chr2.12908_chr2_131683309_131683839_-_2.R fitVsDatCorrelation=0.947825659167615 cont.fitVsDatCorrelation=0.289337880370201 fstatistic=7355.81090997633,62,922 cont.fstatistic=802.623479752182,62,922 residuals=-0.64831462371286,-0.114345866101241,-0.00787003154853496,0.101468865128684,0.890445973835634 cont.residuals=-1.00334905557436,-0.473799415846424,-0.185024654642239,0.445710728523682,1.87611715966321 predictedValues: Include Exclude Both chr2.12908_chr2_131683309_131683839_-_2.R.tl.Lung 74.8333718440713 250.209501875624 59.7307285610009 chr2.12908_chr2_131683309_131683839_-_2.R.tl.cerebhem 79.9374436066863 235.616566234573 59.0539145735022 chr2.12908_chr2_131683309_131683839_-_2.R.tl.cortex 67.8427912351121 183.847157097067 58.8792382353793 chr2.12908_chr2_131683309_131683839_-_2.R.tl.heart 70.6072547288382 198.710948850444 59.3906870008876 chr2.12908_chr2_131683309_131683839_-_2.R.tl.kidney 81.9865838052714 252.375557950516 65.7763373663219 chr2.12908_chr2_131683309_131683839_-_2.R.tl.liver 73.295327406572 209.035688817827 67.8930920634776 chr2.12908_chr2_131683309_131683839_-_2.R.tl.stomach 72.0023118185744 204.534503085656 63.3185890821069 chr2.12908_chr2_131683309_131683839_-_2.R.tl.testicle 77.9837399232508 204.872367320363 64.6505682562752 diffExp=-175.376130031553,-155.679122627886,-116.004365861955,-128.103694121605,-170.388974145244,-135.740361411255,-132.532191267082,-126.888627397112 diffExpScore=0.999124123495935 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 85.2390836583577 83.689259287182 88.6357520252915 cerebhem 81.1252566603413 72.2489727980014 74.6977078753564 cortex 101.644574880423 83.5560593638153 80.3196376446009 heart 96.770250586801 74.3557142349053 71.776822755098 kidney 76.963422110511 91.9453683106442 85.6383705667448 liver 84.1218831130455 59.7828516151416 63.7633595941973 stomach 80.5277660241516 81.7553488558 89.3637288571387 testicle 85.9776668588176 112.176135185152 100.42426835272 cont.diffExp=1.54982437117566,8.8762838623398,18.0885155166080,22.4145363518957,-14.9819462001332,24.3390314979039,-1.22758283164839,-26.1984683263343 cont.diffExpScore=3.47535481095215 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,0,0,1,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,0,1,0,1,0,-1 cont.diffExp1.3Score=1.5 cont.diffExp1.2=0,0,1,1,0,1,0,-1 cont.diffExp1.2Score=1.33333333333333 tran.correlation=0.775355011172325 cont.tran.correlation=-0.0672430236835264 tran.covariance=0.00588763530251178 cont.tran.covariance=-0.000947867952227769 tran.mean=146.105694725028 cont.tran.mean=84.4924758464432 weightedLogRatios: wLogRatio Lung -5.93713936628529 cerebhem -5.32019477449354 cortex -4.70108517407155 heart -4.94025457534237 kidney -5.58666232733674 liver -5.04982817969565 stomach -5.01004554878565 testicle -4.67435506631796 cont.weightedLogRatios: wLogRatio Lung 0.0814032263425145 cerebhem 0.502677597402861 cortex 0.88644492108948 heart 1.17000527743531 kidney -0.788341282371747 liver 1.45550382652551 stomach -0.0665104516236574 testicle -1.22008362215366 varWeightedLogRatios=0.191508313094426 cont.varWeightedLogRatios=0.87662912234131 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.61154257487059 0.09748528516502 57.5629703023544 1.62457492802568e-307 *** df.mm.trans1 -1.44139171258973 0.0847930001184174 -16.9989469717637 1.40131952169857e-56 *** df.mm.trans2 -0.097684912552414 0.0745253314140807 -1.31076119621197 0.190264844603012 df.mm.exp2 0.0172834019701426 0.0960362077179322 0.179967559953071 0.857217580890148 df.mm.exp3 -0.391906560597671 0.0960362077179323 -4.08082086861175 4.87641966836901e-05 *** df.mm.exp4 -0.282869185027805 0.0960362077179322 -2.94544309640609 0.00330599996370045 ** df.mm.exp5 0.00349784669221148 0.0960362077179322 0.0364221659239710 0.970953623996704 df.mm.exp6 -0.328648337815608 0.0960362077179322 -3.42212948246436 0.000648645721140474 *** df.mm.exp7 -0.298459948158489 0.0960362077179322 -3.10778564929485 0.0019427136128036 ** df.mm.exp8 -0.237825268995131 0.0960362077179322 -2.47641253904618 0.0134495072456594 * df.mm.trans1:exp2 0.048697038766929 0.0900069034540578 0.541036708276331 0.588612970972958 df.mm.trans2:exp2 -0.0773762120098786 0.0660470104638278 -1.17153238983096 0.241687502160251 df.mm.trans1:exp3 0.293835762486234 0.0900069034540579 3.26459139477248 0.00113658432367079 ** df.mm.trans2:exp3 0.08371273062764 0.0660470104638278 1.26747191189656 0.205306618070451 df.mm.trans1:exp4 0.224738149312408 0.0900069034540578 2.49689902316349 0.0127019591482162 * df.mm.trans2:exp4 0.0524218610529317 0.0660470104638277 0.793705281810474 0.427571242266305 df.mm.trans1:exp5 0.0877938419211067 0.0900069034540579 0.975412313411263 0.329611621541587 df.mm.trans2:exp5 0.00512186630531683 0.0660470104638278 0.0775487984898567 0.938203797850372 df.mm.trans1:exp6 0.307881265383531 0.0900069034540579 3.42064056831689 0.000652161771885744 *** df.mm.trans2:exp6 0.148854760664017 0.0660470104638278 2.25376984694168 0.0244448160565282 * df.mm.trans1:exp7 0.259894242116213 0.0900069034540578 2.88749231606296 0.00397403135953084 ** df.mm.trans2:exp7 0.096898054222621 0.0660470104638277 1.46710734584557 0.142687862841236 df.mm.trans1:exp8 0.279061678296792 0.0900069034540578 3.10044749444395 0.00199098464623813 ** df.mm.trans2:exp8 0.0379138813688961 0.0660470104638278 0.574043868187805 0.566078125487832 df.mm.trans1:probe2 -0.118663708847335 0.0603784663702602 -1.96533161540823 0.0496757125226329 * df.mm.trans1:probe3 -0.260616434937814 0.0603784663702602 -4.31638050128054 1.75761110751416e-05 *** df.mm.trans1:probe4 0.201639827850199 0.0603784663702602 3.33959836961872 0.00087263951711215 *** df.mm.trans1:probe5 0.0643697340892195 0.0603784663702602 1.06610415863304 0.286655647419229 df.mm.trans1:probe6 -0.0280514422200172 0.0603784663702602 -0.464593486823543 0.642332285593499 df.mm.trans1:probe7 -0.219867911299081 0.0603784663702602 -3.64149546215334 0.000286155899534484 *** df.mm.trans1:probe8 0.723733497613554 0.0603784663702602 11.9866161087197 7.19109304533992e-31 *** df.mm.trans1:probe9 -0.180448111914077 0.0603784663702602 -2.98861701467393 0.00287675767136533 ** df.mm.trans1:probe10 0.0541716470440394 0.0603784663702602 0.897201441186688 0.369845645210381 df.mm.trans1:probe11 -0.25408480757469 0.0603784663702602 -4.20820240806647 2.82579419256286e-05 *** df.mm.trans1:probe12 -0.288409066542746 0.0603784663702602 -4.77668751594531 2.07232296587267e-06 *** df.mm.trans1:probe13 -0.212738640465470 0.0603784663702602 -3.52341908058558 0.000446939655749776 *** df.mm.trans1:probe14 -0.22850371800568 0.0603784663702602 -3.78452338627519 0.000163950471239878 *** df.mm.trans1:probe15 -0.230628523361131 0.0603784663702602 -3.81971482923801 0.000142549921507363 *** df.mm.trans1:probe16 -0.295509166759455 0.0603784663702602 -4.89428076803571 1.16431347922636e-06 *** df.mm.trans1:probe17 0.90954555404872 0.0603784663702602 15.0640718244 5.20046463331266e-46 *** df.mm.trans1:probe18 1.40934315388359 0.0603784663702602 23.3418176811754 4.70077498138924e-95 *** df.mm.trans1:probe19 1.01284317995248 0.0603784663702602 16.7749073608693 2.54582797626349e-55 *** df.mm.trans1:probe20 1.08815501246332 0.0603784663702602 18.0222366992630 1.94398202146165e-62 *** df.mm.trans1:probe21 1.14572859319649 0.0603784663702602 18.9757816333147 4.85351327171979e-68 *** df.mm.trans1:probe22 0.953918737769546 0.0603784663702602 15.7989891945882 6.10647451030534e-50 *** df.mm.trans1:probe23 -0.0237485801991245 0.0603784663702602 -0.393328642259486 0.694167697780233 df.mm.trans1:probe24 0.094389498888284 0.0603784663702602 1.56329738999095 0.118325808507376 df.mm.trans1:probe25 0.000952204101204654 0.0603784663702602 0.0157705910475670 0.987420822330851 df.mm.trans1:probe26 -0.238563048907902 0.0603784663702602 -3.95112799727235 8.37215984152893e-05 *** df.mm.trans2:probe2 0.140024922782696 0.0603784663702602 2.31912022945429 0.0206062942169579 * df.mm.trans2:probe3 -0.233629118171743 0.0603784663702602 -3.86941126889599 0.000116776819441363 *** df.mm.trans2:probe4 -0.0458307972548588 0.0603784663702602 -0.759058651370997 0.448011479978635 df.mm.trans2:probe5 0.445805325794283 0.0603784663702602 7.38351522644615 3.4444928904152e-13 *** df.mm.trans2:probe6 -0.179756651435543 0.0603784663702602 -2.97716491063581 0.00298535172946581 ** df.mm.trans3:probe2 0.441192711414859 0.0603784663702602 7.3071202025789 5.90838246172416e-13 *** df.mm.trans3:probe3 -0.238782797189519 0.0603784663702602 -3.95476751140424 8.24783635695498e-05 *** df.mm.trans3:probe4 -0.219922535651017 0.0603784663702602 -3.64240016138173 0.000285166090238006 *** df.mm.trans3:probe5 -0.0187690482524520 0.0603784663702602 -0.310856657692400 0.755979857717135 df.mm.trans3:probe6 -0.244164614836662 0.0603784663702602 -4.04390223062914 5.696290494053e-05 *** df.mm.trans3:probe7 0.414301169216752 0.0603784663702602 6.86173720736999 1.24708562201456e-11 *** df.mm.trans3:probe8 0.0473788762651005 0.0603784663702602 0.784698239510722 0.432832082506160 df.mm.trans3:probe9 -0.0248078703427969 0.0603784663702602 -0.410872813341548 0.681261270556515 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.19309730983553 0.292718717884864 14.3246641012032 3.601622480267e-42 *** df.mm.trans1 0.159054567144626 0.254607638868357 0.624704615507879 0.532319501893343 df.mm.trans2 0.200483912144059 0.223776946690432 0.895909588137348 0.370534895108941 df.mm.exp2 -0.0253723633431627 0.288367578205584 -0.0879861858987285 0.929906761732767 df.mm.exp3 0.272950395327608 0.288367578205584 0.946536351368233 0.344123087562658 df.mm.exp4 0.219603118725739 0.288367578205584 0.761538866790283 0.446530012860028 df.mm.exp5 0.0263560080011988 0.288367578205584 0.091397265133631 0.927196787569717 df.mm.exp6 -0.0202285346057378 0.288367578205584 -0.0701484360052309 0.944090726739605 df.mm.exp7 -0.0884170052189142 0.288367578205584 -0.306612157195701 0.759207827117528 df.mm.exp8 0.176718547291108 0.288367578205584 0.612823911726723 0.540143901204298 df.mm.trans1:exp2 -0.0240933549098017 0.270263407808262 -0.0891476767246815 0.92898390794868 df.mm.trans2:exp2 -0.121620172426742 0.198319122628335 -0.613254893501458 0.539859060764255 df.mm.trans1:exp3 -0.0969282842947405 0.270263407808262 -0.358643758253452 0.719943711600998 df.mm.trans2:exp3 -0.274543264444715 0.198319122628335 -1.38435094309705 0.166585975388958 df.mm.trans1:exp4 -0.0927235573631346 0.270263407808262 -0.343085873574558 0.731612066948343 df.mm.trans2:exp4 -0.337853238222459 0.198319122628335 -1.70358376814535 0.0887958541283673 . df.mm.trans1:exp5 -0.128485793575466 0.270263407808262 -0.475409507404052 0.63460772556048 df.mm.trans2:exp5 0.0677279246222367 0.198319122628335 0.341509803616688 0.732797642159668 df.mm.trans1:exp6 0.00703521418602316 0.270263407808262 0.0260309534430731 0.979238282371994 df.mm.trans2:exp6 -0.316163253183125 0.198319122628335 -1.59421466267596 0.111230681333936 df.mm.trans1:exp7 0.0315589926909851 0.270263407808262 0.116771237907925 0.907066766619705 df.mm.trans2:exp7 0.0650375969519312 0.198319122628335 0.327944154300322 0.74302834282537 df.mm.trans1:exp8 -0.168091029486505 0.270263407808262 -0.621952601166623 0.53412679719878 df.mm.trans2:exp8 0.116241078956628 0.198319122628335 0.586131470410308 0.557930625164805 df.mm.trans1:probe2 0.103159631326564 0.181298205507007 0.569005253185352 0.569491152843849 df.mm.trans1:probe3 0.102499294843272 0.181298205507007 0.565362986117977 0.571964440121027 df.mm.trans1:probe4 0.2580425901389 0.181298205507007 1.42330471179941 0.154986125215994 df.mm.trans1:probe5 0.0405398021080016 0.181298205507007 0.223608402491523 0.823111559520025 df.mm.trans1:probe6 0.105308360122696 0.181298205507007 0.580857156463283 0.56147867944549 df.mm.trans1:probe7 0.351489247393054 0.181298205507007 1.93873539128588 0.0528384432708396 . df.mm.trans1:probe8 0.0718501462911533 0.181298205507007 0.396309197270993 0.691968642644099 df.mm.trans1:probe9 0.146156688655577 0.181298205507007 0.806167321109687 0.420354256499586 df.mm.trans1:probe10 0.208869159926788 0.181298205507007 1.15207516446552 0.249588820370081 df.mm.trans1:probe11 0.187019999571763 0.181298205507007 1.03156012520231 0.302548741054882 df.mm.trans1:probe12 -0.110114774905416 0.181298205507007 -0.607368256058994 0.543756099943803 df.mm.trans1:probe13 0.416124764053479 0.181298205507007 2.29525031916213 0.0219425631520803 * df.mm.trans1:probe14 0.133028359058185 0.181298205507007 0.733754416852427 0.463284963225178 df.mm.trans1:probe15 0.159088549277959 0.181298205507007 0.877496546824951 0.380445583852494 df.mm.trans1:probe16 -0.177800918855592 0.181298205507007 -0.9807097558322 0.326993153692870 df.mm.trans1:probe17 -0.135341779584300 0.181298205507007 -0.746514722557854 0.455546845764914 df.mm.trans1:probe18 0.207146638200449 0.181298205507007 1.1425741232306 0.253512065782509 df.mm.trans1:probe19 0.415971827409141 0.181298205507007 2.29440675513507 0.0219911376190505 * df.mm.trans1:probe20 0.243540481855709 0.181298205507007 1.34331435424107 0.179500743098258 df.mm.trans1:probe21 0.133998655857082 0.181298205507007 0.73910635509243 0.460030535062566 df.mm.trans1:probe22 -0.106384957777363 0.181298205507007 -0.586795426241833 0.557484754460068 df.mm.trans1:probe23 0.269632601054219 0.181298205507007 1.48723259725700 0.137295281031527 df.mm.trans1:probe24 0.280161481307225 0.181298205507007 1.54530752537646 0.122615043540249 df.mm.trans1:probe25 -0.0174325869470303 0.181298205507007 -0.0961542167407533 0.923418987251372 df.mm.trans1:probe26 -0.0207669584251318 0.181298205507007 -0.114545857566854 0.908830035631136 df.mm.trans2:probe2 0.0264554146693332 0.181298205507007 0.14592209887213 0.88401478200414 df.mm.trans2:probe3 0.146389093819241 0.181298205507007 0.807449215560954 0.419615975917858 df.mm.trans2:probe4 0.0598846358783122 0.181298205507007 0.330310141299208 0.741240670027548 df.mm.trans2:probe5 -0.0113921585243478 0.181298205507007 -0.0628365763052605 0.949910259081578 df.mm.trans2:probe6 0.281604364453863 0.181298205507007 1.55326614329329 0.120702734928213 df.mm.trans3:probe2 -0.148725536607316 0.181298205507007 -0.820336506869445 0.412236328546040 df.mm.trans3:probe3 -0.0775381960667546 0.181298205507007 -0.427683196587172 0.668981655581318 df.mm.trans3:probe4 0.0604053695398646 0.181298205507007 0.333182390696802 0.739072359103123 df.mm.trans3:probe5 -0.0349789397236334 0.181298205507007 -0.192935940131418 0.847051628089593 df.mm.trans3:probe6 -0.122192696336720 0.181298205507007 -0.673987345848259 0.500488291820713 df.mm.trans3:probe7 -0.159475397107493 0.181298205507007 -0.879630312178295 0.379288813617122 df.mm.trans3:probe8 -0.173768791803907 0.181298205507007 -0.958469452678565 0.338077349873008 df.mm.trans3:probe9 0.0433697675217412 0.181298205507007 0.239217853262564 0.810989824185409