chr8.22921_chr8_69777801_69779296_+_2.R fitVsDatCorrelation=0.992376914980066 cont.fitVsDatCorrelation=0.255685161835427 fstatistic=11071.8872623004,48,600 cont.fstatistic=167.626046052506,48,600 residuals=-0.597250541799556,-0.103596788265423,-0.00285689136984347,0.104778529496916,0.687399293018024 cont.residuals=-1.75122056723447,-0.887003266599672,-0.548754070618439,0.315889334068256,3.55866134231119 predictedValues: Include Exclude Both chr8.22921_chr8_69777801_69779296_+_2.R.tl.Lung 176.535444806551 50.5429007327391 65.7006954371908 chr8.22921_chr8_69777801_69779296_+_2.R.tl.cerebhem 169.886496807533 57.7406285471032 68.9912843475939 chr8.22921_chr8_69777801_69779296_+_2.R.tl.cortex 153.800609747311 51.8418363885222 66.0877462235444 chr8.22921_chr8_69777801_69779296_+_2.R.tl.heart 147.101379479190 52.0797271834787 67.4952000699011 chr8.22921_chr8_69777801_69779296_+_2.R.tl.kidney 178.044576653447 51.3011912797064 64.7402686768562 chr8.22921_chr8_69777801_69779296_+_2.R.tl.liver 168.375503756367 51.1803304762729 68.6500747373349 chr8.22921_chr8_69777801_69779296_+_2.R.tl.stomach 158.973439800090 54.1091336029152 65.6675039749476 chr8.22921_chr8_69777801_69779296_+_2.R.tl.testicle 193.758222071566 51.8205889186556 64.2828860747347 diffExp=125.992544073812,112.145868260429,101.958773358789,95.0216522957115,126.743385373741,117.195173280095,104.864306197175,141.937633152911 diffExpScore=0.998921087633078 diffExp1.5=1,1,1,1,1,1,1,1 diffExp1.5Score=0.888888888888889 diffExp1.4=1,1,1,1,1,1,1,1 diffExp1.4Score=0.888888888888889 diffExp1.3=1,1,1,1,1,1,1,1 diffExp1.3Score=0.888888888888889 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 135.434967882821 122.525296049888 63.9143483398203 cerebhem 147.098345310387 151.649588689775 60.7012537763042 cortex 96.012510532858 116.786013720149 115.597310021783 heart 113.031493956194 135.191958393277 156.427887370820 kidney 112.617421869804 117.323953040013 115.608965395051 liver 134.915263196344 160.050920055227 154.803373798005 stomach 115.592753742466 66.2458890076927 88.1737003725581 testicle 141.487069567110 106.189697763982 83.4253266270873 cont.diffExp=12.9096718329334,-4.55124337938761,-20.7735031872914,-22.1604644370828,-4.70653117020956,-25.1356568588828,49.3468647347737,35.2973718031274 cont.diffExpScore=8.23881612464538 cont.diffExp1.5=0,0,0,0,0,0,1,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=0,0,0,0,0,0,1,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,0,0,0,0,1,1 cont.diffExp1.3Score=0.666666666666667 cont.diffExp1.2=0,0,-1,0,0,0,1,1 cont.diffExp1.2Score=1.5 tran.correlation=-0.137199606725978 cont.tran.correlation=0.376025257963495 tran.covariance=-0.000507706602370334 cont.tran.covariance=0.0127519293679869 tran.mean=110.443250640716 cont.tran.mean=123.259571423624 weightedLogRatios: wLogRatio Lung 5.68839510531236 cerebhem 4.95937281356231 cortex 4.88478916656805 heart 4.64343133403157 kidney 5.67394225781487 liver 5.39543530647428 stomach 4.8819956403166 testicle 6.0760830299287 cont.weightedLogRatios: wLogRatio Lung 0.486686187376027 cerebhem -0.15254880958546 cortex -0.913202257905483 heart -0.862416052018648 kidney -0.194250419254223 liver -0.852528983499845 stomach 2.48940775821333 testicle 1.38001175085974 varWeightedLogRatios=0.255929151536617 cont.varWeightedLogRatios=1.49507237487264 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.86714749626755 0.09322460311808 52.2088304318414 2.71489164554479e-225 *** df.mm.trans1 -0.0541419919508613 0.0832985224293803 -0.64997541819259 0.515956871522722 df.mm.trans2 -0.906221058144956 0.077184334407047 -11.7409972516679 8.48493673267634e-29 *** df.mm.exp2 0.0458767641272505 0.105896033167799 0.43322457654817 0.665007323541308 df.mm.exp3 -0.118363511360424 0.105896033167799 -1.11773319377195 0.264128303299481 df.mm.exp4 -0.179393381678171 0.105896033167799 -1.69405195182252 0.0907743800684286 . df.mm.exp5 0.0381298634567913 0.105896033167799 0.360068855425134 0.718922350797732 df.mm.exp6 -0.0787049677139386 0.105896033167799 -0.743228668341389 0.457634159235944 df.mm.exp7 -0.0360987094132959 0.105896033167799 -0.340888212083405 0.733307069875236 df.mm.exp8 0.139870543976779 0.105896033167799 1.32082892807840 0.187061949512692 df.mm.trans1:exp2 -0.0842678925484711 0.100461797996094 -0.838805339236987 0.401912606219642 df.mm.trans2:exp2 0.0872618007617326 0.0885989779200238 0.98490753291197 0.32506648201803 df.mm.trans1:exp3 -0.0195011436743469 0.100461797996094 -0.194115017482617 0.846151524677758 df.mm.trans2:exp3 0.143738491834260 0.0885989779200238 1.62234932285573 0.105253867735705 df.mm.trans1:exp4 -0.00300628957105192 0.100461797996094 -0.0299247040269855 0.97613705460189 df.mm.trans2:exp4 0.209346646048227 0.0885989779200237 2.36285621982230 0.0184527477116238 * df.mm.trans1:exp5 -0.029617590525223 0.100461797996094 -0.294814457993023 0.768237598372213 df.mm.trans2:exp5 -0.0232383848271244 0.0885989779200237 -0.262287278845374 0.793189994479039 df.mm.trans1:exp6 0.031379917666169 0.100461797996094 0.312356719589959 0.754877962894403 df.mm.trans2:exp6 0.0912377604576874 0.0885989779200237 1.02978344219778 0.303526608632744 df.mm.trans1:exp7 -0.0686858242478876 0.100461797996094 -0.683700925306535 0.49442798660208 df.mm.trans2:exp7 0.104279214061798 0.0885989779200237 1.17697987617790 0.239670233140458 df.mm.trans1:exp8 -0.0467811167906616 0.100461797996094 -0.465660755867425 0.641627327712188 df.mm.trans2:exp8 -0.114905499313361 0.0885989779200237 -1.29691675921007 0.195158332502071 df.mm.trans1:probe2 -0.458120846316659 0.0502308989980469 -9.12029956570102 1.12135412596178e-18 *** df.mm.trans1:probe3 -0.666772093578468 0.0502308989980469 -13.2741421491260 1.92773353719499e-35 *** df.mm.trans1:probe4 -0.294357777738253 0.0502308989980469 -5.86009375921579 7.63379468953095e-09 *** df.mm.trans1:probe5 -0.670101907568813 0.0502308989980469 -13.3404323023338 9.71840706356492e-36 *** df.mm.trans1:probe6 0.0265161613312382 0.0502308989980469 0.527885462138936 0.597773999093912 df.mm.trans1:probe7 2.52602260830586 0.0502308989980469 50.2882221638931 2.43440222941813e-217 *** df.mm.trans1:probe8 2.45218190565261 0.0502308989980469 48.8181966591511 3.99221310003048e-211 *** df.mm.trans1:probe9 2.77319437532347 0.0502308989980469 55.208933756716 2.39632517216015e-237 *** df.mm.trans1:probe10 2.03027590478718 0.0502308989980469 40.4188645890277 2.08528300345576e-173 *** df.mm.trans1:probe11 2.54427569975273 0.0502308989980469 50.6516058940465 7.36754199805575e-219 *** df.mm.trans1:probe12 2.6431080426814 0.0502308989980469 52.6191665967231 5.73888356556131e-227 *** df.mm.trans1:probe13 -0.918002070013378 0.0502308989980469 -18.2756448386295 1.19157721200498e-59 *** df.mm.trans1:probe14 -0.879507838179826 0.0502308989980469 -17.5092991708953 9.35167673985059e-56 *** df.mm.trans1:probe15 -0.966560730683977 0.0502308989980469 -19.2423538093865 1.2547243286665e-64 *** df.mm.trans1:probe16 -0.879317767303468 0.0502308989980469 -17.5055152275427 9.77223195631295e-56 *** df.mm.trans1:probe17 -0.843146108026276 0.0502308989980469 -16.7854074851230 3.98703494061089e-52 *** df.mm.trans1:probe18 -0.848847939523504 0.0502308989980469 -16.8989199169322 1.08374311325159e-52 *** df.mm.trans2:probe2 -0.0825250519054852 0.0502308989980469 -1.64291409374724 0.100924624003601 df.mm.trans2:probe3 -0.140496214877719 0.0502308989980469 -2.79700777171402 0.00532322932576895 ** df.mm.trans2:probe4 -0.0453610608774911 0.0502308989980469 -0.903050946375753 0.366861254623617 df.mm.trans2:probe5 -0.0221158226528578 0.0502308989980469 -0.440283233905842 0.659890548362433 df.mm.trans2:probe6 -0.0524373368531318 0.0502308989980469 -1.04392590813815 0.296940077840453 df.mm.trans3:probe2 0.0634032396400375 0.0502308989980469 1.26223581310983 0.207354346370771 df.mm.trans3:probe3 0.771571953271275 0.0502308989980469 15.3605045631629 3.78093625615006e-45 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.07287110127452 0.731304305768129 6.9367444732138 1.04195054472722e-11 *** df.mm.trans1 -0.202545299354714 0.653438749849875 -0.309968301392056 0.75669269025889 df.mm.trans2 -0.36592281230694 0.605475745691576 -0.604355855557817 0.545835530956764 df.mm.exp2 0.347444337072787 0.830705869793686 0.418251934537405 0.67591258236602 df.mm.exp3 -0.984556078038082 0.830705869793686 -1.18520419060311 0.236405926822552 df.mm.exp4 -0.977498160739507 0.830705869793686 -1.17670790141675 0.239778723972111 df.mm.exp5 -0.82054335371252 0.830705869793686 -0.98776640872456 0.323665218967556 df.mm.exp6 -0.621282049676502 0.830705869793686 -0.74789654469494 0.454815589236148 df.mm.exp7 -1.09512726670242 0.830705869793686 -1.31830929155997 0.187903160691736 df.mm.exp8 -0.365781722344786 0.830705869793686 -0.44032639667712 0.659859308644751 df.mm.trans1:exp2 -0.264834541555 0.788076784265795 -0.336051698061034 0.736949366372275 df.mm.trans2:exp2 -0.134189322208833 0.695018395063598 -0.193073051248600 0.846967094292704 df.mm.trans1:exp3 0.640542995779247 0.788076784265795 0.81279262194737 0.416659350162968 df.mm.trans2:exp3 0.936581888682113 0.695018395063598 1.34756417288266 0.178307218225713 df.mm.trans1:exp4 0.79667306491043 0.788076784265795 1.01090792270025 0.312467989803952 df.mm.trans2:exp4 1.07587633620638 0.695018395063598 1.54798253376867 0.122153770177840 df.mm.trans1:exp5 0.636048197695935 0.788076784265795 0.807089119226504 0.41993495559348 df.mm.trans2:exp5 0.777164784731617 0.695018395063598 1.11819311582466 0.263932024180492 df.mm.trans1:exp6 0.617437367727654 0.788076784265795 0.783473615839204 0.43365819169243 df.mm.trans2:exp6 0.888456557591237 0.695018395063598 1.27832092488709 0.201630567384344 df.mm.trans1:exp7 0.936708953800665 0.788076784265795 1.18860112682211 0.235066890543913 df.mm.trans2:exp7 0.48018316989597 0.695018395063598 0.690892749467489 0.489900139120155 df.mm.trans1:exp8 0.409498470814782 0.788076784265795 0.519617477624706 0.603521848007404 df.mm.trans2:exp8 0.222691311541591 0.695018395063598 0.320410672758112 0.748768590572546 df.mm.trans1:probe2 -0.237517706083022 0.394038392132897 -0.602778081590878 0.546884085019497 df.mm.trans1:probe3 0.393769080986701 0.394038392132898 0.999316535770184 0.318044218488529 df.mm.trans1:probe4 0.160974478414061 0.394038392132897 0.408524858561927 0.68303414263342 df.mm.trans1:probe5 0.0582500333981624 0.394038392132897 0.147828319679358 0.88252792253446 df.mm.trans1:probe6 -0.321837963623823 0.394038392132898 -0.816768035931068 0.414385174275513 df.mm.trans1:probe7 -0.163681223508156 0.394038392132897 -0.415394100615839 0.678001931848133 df.mm.trans1:probe8 0.567218759421922 0.394038392132897 1.43950125354947 0.150530057337783 df.mm.trans1:probe9 -0.28312834509621 0.394038392132897 -0.718529845692598 0.472710359975941 df.mm.trans1:probe10 0.240740320850956 0.394038392132897 0.6109565099681 0.541459746569381 df.mm.trans1:probe11 -0.0769947461373229 0.394038392132898 -0.195399097333020 0.845146674812186 df.mm.trans1:probe12 0.190408033114035 0.394038392132898 0.483222033475905 0.629114371427139 df.mm.trans1:probe13 -0.0948759440828642 0.394038392132898 -0.240778426612972 0.809809101234362 df.mm.trans1:probe14 -0.0450999137047083 0.394038392132897 -0.114455633271129 0.908914904448896 df.mm.trans1:probe15 -0.243718149179937 0.394038392132897 -0.618513713500632 0.53647148855181 df.mm.trans1:probe16 0.630634107685364 0.394038392132897 1.60043823210168 0.110027769251898 df.mm.trans1:probe17 0.217202004366934 0.394038392132897 0.551220410760579 0.581687792648048 df.mm.trans1:probe18 -0.190861418119101 0.394038392132898 -0.484372644721202 0.628298188575575 df.mm.trans2:probe2 -0.0949929560972428 0.394038392132897 -0.241075382485077 0.809579049164427 df.mm.trans2:probe3 0.153038380512328 0.394038392132897 0.388384440622509 0.69786932510668 df.mm.trans2:probe4 0.565614641524551 0.394038392132897 1.43543028501087 0.151685606519894 df.mm.trans2:probe5 0.474856097026289 0.394038392132897 1.20510109295679 0.228639360819851 df.mm.trans2:probe6 -0.186193200373931 0.394038392132897 -0.47252553073847 0.636723547711614 df.mm.trans3:probe2 -0.54543574273879 0.394038392132897 -1.38421979590971 0.166805781800332 df.mm.trans3:probe3 -0.49514158659033 0.394038392132898 -1.25658209066931 0.20939399560354