chr13.6530_chr13_12564590_12569171_-_2.R fitVsDatCorrelation=0.757610292721259 cont.fitVsDatCorrelation=0.219561902657372 fstatistic=10439.8193297745,59,853 cont.fstatistic=4664.92385509472,59,853 residuals=-0.55114000876873,-0.090252336927498,-0.00388902409935691,0.0717235848951343,1.79158233633089 cont.residuals=-0.510559152644258,-0.154036501330421,-0.0332080411425718,0.125824705762607,1.90879558140904 predictedValues: Include Exclude Both chr13.6530_chr13_12564590_12569171_-_2.R.tl.Lung 58.1384545686541 46.636175938787 56.3017026481698 chr13.6530_chr13_12564590_12569171_-_2.R.tl.cerebhem 60.3032153388605 51.8780798670996 53.0534029128062 chr13.6530_chr13_12564590_12569171_-_2.R.tl.cortex 56.3670681220661 46.0420740675926 55.627205134645 chr13.6530_chr13_12564590_12569171_-_2.R.tl.heart 60.9858036112449 47.6542881209443 58.9531208977064 chr13.6530_chr13_12564590_12569171_-_2.R.tl.kidney 61.9707043538662 47.6876521886637 58.2842935183645 chr13.6530_chr13_12564590_12569171_-_2.R.tl.liver 72.0910649216642 49.9938672263807 67.2025437769877 chr13.6530_chr13_12564590_12569171_-_2.R.tl.stomach 55.8451404374717 45.9731782786662 53.7711929906375 chr13.6530_chr13_12564590_12569171_-_2.R.tl.testicle 59.0070767169378 49.5518469086486 56.9623309822451 diffExp=11.5022786298671,8.42513547176087,10.3249940544735,13.3315154903006,14.2830521652025,22.0971976952835,9.8719621588055,9.45522980828915 diffExpScore=0.990029051900192 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=0,0,0,0,0,1,0,0 diffExp1.4Score=0.5 diffExp1.3=0,0,0,0,0,1,0,0 diffExp1.3Score=0.5 diffExp1.2=1,0,1,1,1,1,1,0 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 59.8690678474809 59.7489052487365 59.30311928291 cerebhem 56.1829800926323 51.1510938997014 56.7437876463576 cortex 57.49937633078 55.6465356031519 60.7381405495614 heart 58.3225575225886 56.672809858612 56.4948781898973 kidney 56.2926349947279 62.3889813313779 54.156729741361 liver 57.4311127341186 62.0395136307201 57.7571663701672 stomach 57.488404234965 59.0496262752242 60.4515629969077 testicle 57.9775218079848 62.3477849743707 59.4850365053037 cont.diffExp=0.120162598744393,5.03188619293093,1.85284072762807,1.64974766397663,-6.09634633665004,-4.60840089660151,-1.56122204025922,-4.3702631663859 cont.diffExpScore=2.81585496791844 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=0.529375774769937 cont.tran.correlation=0.243476843999234 tran.covariance=0.00192183367615187 cont.tran.covariance=0.000371310854839835 tran.mean=54.3828556667218 cont.tran.mean=58.1318066491983 weightedLogRatios: wLogRatio Lung 0.871354122945533 cerebhem 0.605589247522115 cortex 0.795300517517094 heart 0.983542968460574 kidney 1.04682188519109 liver 1.49886087025936 stomach 0.763570445154923 testicle 0.696864118400137 cont.weightedLogRatios: wLogRatio Lung 0.00821956801294664 cerebhem 0.37360275508352 cortex 0.132176517369149 heart 0.116259381229297 kidney -0.419729076063806 liver -0.315624530601392 stomach -0.108920962455972 testicle -0.297696117711785 varWeightedLogRatios=0.0778612697883378 cont.varWeightedLogRatios=0.0734543350962137 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.79579638324516 0.0727509426261217 52.1752192648876 1.14752574435995e-267 *** df.mm.trans1 0.238201387897877 0.0628259345039695 3.79144997648745 0.000160318916605970 *** df.mm.trans2 0.0292590551327403 0.0555064291660981 0.527129119496864 0.598240987562626 df.mm.exp2 0.202503679887111 0.0713990155415038 2.83622509850150 0.00467310935914287 ** df.mm.exp3 -0.0317107451789371 0.0713990155415038 -0.444134207431808 0.657058204106852 df.mm.exp4 0.023392076356861 0.0713990155415038 0.327624634309746 0.743275885132214 df.mm.exp5 0.0515225301040628 0.0713990155415038 0.72161401264858 0.470729570388869 df.mm.exp6 0.107640268093111 0.0713990155415038 1.50758756653361 0.132030370913809 df.mm.exp7 -0.00857630532347153 0.0713990155415038 -0.120117977235781 0.904417977165789 df.mm.exp8 0.0638076412512822 0.0713990155415038 0.893676765251633 0.37174692775304 df.mm.trans1:exp2 -0.165945568777339 0.0659955948063584 -2.51449463050147 0.0121032816129459 * df.mm.trans2:exp2 -0.0959838798265188 0.0487409769766954 -1.96926458557472 0.0492459997301844 * df.mm.trans1:exp3 0.000768521031938524 0.0659955948063584 0.0116450353117278 0.990711539042923 df.mm.trans2:exp3 0.0188898296106689 0.0487409769766954 0.387555416045532 0.698441750930457 df.mm.trans1:exp4 0.0244217194757080 0.0659955948063584 0.370050751832227 0.71143653483374 df.mm.trans2:exp4 -0.00179600592061636 0.0487409769766954 -0.036847967193499 0.97061484905522 df.mm.trans1:exp5 0.0123119192803458 0.0659955948063584 0.186556683313045 0.852052590600217 df.mm.trans2:exp5 -0.0292265773500690 0.0487409769766954 -0.599630519594287 0.548911741357156 df.mm.trans1:exp6 0.107462528756854 0.0659955948063584 1.62832881606971 0.103824438249237 df.mm.trans2:exp6 -0.0381164733200761 0.0487409769766954 -0.78202111825335 0.434419178821597 df.mm.trans1:exp7 -0.0316684974853164 0.0659955948063584 -0.479857747751753 0.631451563531385 df.mm.trans2:exp7 -0.00574209680369569 0.0487409769766954 -0.117808405983351 0.906247203098672 df.mm.trans1:exp8 -0.0489775737543772 0.0659955948063584 -0.742133984822551 0.458210457508492 df.mm.trans2:exp8 -0.00316465519416352 0.0487409769766954 -0.0649280213582227 0.948246522702335 df.mm.trans1:probe2 0.162823194640384 0.0451840949642666 3.60355108958477 0.000332079027730094 *** df.mm.trans1:probe3 0.24317380348123 0.0451840949642666 5.38184517524456 9.53231311882293e-08 *** df.mm.trans1:probe4 -0.0643295793408108 0.0451840949642666 -1.42372176297180 0.154892704958043 df.mm.trans1:probe5 0.165341479545879 0.0451840949642666 3.65928496911663 0.000268456154738618 *** df.mm.trans1:probe6 0.0597742306257366 0.0451840949642666 1.3229042359487 0.186221752367292 df.mm.trans1:probe7 0.0348821950985629 0.0451840949642666 0.772001633011553 0.440327284819145 df.mm.trans1:probe8 0.179535413406688 0.0451840949642666 3.97342059299124 7.68362867141598e-05 *** df.mm.trans1:probe9 -0.0243408573530619 0.0451840949642666 -0.538704103121058 0.590231595292739 df.mm.trans1:probe10 0.425460686239571 0.0451840949642666 9.41616041166791 4.24396924541153e-20 *** df.mm.trans1:probe11 -0.146081778894322 0.0451840949642666 -3.23303540792063 0.00127186873579614 ** df.mm.trans1:probe12 0.0113236570642723 0.0451840949642666 0.250611571908821 0.802174784654285 df.mm.trans1:probe13 0.0517534898978444 0.0451840949642666 1.14539175651904 0.252368160655113 df.mm.trans1:probe14 -0.0560559848961336 0.0451840949642666 -1.24061320560841 0.215089784312818 df.mm.trans1:probe15 -0.0471304807464995 0.0451840949642666 -1.04307679026817 0.29720825185718 df.mm.trans1:probe16 -0.243418024039192 0.0451840949642666 -5.38725018685661 9.25930776422011e-08 *** df.mm.trans1:probe17 0.092383317402181 0.0451840949642666 2.04459815949045 0.0412009976974608 * df.mm.trans1:probe18 -0.0226314921656722 0.0451840949642666 -0.50087297717416 0.616589737787911 df.mm.trans1:probe19 -0.0633763816424936 0.0451840949642666 -1.40262589507689 0.161092268863339 df.mm.trans1:probe20 0.102334234343908 0.0451840949642666 2.26482868418275 0.0237733466501785 * df.mm.trans1:probe21 0.108674521658604 0.0451840949642666 2.40514990384444 0.0163778863208823 * df.mm.trans1:probe22 -0.0475502866336390 0.0451840949642666 -1.05236780046704 0.292928855189143 df.mm.trans2:probe2 0.0482218913297175 0.0451840949642666 1.06723154171514 0.286169244517793 df.mm.trans2:probe3 -0.0084611922991992 0.0451840949642666 -0.187260413335503 0.851500990783448 df.mm.trans2:probe4 0.0415145329077566 0.0451840949642666 0.918786421208347 0.358467023567774 df.mm.trans2:probe5 0.0775205877644144 0.0451840949642666 1.71566096047117 0.0865872438169719 . df.mm.trans2:probe6 0.118341928809788 0.0451840949642666 2.61910588014163 0.00897256720945171 ** df.mm.trans3:probe2 0.0425839595385262 0.0451840949642666 0.94245463082094 0.346226766600527 df.mm.trans3:probe3 0.195143437830663 0.0451840949642666 4.31885241886533 1.75275766630519e-05 *** df.mm.trans3:probe4 -0.109878972175337 0.0451840949642666 -2.43180641910022 0.0152286043731103 * df.mm.trans3:probe5 0.145555345742295 0.0451840949642666 3.22138455705279 0.00132407103094937 ** df.mm.trans3:probe6 -0.0794938427204848 0.0451840949642666 -1.75933241073771 0.0788795336751714 . df.mm.trans3:probe7 -0.293921824972617 0.0451840949642666 -6.50498422520275 1.32274721825377e-10 *** df.mm.trans3:probe8 -0.276696167606563 0.0451840949642666 -6.12375146222106 1.39344414729505e-09 *** df.mm.trans3:probe9 -0.210024522658321 0.0451840949642666 -4.64819584910171 3.87813911572377e-06 *** df.mm.trans3:probe10 0.261412095334074 0.0451840949642666 5.78548924219483 1.01480922050662e-08 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.06124461851694 0.108740518484198 37.3480343401814 1.14426907964106e-181 *** df.mm.trans1 0.0132873192984940 0.0939056518803497 0.141496481121542 0.887511149521656 df.mm.trans2 0.0259480172740695 0.0829652189903131 0.312757774762207 0.754541144782209 df.mm.exp2 -0.174797374892228 0.106719798932979 -1.63790952231837 0.101809368773601 df.mm.exp3 -0.135426859375545 0.106719798932979 -1.26899470135428 0.204789109257721 df.mm.exp4 -0.0305154280520844 0.106719798932979 -0.285939707132023 0.77499372576607 df.mm.exp5 0.072421205356765 0.106719798932979 0.678610774016227 0.497568576224715 df.mm.exp6 0.0224613168526675 0.106719798932979 0.210470007226807 0.83335112256059 df.mm.exp7 -0.0715298943967409 0.106719798932979 -0.670258893962706 0.50287417981394 df.mm.exp8 0.00740979530079783 0.106719798932979 0.0694322457021423 0.944661835578826 df.mm.trans1:exp2 0.111251265391560 0.098643329390205 1.12781336639076 0.259715872411872 df.mm.trans2:exp2 0.0194303847277148 0.0728529269388346 0.26670698823162 0.789759233661773 df.mm.trans1:exp3 0.095040985492228 0.098643329390205 0.963481120109731 0.335579187352269 df.mm.trans2:exp3 0.0642958133997589 0.0728529269388346 0.882542625277636 0.377732076715468 df.mm.trans1:exp4 0.00434439285236014 0.098643329390205 0.044041425600863 0.964881690427604 df.mm.trans2:exp4 -0.0223408886188887 0.0728529269388346 -0.306657392607513 0.759179002960824 df.mm.trans1:exp5 -0.134017471120164 0.098643329390205 -1.35860652665147 0.174630467277265 df.mm.trans2:exp5 -0.0291833952484900 0.0728529269388346 -0.400579585127604 0.68882998625326 df.mm.trans1:exp6 -0.0640351018854836 0.098643329390205 -0.649157954028284 0.516411029031442 df.mm.trans2:exp6 0.0151593133700596 0.0728529269388346 0.208081047763351 0.835215356112516 df.mm.trans1:exp7 0.0309531811773774 0.098643329390205 0.313788893468259 0.753758099640284 df.mm.trans2:exp7 0.0597572396184824 0.0728529269388346 0.820244870444986 0.412305673408922 df.mm.trans1:exp8 -0.039514390114566 0.098643329390205 -0.400578430988053 0.688830835803994 df.mm.trans2:exp8 0.0351674820756273 0.0728529269388346 0.482718863240087 0.629419223959322 df.mm.trans1:probe2 0.0588565346778834 0.0675364708180345 0.871477795108103 0.383738534585592 df.mm.trans1:probe3 0.0126414817162576 0.0675364708180345 0.187180075641173 0.851563957646122 df.mm.trans1:probe4 0.00893201298664292 0.0675364708180345 0.132254660014864 0.894814057954623 df.mm.trans1:probe5 0.0469992576722854 0.0675364708180345 0.695909293201252 0.486675195865125 df.mm.trans1:probe6 -0.0119358396560244 0.0675364708180345 -0.176731764503708 0.859761041388414 df.mm.trans1:probe7 -0.0240283786922414 0.0675364708180345 -0.355783747672895 0.72209048879499 df.mm.trans1:probe8 0.144589151019006 0.0675364708180345 2.14090474772626 0.0325645875758255 * df.mm.trans1:probe9 -0.00039247940679558 0.0675364708180345 -0.00581136979829829 0.995364582652993 df.mm.trans1:probe10 -0.0272033714971268 0.0675364708180345 -0.402795277390518 0.687199763043752 df.mm.trans1:probe11 0.0184716701558602 0.0675364708180345 0.273506594764611 0.78453003272649 df.mm.trans1:probe12 0.0305530038487975 0.0675364708180345 0.452392662493682 0.651101157439663 df.mm.trans1:probe13 0.0319296871183716 0.0675364708180345 0.472776956385547 0.63649326000956 df.mm.trans1:probe14 0.0107092202584896 0.0675364708180345 0.158569438538530 0.874045641380676 df.mm.trans1:probe15 0.0372958753881669 0.0675364708180345 0.552233111034989 0.580933311094274 df.mm.trans1:probe16 -0.0218400469083868 0.0675364708180345 -0.323381524735444 0.746485581503614 df.mm.trans1:probe17 0.0642804032740554 0.0675364708180345 0.951788011654444 0.341474112378885 df.mm.trans1:probe18 -0.00898481932217253 0.0675364708180345 -0.133036553633082 0.894195848959072 df.mm.trans1:probe19 -0.00804391481062153 0.0675364708180345 -0.119104755004070 0.90522040715979 df.mm.trans1:probe20 0.0746274780133849 0.0675364708180345 1.10499522864403 0.269473235752769 df.mm.trans1:probe21 0.0661272941736533 0.0675364708180345 0.97913458273267 0.327791097280719 df.mm.trans1:probe22 0.0605129765070843 0.0675364708180345 0.896004422116254 0.370503183416591 df.mm.trans2:probe2 0.0248842787880497 0.0675364708180345 0.368456901680518 0.712623998165988 df.mm.trans2:probe3 -0.00324310676571622 0.0675364708180345 -0.0480200805051572 0.961711479742182 df.mm.trans2:probe4 -0.039684741571859 0.0675364708180345 -0.587604609645398 0.556953229147278 df.mm.trans2:probe5 0.0816009544808799 0.0675364708180345 1.20825020159463 0.227285891704232 df.mm.trans2:probe6 -0.0162256624373306 0.0675364708180345 -0.240250374957375 0.810193888675447 df.mm.trans3:probe2 -0.0132882020827665 0.0675364708180345 -0.196755944185614 0.844065397212093 df.mm.trans3:probe3 0.00172698185778996 0.0675364708180345 0.0255711001311132 0.979605418074217 df.mm.trans3:probe4 -0.0330051951424051 0.0675364708180345 -0.488701804264128 0.625178442917252 df.mm.trans3:probe5 0.000538721937406995 0.0675364708180345 0.00797675583106037 0.993637402293045 df.mm.trans3:probe6 -0.0366049688112433 0.0675364708180345 -0.542002985466463 0.587958001257904 df.mm.trans3:probe7 -0.0155912203030793 0.0675364708180345 -0.230856307921201 0.817481793517047 df.mm.trans3:probe8 0.014805018969948 0.0675364708180345 0.219215170568175 0.826534881139884 df.mm.trans3:probe9 -0.0784320631642271 0.0675364708180345 -1.16132901548186 0.245832995344589 df.mm.trans3:probe10 -0.0183295605997842 0.0675364708180345 -0.271402404919412 0.786147219842951