898539424 df.mm.trans1:exp4 0.880071907361535 0.101850189229333 8.64084705213365 3.26362586983003e-17 *** df.mm.trans2:exp4 0.112496392160665 0.0798978618989978 1.40800253582351 0.159538686391459 df.mm.trans1:exp5 0.323718372727871 0.101850189229333 3.17837772494428 0.00154091586808070 ** df.mm.trans2:exp5 -0.00461283543158557 0.0798978618989978 -0.0577341536049719 0.953975544184758 df.mm.trans1:exp6 0.167209844725676 0.101850189229333 1.64172345668573 0.101060486955911 df.mm.trans2:exp6 -0.0475407106156125 0.0798978618989978 -0.595018558515504 0.552007947236665 df.mm.trans1:exp7 0.0227314856158420 0.101850189229333 0.223185502038276 0.823451028928991 df.mm.trans2:exp7 -0.0255033091136484 0.0798978618989977 -0.319198893530945 0.749663293544035 df.mm.trans1:exp8 0.0839159290169282 0.101850189229333 0.823915298065647 0.410245827733677 df.mm.trans2:exp8 -0.0130189295344543 0.0798978618989978 -0.162944654900929 0.87060527024637 df.mm.trans1:probe2 0.309787409660887 0.0647246656655757 4.78623421960215 2.04188726794278e-06 *** df.mm.trans1:probe3 0.360348626145561 0.0647246656655757 5.56740807295069 3.58568665451661e-08 *** df.mm.trans1:probe4 -0.129719851590759 0.0647246656655757 -2.00417955437584 0.0454047502939358 * df.mm.trans1:probe5 -0.453749567465414 0.0647246656655757 -7.01045826655762 5.24391731833455e-12 *** df.mm.trans1:probe6 -0.072385752803461 0.0647246656655757 -1.11836425973166 0.263764357254152 df.mm.trans1:probe7 -0.131139323799852 0.0647246656655757 -2.02611048587617 0.0431018449512804 * df.mm.trans1:probe8 -0.0781459990166078 0.0647246656655757 -1.20736041218627 0.227668495319944 df.mm.trans1:probe9 -0.107320338650347 0.0647246656655757 -1.65810572440586 0.097708232581603 . df.mm.trans1:probe10 0.448540588294709 0.0647246656655757 6.92997922325721 8.9780473559765e-12 *** df.mm.trans1:probe11 0.588415296192894 0.0647246656655757 9.0910519218927 8.37771379765898e-19 *** df.mm.trans1:probe12 0.466813725059601 0.0647246656655757 7.21230029169358 1.33050581976199e-12 *** df.mm.trans1:probe13 0.434333542761997 0.0647246656655757 6.71047951033296 3.78884742614529e-11 *** df.mm.trans1:probe14 0.666135438292708 0.0647246656655757 10.2918328189526 2.39387338052662e-23 *** df.mm.trans1:probe15 0.685841815205658 0.0647246656655757 10.5962975343792 1.44681869081721e-24 *** df.mm.trans1:probe16 0.832996901660115 0.0647246656655757 12.8698525221298 1.95365591102842e-34 *** df.mm.trans1:probe17 0.801013984255355 0.0647246656655757 12.3757145134452 3.5032949214334e-32 *** df.mm.trans1:probe18 0.763700934509139 0.0647246656655757 11.7992256376431 1.25964954876978e-29 *** df.mm.trans1:probe19 1.01148552735239 0.0647246656655757 15.6275125866020 5.93246076333988e-48 *** df.mm.trans1:probe20 1.11534805548048 0.0647246656655757 17.2321949292616 1.96631371430111e-56 *** df.mm.trans1:probe21 0.84710601403353 0.0647246656655757 13.0878391618185 1.90083564826982e-35 *** df.mm.trans2:probe2 -0.721653126630638 0.0647246656655757 -11.1495844622718 7.59359864715541e-27 *** df.mm.trans2:probe3 0.211383423262178 0.0647246656655757 3.26588667687168 0.00114008172016281 ** df.mm.trans2:probe4 -0.723552892112062 0.0647246656655757 -11.1789359538846 5.71741371169329e-27 *** df.mm.trans2:probe5 -0.208959489527469 0.0647246656655757 -3.22843675403651 0.00129806109958456 ** df.mm.trans2:probe6 -0.795532650680417 0.0647246656655757 -12.2910275781235 8.41333564577818e-32 *** df.mm.trans3:probe2 -0.332312041720483 0.0647246656655757 -5.1342411475325 3.60094056161312e-07 *** df.mm.trans3:probe3 -0.255469333569722 0.0647246656655757 -3.9470166580651 8.64601293147304e-05 *** df.mm.trans3:probe4 0.0596400483849565 0.0647246656655757 0.92144235542458 0.357111541489355 df.mm.trans3:probe5 -0.572333917105792 0.0647246656655757 -8.84259364216681 6.43890463114688e-18 *** df.mm.trans3:probe6 -0.348178540064338 0.0647246656655757 -5.37937950677618 9.9561368368141e-08 *** df.mm.trans3:probe7 -0.220626272239640 0.0647246656655757 -3.40868925271222 0.000687112198467865 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.79953562150029 0.260672605797682 18.412121238491 6.783328293299e-63 *** df.mm.trans1 0.149041271092759 0.226886380945621 0.656898269837008 0.51144493286289 df.mm.trans2 0.0956097140077484 0.202933348385328 0.471138503200594 0.63767685729541 df.mm.exp2 -0.412923616434517 0.265702122859032 -1.55408474720239 0.120579959345686 df.mm.exp3 -0.15158110779384 0.265702122859032 -0.570492648544857 0.568512007946104 df.mm.exp4 -0.161730469586039 0.265702122859032 -0.60869091991352 0.542910970444382 df.mm.exp5 0.145870502156441 0.265702122859032 0.549000138150317 0.583166396610974 df.mm.exp6 -0.339622694683155 0.265702122859032 -1.27820843517815 0.201565662437420 df.mm.exp7 -0.583188302793429 0.265702122859032 -2.19489515747241 0.0284725053514726 * df.mm.exp8 -0.397920877660059 0.265702122859032 -1.49762024246670 0.134646592409393 df.mm.trans1:exp2 0.348838100432452 0.247355214916167 1.41027186570810 0.158868016881692 df.mm.trans2:exp2 0.280843126521326 0.194041395022534 1.44733615468344 0.148214602160164 df.mm.trans1:exp3 0.0961065138658641 0.247355214916167 0.388536436955397 0.697727769145943 df.mm.trans2:exp3 0.15316405585711 0.194041395022534 0.789337016667618 0.430160911110474 df.mm.trans1:exp4 -0.000882977802106843 0.247355214916167 -0.00356967530442445 0.997152752760621 df.mm.trans2:exp4 0.0240472890186291 0.194041395022534 0.123928654583402 0.901404489724373 df.mm.trans1:exp5 -0.126237340647534 0.247355214916167 -0.510348410039863 0.609955386787375 df.mm.trans2:exp5 0.0184395448812481 0.194041395022534 0.0950289234887572 0.924316869527637 df.mm.trans1:exp6 0.259364369964346 0.247355214916167 1.04855023999494 0.294718057861249 df.mm.trans2:exp6 0.195808889722609 0.194041395022534 1.00910885380859 0.31324317332016 df.mm.trans1:exp7 0.503433672773331 0.247355214916167 2.0352660563229 0.0421701313330505 * df.mm.trans2:exp7 0.196258903636636 0.194041395022534 1.01142801830426 0.312133087043259 df.mm.trans1:exp8 0.270952151361938 0.247355214916167 1.09539696364909 0.273689312871383 df.mm.trans2:exp8 0.12409602757767 0.194041395022534 0.63953378382617 0.522668209806232 df.mm.trans1:probe2 -0.194356905109889 0.157191495737297 -1.23643396990575 0.216678760354379 df.mm.trans1:probe3 -0.186589335919480 0.157191495737297 -1.18701927890115 0.235590419935938 df.mm.trans1:probe4 -0.0341318180936315 0.157191495737297 -0.217135271431437 0.828161126840718 df.mm.trans1:probe5 -0.0690365343553191 0.157191495737297 -0.439187463873332 0.660650381754245 df.mm.trans1:probe6 0.0266239539413282 0.157191495737297 0.16937273747826 0.86554847715818 df.mm.trans1:probe7 -0.254225137732304 0.157191495737297 -1.61729574834743 0.106228859325014 df.mm.trans1:probe8 0.0745054168555779 0.157191495737297 0.473978674902958 0.635651070333066 df.mm.trans1:probe9 -0.192553449273612 0.157191495737297 -1.22496098386527 0.220968939698999 df.mm.trans1:probe10 -0.234598248061442 0.157191495737297 -1.49243600591160 0.135999317492980 df.mm.trans1:probe11 -0.063529754635465 0.157191495737297 -0.404155163340629 0.686212175665318 df.mm.trans1:probe12 -0.153388577308740 0.157191495737297 -0.975807098146626 0.329470147996361 df.mm.trans1:probe13 -0.117937778787740 0.157191495737297 -0.75028091204655 0.453317438833508 df.mm.trans1:probe14 -0.0497026278213125 0.157191495737297 -0.316191582681909 0.751943800965121 df.mm.trans1:probe15 -0.225178099259691 0.157191495737297 -1.43250815321469 0.152409079436418 df.mm.trans1:probe16 -0.0692311158964384 0.157191495737297 -0.440425326902796 0.659754156059263 df.mm.trans1:probe17 0.0870592618101502 0.157191495737297 0.55384205997789 0.579849634042226 df.mm.trans1:probe18 -0.0581947576097004 0.157191495737297 -0.370215687157511 0.711324801929876 df.mm.trans1:probe19 -0.0531892837137014 0.157191495737297 -0.338372527497244 0.735175805810775 df.mm.trans1:probe20 -0.272346907327662 0.157191495737297 -1.73258041759979 0.0835754147291365 . df.mm.trans1:probe21 -0.0780574257096551 0.157191495737297 -0.496575373518342 0.61963192960375 df.mm.trans2:probe2 0.0539622350456594 0.157191495737297 0.343289786718759 0.73147527703062 df.mm.trans2:probe3 -0.0628771251404963 0.157191495737297 -0.400003351616289 0.689266299762013 df.mm.trans2:probe4 -0.096199189251719 0.157191495737297 -0.611987237607878 0.54072899675916 df.mm.trans2:probe5 -0.0304080319722796 0.157191495737297 -0.193445782990057 0.846661481980906 df.mm.trans2:probe6 0.043722905112149 0.157191495737297 0.278150576194147 0.78097232777278 df.mm.trans3:probe2 -0.370648290012961 0.157191495737297 -2.35794111045549 0.0186287117839811 * df.mm.trans3:probe3 -0.462844399749718 0.157191495737297 -2.94446208796968 0.00333371870404359 ** df.mm.trans3:probe4 -0.151943811181944 0.157191495737297 -0.966615976705747 0.334043126111151 df.mm.trans3:probe5 -0.358734805281345 0.157191495737297 -2.28215148407821 0.0227555919982885 * df.mm.trans3:probe6 -0.389890381817551 0.157191495737297 -2.48035289688411 0.0133404430458233 * df.mm.trans3:probe7 -0.42808071861337 0.157191495737297 -2.72330711407436 0.00661128028668252 **