chr2.12756_chr2_26649442_26650941_-_0.R fitVsDatCorrelation=0.835825976384038 cont.fitVsDatCorrelation=0.325747779463262 fstatistic=12387.5896959061,39,393 cont.fstatistic=4170.08026234763,39,393 residuals=-0.338356911001479,-0.0735995099558163,0.00446850952898671,0.0672112702871675,0.408999372293002 cont.residuals=-0.465018051728394,-0.129882095241347,-0.0343448699283035,0.085621524588314,0.8184473717656 predictedValues: Include Exclude Both chr2.12756_chr2_26649442_26650941_-_0.R.tl.Lung 54.5863906933412 48.7713855368639 64.8662397432563 chr2.12756_chr2_26649442_26650941_-_0.R.tl.cerebhem 55.928604267899 52.9106722024443 65.4047405943068 chr2.12756_chr2_26649442_26650941_-_0.R.tl.cortex 54.8017866057937 50.5097901242177 68.6857703870818 chr2.12756_chr2_26649442_26650941_-_0.R.tl.heart 56.8428760773707 50.0103260641982 62.2376256761757 chr2.12756_chr2_26649442_26650941_-_0.R.tl.kidney 58.3410275437413 52.8576339663338 68.5728527745006 chr2.12756_chr2_26649442_26650941_-_0.R.tl.liver 56.9075695100341 52.0299747827595 66.3233876389825 chr2.12756_chr2_26649442_26650941_-_0.R.tl.stomach 55.17503054723 48.6329021413728 60.1748097906423 chr2.12756_chr2_26649442_26650941_-_0.R.tl.testicle 57.902808808599 51.6247399806389 68.1452185624517 diffExp=5.8150051564773,3.01793206545464,4.29199648157597,6.83255001317255,5.48339357740758,4.87759472727455,6.54212840585723,6.27806882796016 diffExpScore=0.977344128926528 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=0,0,0,0,0,0,0,0 diffExp1.4Score=0 diffExp1.3=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 56.6004981099606 58.5169566531046 59.9146122001552 cerebhem 60.1624131732736 60.4609607598091 54.4547069948718 cortex 56.5363411803922 54.9330270487945 54.2382134760332 heart 56.6078155924252 56.8813269435115 59.3514045080473 kidney 61.3744733963226 59.0209582678786 58.067639584681 liver 54.4390058387525 63.9055627288801 67.2253907671168 stomach 57.7420954151653 55.5754617290556 60.9489207700475 testicle 60.492123424457 57.6607243150225 60.3233660645317 cont.diffExp=-1.91645854314397,-0.298547586535584,1.60331413159778,-0.27351135108632,2.35351512844401,-9.4665568901276,2.16663368610961,2.83139910943453 cont.diffExpScore=5.22720665262283 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=0,0,0,0,0,0,0,0 cont.diffExp1.3Score=0 cont.diffExp1.2=0,0,0,0,0,0,0,0 cont.diffExp1.2Score=0 tran.correlation=0.676545168610857 cont.tran.correlation=-0.146632691139249 tran.covariance=0.000571203049187413 cont.tran.covariance=-0.000287269985622387 tran.mean=53.6145949283024 cont.tran.mean=58.1818590360503 weightedLogRatios: wLogRatio Lung 0.444195032077738 cerebhem 0.221680572953458 cortex 0.323200413293504 heart 0.50920543287203 kidney 0.3964871224267 liver 0.358130991865993 stomach 0.498202845731588 testicle 0.459218292822946 cont.weightedLogRatios: wLogRatio Lung -0.134948888386379 cerebhem -0.0202930013942720 cortex 0.115665278570832 heart -0.0194660620258201 kidney 0.160215770783851 liver -0.653686109560005 stomach 0.154388641214258 testicle 0.195512835855291 varWeightedLogRatios=0.00949680952267666 cont.varWeightedLogRatios=0.0774692439883189 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.54861079078206 0.0633623186261507 56.0050652773538 1.99908033205683e-189 *** df.mm.trans1 0.410470503109839 0.0517351165179052 7.93407903058995 2.23250012436357e-14 *** df.mm.trans2 0.318182014112042 0.0517351165179052 6.15021354019606 1.90526103219783e-09 *** df.mm.exp2 0.0974851966232923 0.0702941811504226 1.3868174438889 0.166283527451258 df.mm.exp3 -0.0182531502970938 0.0702941811504226 -0.259668012321445 0.795255843229556 df.mm.exp4 0.106959599199502 0.0702941811504226 1.52159961819058 0.128913599107129 df.mm.exp5 0.0914099244386224 0.0702941811504226 1.30039105574065 0.194229031424546 df.mm.exp6 0.0841046886014517 0.0702941811504226 1.19646729252704 0.232235557532894 df.mm.exp7 0.0829559072933021 0.0702941811504226 1.18012481169365 0.238664392734467 df.mm.exp8 0.0665248377578585 0.0702941811504226 0.946377590137965 0.344537539805820 df.mm.trans1:exp2 -0.0731938400634545 0.0573949585684342 -1.27526601445635 0.202968444549742 df.mm.trans2:exp2 -0.0160239140812461 0.0573949585684342 -0.279186787148565 0.780248343997673 df.mm.trans1:exp3 0.0221913490340923 0.0573949585684342 0.386642826958968 0.699229907339663 df.mm.trans2:exp3 0.0532765527029427 0.0573949585684343 0.928244466618422 0.353850518595245 df.mm.trans1:exp4 -0.0664532947002437 0.0573949585684342 -1.15782459570920 0.247638785188348 df.mm.trans2:exp4 -0.0818738727421714 0.0573949585684343 -1.42649937876599 0.154518161136840 df.mm.trans1:exp5 -0.0248889441125379 0.0573949585684342 -0.43364338494751 0.664785359510125 df.mm.trans2:exp5 -0.0109515555760594 0.0573949585684342 -0.190810409994485 0.848772663414935 df.mm.trans1:exp6 -0.0424609214873534 0.0573949585684342 -0.739802284842242 0.45986165953118 df.mm.trans2:exp6 -0.0194284768988673 0.0573949585684342 -0.338504938124521 0.735163478927148 df.mm.trans1:exp7 -0.0722299984890967 0.0573949585684342 -1.25847287445942 0.208967892405439 df.mm.trans2:exp7 -0.0857993855856757 0.0573949585684342 -1.49489411135952 0.135744586656609 df.mm.trans1:exp8 -0.00754353996181302 0.0573949585684342 -0.131432100483504 0.89550075312688 df.mm.trans2:exp8 -0.00966760211618572 0.0573949585684342 -0.168439918022742 0.866323859041177 df.mm.trans1:probe2 0.0493475358007245 0.0351470905752113 1.40402903890795 0.161099940377011 df.mm.trans1:probe3 0.127138619346599 0.0351470905752113 3.61732983487026 0.000336464462144256 *** df.mm.trans1:probe4 0.0949228083580383 0.0351470905752113 2.70073018291266 0.00721797737626887 ** df.mm.trans1:probe5 0.082986874622657 0.0351470905752113 2.36113070141818 0.0187066136076636 * df.mm.trans1:probe6 0.134043798941566 0.0351470905752113 3.81379501824555 0.000158854992826429 *** df.mm.trans2:probe2 0.00383727025526602 0.0351470905752113 0.109177465117764 0.913117457200383 df.mm.trans2:probe3 0.0704224515915218 0.0351470905752113 2.00364953226569 0.0457936001907195 * df.mm.trans2:probe4 0.133022774933296 0.0351470905752113 3.78474498902379 0.000177863955373487 *** df.mm.trans2:probe5 0.0315096204719747 0.0351470905752113 0.896507220264711 0.370530745754796 df.mm.trans2:probe6 0.00541957120502466 0.0351470905752113 0.154196865695820 0.87753366589676 df.mm.trans3:probe2 -0.177791351187071 0.0351470905752113 -5.0584941250433 6.4983052563586e-07 *** df.mm.trans3:probe3 -0.38864561984067 0.0351470905752113 -11.0576896545393 6.25502385266027e-25 *** df.mm.trans3:probe4 -0.118060377312040 0.0351470905752113 -3.35903698940322 0.000858596436883374 *** df.mm.trans3:probe5 -0.30551731189747 0.0351470905752113 -8.69253491248993 9.72531639546217e-17 *** df.mm.trans3:probe6 0.36039860926788 0.0351470905752113 10.254009745036 5.08170437253998e-22 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.03791764629347 0.109120094031839 37.0043453693807 3.99341934392198e-130 *** df.mm.trans1 -0.0202298014325927 0.0890961836875085 -0.227055756995673 0.820498449132235 df.mm.trans2 0.0526419718193885 0.0890961836875085 0.590844294790699 0.554964387050021 df.mm.exp2 0.189262443012385 0.121057875143153 1.56340463425926 0.118762301289541 df.mm.exp3 0.0351987489972783 0.121057875143153 0.290759679662766 0.771388502239101 df.mm.exp4 -0.0187755478587865 0.121057875143153 -0.155095633692431 0.876825548692832 df.mm.exp5 0.120864144243551 0.121057875143153 0.998399683627578 0.318699911672937 df.mm.exp6 -0.0659776243281785 0.121057875143153 -0.545008940972727 0.586056514394554 df.mm.exp7 -0.0487218534675578 0.121057875143153 -0.402467443030396 0.687558863116575 df.mm.exp8 0.0449559569480833 0.121057875143153 0.37135921058355 0.710570120796677 df.mm.trans1:exp2 -0.128232437287382 0.09884334114876 -1.29733005579396 0.195278683362842 df.mm.trans2:exp2 -0.156581132508892 0.09884334114876 -1.58413435532532 0.113967477854014 df.mm.trans1:exp3 -0.0363328965808218 0.09884334114876 -0.367580619580033 0.713383840622173 df.mm.trans2:exp3 -0.0984005653289444 0.09884334114876 -0.995520428440907 0.320095762182288 df.mm.trans1:exp4 0.0189048225071835 0.09884334114876 0.191260456065843 0.8484203117883 df.mm.trans2:exp4 -0.00957390764962118 0.09884334114876 -0.0968594094286267 0.92288741888068 df.mm.trans1:exp5 -0.0398879239660773 0.09884334114876 -0.403546900605531 0.686765414155044 df.mm.trans2:exp5 -0.112288108091274 0.09884334114876 -1.13602096799095 0.256640065343225 df.mm.trans1:exp6 0.0270407546496591 0.09884334114876 0.273571839391412 0.784557393557064 df.mm.trans2:exp6 0.154067466027492 0.09884334114876 1.55870354276692 0.119871452343652 df.mm.trans1:exp7 0.0686905318734695 0.09884334114876 0.694943443586045 0.487501406426695 df.mm.trans2:exp7 -0.00285294805689049 0.09884334114876 -0.0288633308398264 0.976988242475696 df.mm.trans1:exp8 0.0215394225820439 0.09884334114876 0.217914756135437 0.827608631007249 df.mm.trans2:exp8 -0.059696272543701 0.09884334114876 -0.603948347454763 0.546226438722371 df.mm.trans1:probe2 0.0617103752413103 0.0605289375715765 1.01951855950448 0.308584041098087 df.mm.trans1:probe3 0.0232006341529098 0.0605289375715765 0.383298222035941 0.701705908923056 df.mm.trans1:probe4 -0.00978854088651043 0.0605289375715765 -0.161716714008656 0.871612048269036 df.mm.trans1:probe5 0.141529472305049 0.0605289375715765 2.33821173777729 0.0198770677268292 * df.mm.trans1:probe6 0.00330734925372333 0.0605289375715766 0.0546407947407359 0.956452403702701 df.mm.trans2:probe2 -0.104099827471970 0.0605289375715765 -1.71983569592428 0.0862495907930935 . df.mm.trans2:probe3 -0.0669980501887309 0.0605289375715766 -1.10687636156680 0.269024428561691 df.mm.trans2:probe4 -0.0409256782072561 0.0605289375715765 -0.676134091381676 0.49935321012194 df.mm.trans2:probe5 -0.0307478193973637 0.0605289375715765 -0.507985446812177 0.611748539060519 df.mm.trans2:probe6 -0.0121452074251394 0.0605289375715766 -0.200651257273060 0.841075072936721 df.mm.trans3:probe2 0.091611052962501 0.0605289375715765 1.51350835877747 0.130954343597631 df.mm.trans3:probe3 0.0728453796276373 0.0605289375715765 1.20348022863438 0.229514968273146 df.mm.trans3:probe4 -0.00926994032718784 0.0605289375715766 -0.153148901981403 0.878359454939466 df.mm.trans3:probe5 -0.00311337821698390 0.0605289375715765 -0.0514361946846047 0.959004076819188 df.mm.trans3:probe6 -0.0165295024471016 0.0605289375715766 -0.273084298358205 0.784931859686916