chr10.1928_chr10_81743640_81744920_+_1.R fitVsDatCorrelation=0.792832432524433 cont.fitVsDatCorrelation=0.309491568528456 fstatistic=5798.98621661607,38,370 cont.fstatistic=2376.26319191287,38,370 residuals=-0.532048319281575,-0.107874402240915,0.000566343858258165,0.0896841993557479,1.41640366813553 cont.residuals=-0.621306584586378,-0.190388554654912,-0.0139527678008707,0.184447537946294,1.49745524963412 predictedValues: Include Exclude Both chr10.1928_chr10_81743640_81744920_+_1.R.tl.Lung 101.061267828794 73.114050771059 67.2654428176312 chr10.1928_chr10_81743640_81744920_+_1.R.tl.cerebhem 73.8409930858729 84.5276944577848 77.455375781604 chr10.1928_chr10_81743640_81744920_+_1.R.tl.cortex 97.3245911119525 99.8642608208279 62.7325462736001 chr10.1928_chr10_81743640_81744920_+_1.R.tl.heart 110.709667333531 84.1287278631665 73.7825444984433 chr10.1928_chr10_81743640_81744920_+_1.R.tl.kidney 106.645410111491 68.754103247364 70.3304304487966 chr10.1928_chr10_81743640_81744920_+_1.R.tl.liver 116.293452284877 72.6782311766312 69.4969606687449 chr10.1928_chr10_81743640_81744920_+_1.R.tl.stomach 117.754134933784 80.3181306065559 69.4149699350415 chr10.1928_chr10_81743640_81744920_+_1.R.tl.testicle 101.028913562514 86.303010478163 72.4605622002853 diffExp=27.9472170577351,-10.6867013719119,-2.53966970887541,26.580939470364,37.8913068641271,43.6152211082459,37.436004327228,14.7259030843513 diffExpScore=1.14464232664674 diffExp1.5=0,0,0,0,1,1,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,0,0,0,1,1,1,0 diffExp1.4Score=0.75 diffExp1.3=1,0,0,1,1,1,1,0 diffExp1.3Score=0.833333333333333 diffExp1.2=1,0,0,1,1,1,1,0 diffExp1.2Score=0.833333333333333 cont.predictedValues: Include Exclude Both Lung 73.2880052892699 84.0465973948278 79.9000181426775 cerebhem 79.1984950411746 73.3686509170237 80.0331108446846 cortex 74.1436196913223 78.2833158612703 80.5864975582907 heart 75.6652892566651 80.2251521015334 71.9542315946931 kidney 82.7730837244209 84.558573385181 84.0865734082164 liver 73.2151511075697 70.1114824083783 77.7667752429156 stomach 86.2705702074876 70.0407286171056 88.552461153488 testicle 67.5285324646242 73.0901538245813 72.215018490824 cont.diffExp=-10.7585921055579,5.82984412415098,-4.13969616994801,-4.55986284486833,-1.78548966076008,3.10366869919139,16.229841590382,-5.5616213599571 cont.diffExpScore=19.6708673874119 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=0,0,0,0,0,0,1,0 cont.diffExp1.2Score=0.5 tran.correlation=-0.358587669143409 cont.tran.correlation=-0.00406561527281056 tran.covariance=-0.00611921193616172 cont.tran.covariance=1.19158264493569e-05 tran.mean=92.146664979648 cont.tran.mean=76.6129625807772 weightedLogRatios: wLogRatio Lung 1.44174736653569 cerebhem -0.590603827094769 cortex -0.118263228535527 heart 1.25465151630033 kidney 1.95343985776922 liver 2.12524569616441 stomach 1.75128974629255 testicle 0.714711861237411 cont.weightedLogRatios: wLogRatio Lung -0.597603524049233 cerebhem 0.331359157938246 cortex -0.235423173183787 heart -0.25487780576326 kidney -0.0944741575442445 liver 0.185034033290985 stomach 0.90727467016728 testicle -0.336527605633256 varWeightedLogRatios=0.975166460899064 cont.varWeightedLogRatios=0.22367756457574 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.10382931475185 0.0998427188060117 51.1186932385953 8.89917676640261e-170 *** df.mm.trans1 -0.399345860939273 0.0822244538649597 -4.85677729882078 1.76414573249213e-06 *** df.mm.trans2 -0.70112130231857 0.0822244538649597 -8.52691953989804 3.88688568047802e-16 *** df.mm.exp2 -0.309809590458792 0.112398546897771 -2.7563487163279 0.00613447949286266 ** df.mm.exp3 0.343882290749386 0.112398546897771 3.05949053827319 0.00237876143497550 ** df.mm.exp4 0.139036204874273 0.112398546897771 1.23699290348237 0.216874245813745 df.mm.exp5 -0.0522596265827263 0.112398546897771 -0.464949307843434 0.642241261841751 df.mm.exp6 0.101774762293451 0.112398546897771 0.905481121442054 0.365799797984508 df.mm.exp7 0.215390799182565 0.112398546897771 1.91631302296522 0.0560954409248007 . df.mm.exp8 0.091127904625957 0.112398546897771 0.810756963867513 0.418026436753926 df.mm.trans1:exp2 -0.00400331537117565 0.0931959517602677 -0.0429558934219972 0.965759864797988 df.mm.trans2:exp2 0.454868254892219 0.0931959517602677 4.88077267628854 1.57394890526541e-06 *** df.mm.trans1:exp3 -0.381557543618738 0.0931959517602678 -4.09414289367672 5.20660914352844e-05 *** df.mm.trans2:exp3 -0.0320909799393367 0.0931959517602678 -0.344338775807407 0.730787148714324 df.mm.trans1:exp4 -0.0478519849458816 0.0931959517602677 -0.513455617353139 0.60793910745491 df.mm.trans2:exp4 0.00129133419412676 0.0931959517602677 0.0138561189594213 0.988952238536833 df.mm.trans1:exp5 0.106042088551929 0.0931959517602677 1.13784007297555 0.255923529949132 df.mm.trans2:exp5 -0.00922451634912887 0.0931959517602678 -0.0989797965995081 0.921207913592788 df.mm.trans1:exp6 0.0386150503374814 0.0931959517602677 0.414342571840595 0.678863343268281 df.mm.trans2:exp6 -0.107753417497659 0.0931959517602678 -1.15620276913785 0.248344223649709 df.mm.trans1:exp7 -0.0625188957848697 0.0931959517602677 -0.670832741165517 0.502745620194071 df.mm.trans2:exp7 -0.121415979126329 0.0931959517602678 -1.30280314577024 0.193452217902985 df.mm.trans1:exp8 -0.0914481009495347 0.0931959517602677 -0.98124542131155 0.327112899847456 df.mm.trans2:exp8 0.0747160154315428 0.0931959517602678 0.80170880837977 0.423235992108876 df.mm.trans1:probe2 -0.255522922464100 0.0544147125341225 -4.69584255000641 3.74709029266595e-06 *** df.mm.trans1:probe3 -0.328188604871829 0.0544147125341225 -6.03124760910991 3.94532936172552e-09 *** df.mm.trans1:probe4 -0.399941035787074 0.0544147125341225 -7.34986949598013 1.28243529845028e-12 *** df.mm.trans1:probe5 0.117246413087433 0.0544147125341225 2.15468221051263 0.0318315666224465 * df.mm.trans1:probe6 -0.109915445882477 0.0544147125341225 -2.01995822018816 0.0441080019941499 * df.mm.trans2:probe2 -0.0287215685496638 0.0544147125341225 -0.527827258696864 0.597935624639543 df.mm.trans2:probe3 -0.367622335987579 0.0544147125341225 -6.75593637946813 5.5247878745023e-11 *** df.mm.trans2:probe4 -0.228421954861758 0.0544147125341225 -4.19779769521926 3.37928232219063e-05 *** df.mm.trans2:probe5 -0.311903655917041 0.0544147125341225 -5.73197286894516 2.06173453427693e-08 *** df.mm.trans2:probe6 -0.280892447198811 0.0544147125341225 -5.16206801648852 3.99535286775546e-07 *** df.mm.trans3:probe2 0.303476177341261 0.0544147125341225 5.57709786945867 4.72727606039769e-08 *** df.mm.trans3:probe3 0.389560933314963 0.0544147125341225 7.15911037976497 4.40343473207173e-12 *** df.mm.trans3:probe4 0.249534191012104 0.0544147125341225 4.58578533986788 6.19807750839071e-06 *** df.mm.trans3:probe5 0.0838510663429508 0.0544147125341225 1.54096314099554 0.124180531803358 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.27363614699504 0.155783519592934 27.4331723802502 3.39625119172828e-91 *** df.mm.trans1 -0.0236393489283591 0.128293930422485 -0.184259293097594 0.853910991462397 df.mm.trans2 0.107848603933687 0.128293930422485 0.840636837444537 0.401094324768321 df.mm.exp2 -0.0599786457786999 0.175374243032050 -0.342003732941208 0.732542256052297 df.mm.exp3 -0.0679848448338697 0.175374243032051 -0.387655813410668 0.698493668821932 df.mm.exp4 0.0901341103550935 0.175374243032050 0.513952954531762 0.607591683540618 df.mm.exp5 0.076708246246896 0.175374243032050 0.437397447428339 0.66207832599528 df.mm.exp6 -0.155217576585566 0.175374243032050 -0.885064841347307 0.376696463932487 df.mm.exp7 -0.122021977885846 0.175374243032050 -0.69578049647545 0.487003094233586 df.mm.exp8 -0.120396414752026 0.175374243032051 -0.686511386566743 0.492820684048018 df.mm.trans1:exp2 0.137538985529242 0.145412640507478 0.945853022469313 0.344840830763209 df.mm.trans2:exp2 -0.0758959849846104 0.145412640507478 -0.521935264497913 0.602027712706019 df.mm.trans1:exp3 0.0795919068616871 0.145412640507478 0.54735204989001 0.584466885415306 df.mm.trans2:exp3 -0.00305203047915406 0.145412640507478 -0.0209887563316554 0.983265938776713 df.mm.trans1:exp4 -0.058211542247825 0.145412640507478 -0.400319683657979 0.689152103971852 df.mm.trans2:exp4 -0.136668403351943 0.145412640507478 -0.939866045173115 0.347899441063329 df.mm.trans1:exp5 0.0449977296197838 0.145412640507478 0.309448542181378 0.757154542260973 df.mm.trans2:exp5 -0.0706351517912252 0.145412640507478 -0.485756613350218 0.627427269397747 df.mm.trans1:exp6 0.154223001594862 0.145412640507478 1.06058868786535 0.289568682719048 df.mm.trans2:exp6 -0.0260672183107044 0.145412640507478 -0.179263771153126 0.857828717260616 df.mm.trans1:exp7 0.285113543637214 0.145412640507478 1.96072048923802 0.0506614921724806 . df.mm.trans2:exp7 -0.0602724878071349 0.145412640507478 -0.414492767594268 0.678753463216755 df.mm.trans1:exp8 0.0385496696123798 0.145412640507478 0.265105354512818 0.791075933769001 df.mm.trans2:exp8 -0.0192812980943629 0.145412640507478 -0.132597125167886 0.894584086158327 df.mm.trans1:probe2 0.132353503644579 0.084902690327108 1.55888468474503 0.119878575668333 df.mm.trans1:probe3 0.0380736860319978 0.084902690327108 0.448439099930872 0.654098821922816 df.mm.trans1:probe4 0.141551523136390 0.084902690327108 1.66722070397332 0.0963166746959788 . df.mm.trans1:probe5 0.0217068353533167 0.084902690327108 0.255667226441069 0.798349874146013 df.mm.trans1:probe6 0.154716198823405 0.084902690327108 1.82227675268385 0.0692200747092304 . df.mm.trans2:probe2 0.220531936723779 0.084902690327108 2.59746700456872 0.00976624611758646 ** df.mm.trans2:probe3 0.0814048822601468 0.084902690327108 0.958802152752934 0.338284521466073 df.mm.trans2:probe4 0.0592698448375218 0.084902690327108 0.698091481072867 0.485558468962891 df.mm.trans2:probe5 0.0714421014439067 0.084902690327108 0.841458629504658 0.400634556598421 df.mm.trans2:probe6 0.116104109724613 0.084902690327108 1.36749623925101 0.172299903776418 df.mm.trans3:probe2 0.0640618345418149 0.084902690327108 0.754532445261761 0.451009531135586 df.mm.trans3:probe3 0.00392792165238583 0.084902690327108 0.0462638066856606 0.963124945994342 df.mm.trans3:probe4 0.0663454324612508 0.084902690327108 0.781429094951398 0.435049881894303 df.mm.trans3:probe5 -0.0196817994597745 0.084902690327108 -0.231815969363817 0.816809107159173