chr2.12941_chr2_179347611_179348401_+_2.R fitVsDatCorrelation=0.937417844570018 cont.fitVsDatCorrelation=0.245594915676710 fstatistic=10731.2728391893,62,922 cont.fstatistic=1371.70933641800,62,922 residuals=-0.676903946116128,-0.0887301647252822,-0.00797918976142703,0.0831302914193092,0.925859619850402 cont.residuals=-1.05627283378196,-0.305041332825018,-0.133994463975076,0.202312802333941,1.85292502381796 predictedValues: Include Exclude Both chr2.12941_chr2_179347611_179348401_+_2.R.tl.Lung 62.3853531660906 66.5654521493945 62.228592179979 chr2.12941_chr2_179347611_179348401_+_2.R.tl.cerebhem 66.4645273590625 91.9978951430251 54.0507303720925 chr2.12941_chr2_179347611_179348401_+_2.R.tl.cortex 58.3942435328335 62.9138143273559 58.6124652024137 chr2.12941_chr2_179347611_179348401_+_2.R.tl.heart 62.2605742008296 63.7539130983484 59.630815458549 chr2.12941_chr2_179347611_179348401_+_2.R.tl.kidney 63.5414479400133 71.7306156630673 64.7000404368795 chr2.12941_chr2_179347611_179348401_+_2.R.tl.liver 64.448267627114 73.036902237977 69.6703629404774 chr2.12941_chr2_179347611_179348401_+_2.R.tl.stomach 67.0453232799914 68.0403533427846 60.791353821622 chr2.12941_chr2_179347611_179348401_+_2.R.tl.testicle 66.9240353698097 71.1261585271565 67.7271731772919 diffExp=-4.18009898330393,-25.5333677839626,-4.51957079452235,-1.49333889751877,-8.18916772305403,-8.58863461086287,-0.995030062793205,-4.20212315734685 diffExpScore=0.982964611437227 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,-1,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,-1,0,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 65.5728780776039 69.7117949996672 69.6801220227559 cerebhem 68.1909398155553 55.1670677674463 61.9102036733965 cortex 66.0387692982018 60.0433440776728 110.439004549246 heart 69.1838936274755 69.1996023531357 56.5247438294678 kidney 69.4319427983052 75.3602733232385 68.7149564649777 liver 64.5686346879234 68.7361253208465 77.0458373470243 stomach 66.6330430024836 72.452678744396 65.1177167813595 testicle 65.7918137264493 70.9467922614934 54.3282791696625 cont.diffExp=-4.1389169220633,13.023872048109,5.99542522052896,-0.0157087256602040,-5.9283305249333,-4.16749063292306,-5.81963574191236,-5.15497853504415 cont.diffExpScore=6.14013441098863 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=0,1,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.571399679907086 cont.tran.correlation=0.0389751708926922 tran.covariance=0.00337695470484577 cont.tran.covariance=2.62344569537419e-05 tran.mean=67.5393048103034 cont.tran.mean=67.3143496176184 weightedLogRatios: wLogRatio Lung -0.270171007110075 cerebhem -1.41716975843613 cortex -0.305983473698693 heart -0.0982023711683563 kidney -0.510637675030004 liver -0.528982917162246 stomach -0.0620624451019631 testicle -0.257838326783123 cont.weightedLogRatios: wLogRatio Lung -0.257913492360371 cerebhem 0.872439646766009 cortex 0.394278288960289 heart -0.000961906772614924 kidney -0.350781832755769 liver -0.262631360367034 stomach -0.355117468538221 testicle -0.3186525306454 varWeightedLogRatios=0.186688812224148 cont.varWeightedLogRatios=0.199006239763783 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.13616583298436 0.0857793097756137 48.218688676838 2.7342164943544e-254 *** df.mm.trans1 -0.307232449813436 0.0776103516669697 -3.95865297881637 8.11704106322095e-05 *** df.mm.trans2 0.0255221151147025 0.0706062926648472 0.361470828610849 0.717830324748763 df.mm.exp2 0.527809369278062 0.0964823270014689 5.47052901481145 5.78138141176323e-08 *** df.mm.exp3 -0.0626659660621346 0.0964823270014689 -0.649507200019964 0.516172364699595 df.mm.exp4 -0.00251518056672205 0.0964823270014689 -0.0260688215644276 0.979208086432175 df.mm.exp5 0.0541465891919159 0.0964823270014689 0.561207330655401 0.5747925747287 df.mm.exp6 0.0123510008651822 0.0964823270014689 0.128013090573512 0.898166528950881 df.mm.exp7 0.117320592347126 0.0964823270014689 1.21598012810512 0.224303721818817 df.mm.exp8 0.0518242270013171 0.0964823270014689 0.537136992980364 0.591302587428709 df.mm.trans1:exp2 -0.464471510029786 0.0936016059370445 -4.96221731860226 8.2980671713603e-07 *** df.mm.trans2:exp2 -0.204229377831353 0.0799275873043039 -2.55518006634932 0.0107728255007935 * df.mm.trans1:exp3 -0.00344724152603777 0.0936016059370445 -0.036828871593895 0.97062942555493 df.mm.trans2:exp3 0.00624602284070046 0.0799275873043039 0.0781460200583851 0.937728856046396 df.mm.trans1:exp4 0.00051304524503606 0.0936016059370445 0.00548115857521856 0.995627875779003 df.mm.trans2:exp4 -0.040639961804103 0.0799275873043039 -0.508459759324108 0.611252587430558 df.mm.trans1:exp5 -0.035784695680589 0.0936016059370445 -0.382308565353648 0.70232060779804 df.mm.trans2:exp5 0.0205853575115684 0.0799275873043039 0.25755009260063 0.796811620301404 df.mm.trans1:exp6 0.0201813259069260 0.0936016059370445 0.215608756974744 0.829340415600207 df.mm.trans2:exp6 0.0804281162048461 0.0799275873043039 1.00626227961363 0.314553427799686 df.mm.trans1:exp7 -0.0452822577119794 0.0936016059370445 -0.483776504245406 0.628659367827329 df.mm.trans2:exp7 -0.0954053381307733 0.0799275873043039 -1.19364716674784 0.232923047062246 df.mm.trans1:exp8 0.0184034257802817 0.0936016059370445 0.196614423396321 0.844172612008463 df.mm.trans2:exp8 0.0144452474588470 0.0799275873043039 0.180729181826174 0.856619869771131 df.mm.trans1:probe2 0.490032840344535 0.0468008029685223 10.4706075379546 2.55909011743551e-24 *** df.mm.trans1:probe3 -0.0625472740136585 0.0468008029685223 -1.33645728377197 0.181729563604519 df.mm.trans1:probe4 0.128842513227255 0.0468008029685223 2.75299792001247 0.00602126511155651 ** df.mm.trans1:probe5 0.687820347061422 0.0468008029685222 14.6967638039040 4.35107470583247e-44 *** df.mm.trans1:probe6 0.151396641312194 0.0468008029685223 3.23491546531845 0.00126008453589125 ** df.mm.trans1:probe7 0.221221455924149 0.0468008029685223 4.72687308533873 2.63578682959876e-06 *** df.mm.trans1:probe8 0.0701932795660057 0.0468008029685223 1.49983066771775 0.134000598815104 df.mm.trans1:probe9 0.142251052832523 0.0468008029685223 3.03950026088655 0.00243659731583625 ** df.mm.trans1:probe10 0.0594569821857587 0.0468008029685223 1.27042654002644 0.204253216819036 df.mm.trans1:probe11 0.0321758045615544 0.0468008029685223 0.687505395648779 0.491937205006498 df.mm.trans1:probe12 0.0142080238221058 0.0468008029685223 0.303585043864782 0.761512539558908 df.mm.trans1:probe13 -0.0310678167086179 0.0468008029685222 -0.663830847721006 0.506964536560647 df.mm.trans1:probe14 0.0376169597781957 0.0468008029685223 0.803767401245155 0.421738493459802 df.mm.trans1:probe15 0.0356403360775306 0.0468008029685223 0.76153257672741 0.446533766466089 df.mm.trans1:probe16 0.288845561041498 0.0468008029685223 6.17180780500225 1.01013794318525e-09 *** df.mm.trans1:probe17 1.34258599441408 0.0468008029685223 28.6872427235296 7.24815026580172e-130 *** df.mm.trans1:probe18 0.789956997676709 0.0468008029685223 16.879133424442 6.6232771127299e-56 *** df.mm.trans1:probe19 0.955745022588615 0.0468008029685223 20.4215518103704 9.13887650580702e-77 *** df.mm.trans1:probe20 0.815859956603552 0.0468008029685223 17.4326059566177 4.83926781876778e-59 *** df.mm.trans1:probe21 1.11489762711496 0.0468008029685223 23.8221901420116 3.96235168396046e-98 *** df.mm.trans1:probe22 1.83687416999723 0.0468008029685223 39.2487746680905 6.9228077079598e-199 *** df.mm.trans1:probe23 0.157281158842089 0.0468008029685223 3.36065086207762 0.000809518124526908 *** df.mm.trans1:probe24 0.0469020213419227 0.0468008029685222 1.00216274864917 0.316527932642186 df.mm.trans1:probe25 0.0926754096608293 0.0468008029685223 1.98020982082641 0.0479768844945343 * df.mm.trans1:probe26 0.745374246768656 0.0468008029685223 15.9265268860875 1.23831954061258e-50 *** df.mm.trans1:probe27 0.100053651714688 0.0468008029685223 2.13786186066044 0.0327903537987514 * df.mm.trans1:probe28 -0.108564886371319 0.0468008029685223 -2.31972272878178 0.0205735058358224 * df.mm.trans1:probe29 0.292148990389060 0.0468008029685223 6.24239269111594 6.56483928062581e-10 *** df.mm.trans1:probe30 0.080223232189161 0.0468008029685223 1.71414221766918 0.0868386974466682 . df.mm.trans1:probe31 0.160811001230106 0.0468008029685223 3.43607355066676 0.000616563476234096 *** df.mm.trans1:probe32 -0.0350114099277182 0.0468008029685223 -0.748094214350692 0.454594102318181 df.mm.trans2:probe2 -0.0495478268286436 0.0468008029685223 -1.05869608395328 0.290015492279716 df.mm.trans2:probe3 -0.0179224924343723 0.0468008029685222 -0.382952669560536 0.701843128246603 df.mm.trans2:probe4 0.0216305495358495 0.0468008029685223 0.462183299513001 0.64405891888735 df.mm.trans2:probe5 0.0734684633284001 0.0468008029685222 1.56981202604182 0.116801949971318 df.mm.trans2:probe6 0.300851131651189 0.0468008029685223 6.42833269022197 2.06692204062876e-10 *** df.mm.trans3:probe2 0.113552802381126 0.0468008029685222 2.42630030210166 0.0154445158913523 * df.mm.trans3:probe3 0.715524429184513 0.0468008029685222 15.2887212141588 3.3592673850898e-47 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.30551532327439 0.238801119228601 18.0297116578955 1.75910186317209e-62 *** df.mm.trans1 -0.0332358126908643 0.216059547346306 -0.153827095812586 0.877779730798044 df.mm.trans2 0.0133239878528064 0.196560939427622 0.0677855320167136 0.945971057760845 df.mm.exp2 -0.0766237332643122 0.268597261204365 -0.285273695348711 0.77549853405714 df.mm.exp3 -0.602771299121888 0.268597261204365 -2.24414536625995 0.0250596110557196 * df.mm.exp4 0.25546810309765 0.268597261204365 0.951119538420292 0.341792952019408 df.mm.exp5 0.149043795719432 0.268597261204365 0.554896930263301 0.57909974797457 df.mm.exp6 -0.130013482046764 0.268597261204365 -0.484046194156249 0.628468035258622 df.mm.exp7 0.122320966614985 0.268597261204365 0.455406604172021 0.648923969058744 df.mm.exp8 0.269764112589243 0.268597261204365 1.00434424155945 0.315476222932166 df.mm.trans1:exp2 0.115773275489930 0.260577618516991 0.444294779224798 0.65693373704327 df.mm.trans2:exp2 -0.157379618599918 0.222510502304551 -0.70729074344775 0.479564545134849 df.mm.trans1:exp3 0.609851115778022 0.260577618516991 2.3403817996681 0.0194764568646916 * df.mm.trans2:exp3 0.453468473136515 0.222510502304551 2.03796435871531 0.041838481599738 * df.mm.trans1:exp4 -0.201862185132365 0.260577618516991 -0.774672000923219 0.43873211308459 df.mm.trans2:exp4 -0.262842515528308 0.222510502304551 -1.18125891949385 0.237804488075963 df.mm.trans1:exp5 -0.0918589297494347 0.260577618516991 -0.35252041319675 0.724528578699208 df.mm.trans2:exp5 -0.0711330672529804 0.222510502304551 -0.3196840891385 0.749280244942304 df.mm.trans1:exp6 0.114580077260641 0.260577618516991 0.439715728130235 0.660246056464784 df.mm.trans2:exp6 0.115918856015594 0.222510502304551 0.520959032562586 0.602520401658952 df.mm.trans1:exp7 -0.106282537447118 0.260577618516991 -0.407872855896054 0.683461714144901 df.mm.trans2:exp7 -0.083756853529939 0.222510502304551 -0.376417529341158 0.706693119262921 df.mm.trans1:exp8 -0.266430859969425 0.260577618516991 -1.02246256407494 0.30683021646875 df.mm.trans2:exp8 -0.252203449955550 0.222510502304551 -1.13344515132305 0.257321997131627 df.mm.trans1:probe2 -0.102678617916776 0.130288809258496 -0.788084705825039 0.430849724728707 df.mm.trans1:probe3 -0.103456778094587 0.130288809258496 -0.794057284607817 0.427366404381348 df.mm.trans1:probe4 0.0101510366809113 0.130288809258496 0.0779118079187555 0.937915111144952 df.mm.trans1:probe5 -0.147156855756416 0.130288809258495 -1.12946657962353 0.258994823429718 df.mm.trans1:probe6 -0.154604480693671 0.130288809258496 -1.18662900960997 0.235679654113305 df.mm.trans1:probe7 -0.0176768941067300 0.130288809258496 -0.135674692303455 0.89210807037991 df.mm.trans1:probe8 -0.227784380552788 0.130288809258496 -1.74830349474497 0.0807443081183955 . df.mm.trans1:probe9 -0.0345769555773563 0.130288809258496 -0.265386995046942 0.790770677660466 df.mm.trans1:probe10 -0.292711264483843 0.130288809258496 -2.24663396764259 0.0248993717989271 * df.mm.trans1:probe11 -0.0712328909027285 0.130288809258496 -0.5467306924373 0.584696052095354 df.mm.trans1:probe12 -0.203046834730372 0.130288809258496 -1.55843649109973 0.119472976882871 df.mm.trans1:probe13 -0.262561850723041 0.130288809258495 -2.015229490678 0.0441704069676810 * df.mm.trans1:probe14 -0.0230961008889462 0.130288809258496 -0.177268493129929 0.8593364321232 df.mm.trans1:probe15 -0.121431700667775 0.130288809258496 -0.932019421766704 0.351570474608937 df.mm.trans1:probe16 -0.198332665034039 0.130288809258496 -1.52225403058633 0.128288321049998 df.mm.trans1:probe17 -0.103272187126988 0.130288809258496 -0.792640501626616 0.428191208945468 df.mm.trans1:probe18 -0.135027671091913 0.130288809258496 -1.03637197899334 0.300300366978012 df.mm.trans1:probe19 -0.0911514476653795 0.130288809258496 -0.699610720092876 0.484346911466842 df.mm.trans1:probe20 0.0682009225589115 0.130288809258496 0.523459558399981 0.600780272438879 df.mm.trans1:probe21 -0.0541320139222012 0.130288809258496 -0.415477079192597 0.677889363213215 df.mm.trans1:probe22 -0.176737096837352 0.130288809258496 -1.35650251040903 0.175271393541354 df.mm.trans1:probe23 -0.134841166215864 0.130288809258496 -1.03494050627431 0.300968064339778 df.mm.trans1:probe24 0.0167315240415826 0.130288809258495 0.128418734784712 0.897845611015471 df.mm.trans1:probe25 0.0306880113141564 0.130288809258496 0.235538351212273 0.813843222051854 df.mm.trans1:probe26 -0.134289768179616 0.130288809258496 -1.03070838504006 0.302947888191158 df.mm.trans1:probe27 -0.107178528730152 0.130288809258496 -0.822622674503899 0.410935296857565 df.mm.trans1:probe28 -0.0336451166125616 0.130288809258496 -0.258234892191002 0.796283262044458 df.mm.trans1:probe29 -0.127737088080705 0.130288809258496 -0.98041488603424 0.327138548014487 df.mm.trans1:probe30 -0.0165026560779244 0.130288809258496 -0.126662114511944 0.8992354487533 df.mm.trans1:probe31 -0.102124990605577 0.130288809258496 -0.783835474334243 0.433337968774841 df.mm.trans1:probe32 -0.067890535558697 0.130288809258496 -0.521077258630869 0.602438076319297 df.mm.trans2:probe2 -0.111217343770863 0.130288809258496 -0.853621614963153 0.393536392357531 df.mm.trans2:probe3 -0.237499889868704 0.130288809258495 -1.82287251852536 0.0686464329812438 . df.mm.trans2:probe4 0.0194263315057374 0.130288809258496 0.149102072666849 0.881505696209014 df.mm.trans2:probe5 -0.174206830794147 0.130288809258495 -1.33708207009949 0.181525635554813 df.mm.trans2:probe6 -0.166730308954544 0.130288809258496 -1.27969784898216 0.200973334681171 df.mm.trans3:probe2 -0.109064678732697 0.130288809258495 -0.837099359134599 0.402753639461059 df.mm.trans3:probe3 -0.0160005653851779 0.130288809258495 -0.122808439774996 0.90228555444074