chr14.7354_chr14_22607308_22614426_-_2.R fitVsDatCorrelation=0.700617133390356 cont.fitVsDatCorrelation=0.252693423351220 fstatistic=10324.0399748319,44,508 cont.fstatistic=5609.60192400672,44,508 residuals=-0.369234900516702,-0.0783476775684182,-0.00132011866724461,0.068023884924873,1.20304935080396 cont.residuals=-0.386032728832274,-0.104919993211226,-0.0212100683004701,0.0760210370643278,1.69080074566687 predictedValues: Include Exclude Both chr14.7354_chr14_22607308_22614426_-_2.R.tl.Lung 47.9248142889725 48.3126920920618 48.226234746406 chr14.7354_chr14_22607308_22614426_-_2.R.tl.cerebhem 56.2424658880011 58.1222987175936 67.4283401066481 chr14.7354_chr14_22607308_22614426_-_2.R.tl.cortex 49.1235167167596 47.2098649535279 53.7191147726241 chr14.7354_chr14_22607308_22614426_-_2.R.tl.heart 50.4498451181822 47.5467457179581 53.7321626334457 chr14.7354_chr14_22607308_22614426_-_2.R.tl.kidney 46.5857776424722 47.4943579787212 51.6141884252486 chr14.7354_chr14_22607308_22614426_-_2.R.tl.liver 53.0647296701223 48.2876279583901 52.6195499324068 chr14.7354_chr14_22607308_22614426_-_2.R.tl.stomach 48.6181689146993 49.171942703486 51.8455554582061 chr14.7354_chr14_22607308_22614426_-_2.R.tl.testicle 50.0473208667153 51.737420169733 55.2841066170571 diffExp=-0.387877803089324,-1.87983282959246,1.91365176323161,2.90309940022412,-0.908580336249003,4.77710171173219,-0.553773788786692,-1.69009930301775 diffExpScore=2.90199458730133 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 50.5215682479347 49.0616130477821 52.5950163945504 cerebhem 49.3310666230447 48.0274828347973 49.1283130857574 cortex 48.7627358203088 51.070861537499 48.8651250282025 heart 52.9064785016401 50.4773849983417 51.1307734075229 kidney 49.8727264885136 51.5910718427481 49.6156301402112 liver 51.8277988037591 48.2835557172367 49.0649048107282 stomach 48.3868357569615 50.4904177769737 50.6582367862393 testicle 49.6995949113203 52.4634147172054 48.7041850591036 cont.diffExp=1.4599552001526,1.30358378824733,-2.30812571719018,2.42909350329843,-1.7183453542345,3.54424308652236,-2.10358202001220,-2.76381980588511 cont.diffExpScore=15.2383658842338 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=0.761809879409893 cont.tran.correlation=-0.246828430365899 tran.covariance=0.00314366409297741 cont.tran.covariance=-0.000238022183110027 tran.mean=49.9962243373373 cont.tran.mean=50.1734129766292 weightedLogRatios: wLogRatio Lung -0.0312251723784818 cerebhem -0.133025183736958 cortex 0.153952086801505 heart 0.2306258238047 kidney -0.0743835886672465 liver 0.370211245293169 stomach -0.0440538390389233 testicle -0.130510381417794 cont.weightedLogRatios: wLogRatio Lung 0.114588267880561 cerebhem 0.104047136367608 cortex -0.180832678740982 heart 0.185417718980164 kidney -0.133004601635759 liver 0.27714499186937 stomach -0.165989073500902 testicle -0.21285418872881 varWeightedLogRatios=0.034648237245481 cont.varWeightedLogRatios=0.0369112619889392 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.64619819197972 0.0691750540361633 52.7097266895312 4.26915569198356e-208 *** df.mm.trans1 0.258802952325078 0.0596089683247233 4.34167809976569 1.70735364866396e-05 *** df.mm.trans2 0.246301764176485 0.0556718014309814 4.42417449849967 1.18529036554822e-05 *** df.mm.exp2 0.0097315216616699 0.0748476548410647 0.130017723098129 0.896603870653393 df.mm.exp3 -0.106252697229047 0.0748476548410647 -1.41958619083884 0.156341521677837 df.mm.exp4 -0.0727432836024657 0.0748476548410647 -0.971884606898272 0.33157048232589 df.mm.exp5 -0.113314939770864 0.0748476548410647 -1.51394108488078 0.130662679423956 df.mm.exp6 0.0141755844595206 0.0748476548410647 0.189392499866853 0.849860848221609 df.mm.exp7 -0.040373268106384 0.0748476548410647 -0.539405919826274 0.589843131139792 df.mm.exp8 -0.0247597289270036 0.0748476548410646 -0.330801666125408 0.740930699277004 df.mm.trans1:exp2 0.150307156793541 0.0675628024917495 2.22470281353257 0.0265397315045002 * df.mm.trans2:exp2 0.175123565118044 0.0593910188990825 2.94865399456465 0.00333859211615776 ** df.mm.trans1:exp3 0.130957159012030 0.0675628024917495 1.93830264853241 0.053139956040921 . df.mm.trans2:exp3 0.0831612688630675 0.0593910188990825 1.40023307235014 0.162053982068044 df.mm.trans1:exp4 0.124089546501354 0.0675628024917496 1.83665481485181 0.0668449546214696 . df.mm.trans2:exp4 0.0567623287200744 0.0593910188990825 0.955739264492587 0.339658562194141 df.mm.trans1:exp5 0.0849768196241829 0.0675628024917496 1.25774563058659 0.209061612291410 df.mm.trans2:exp5 0.0962315619892212 0.0593910188990825 1.62030495137217 0.105787329139602 df.mm.trans1:exp6 0.0877034845355858 0.0675628024917496 1.29810311741133 0.194840947324019 df.mm.trans2:exp6 -0.0146945089148654 0.0593910188990825 -0.247419714078898 0.804683384117357 df.mm.trans1:exp7 0.0547371612415833 0.0675628024917496 0.810167121890296 0.41822347876341 df.mm.trans2:exp7 0.0580021563123074 0.0593910188990825 0.976614939219429 0.329224650430121 df.mm.trans1:exp8 0.0680952902292219 0.0675628024917495 1.00788137433372 0.313991236143026 df.mm.trans2:exp8 0.0932467406420446 0.0593910188990825 1.57004783501846 0.11702660815006 df.mm.trans1:probe2 0.00919005771818052 0.0394481778033154 0.23296532894374 0.81588216337885 df.mm.trans1:probe3 0.107105486846636 0.0394481778033154 2.71509339114859 0.00685121937793601 ** df.mm.trans1:probe4 0.132094732040629 0.0394481778033154 3.34856359396980 0.000872623978700277 *** df.mm.trans1:probe5 -0.0250000542145314 0.0394481778033154 -0.633744208393582 0.526533001876081 df.mm.trans1:probe6 -0.0209787447070810 0.0394481778033154 -0.53180516503649 0.59509342434482 df.mm.trans1:probe7 -0.189200756960343 0.0394481778033154 -4.79618495697517 2.12816241201026e-06 *** df.mm.trans1:probe8 -0.0990173381899365 0.0394481778033154 -2.51006114106529 0.0123808067097259 * df.mm.trans1:probe9 -0.110612245901758 0.0394481778033154 -2.80398872802844 0.00524065368251706 ** df.mm.trans1:probe10 -0.116295543383934 0.0394481778033154 -2.94805869015729 0.00334491814064934 ** df.mm.trans1:probe11 -0.135205560178710 0.0394481778033154 -3.42742219559116 0.000658790217404858 *** df.mm.trans1:probe12 -0.153331450125459 0.0394481778033154 -3.88690831018745 0.000114988438685634 *** df.mm.trans2:probe2 -0.0473019621471635 0.0394481778033154 -1.19909118193003 0.231051504904697 df.mm.trans2:probe3 -0.0639929701509578 0.0394481778033154 -1.62220345056292 0.105380207887981 df.mm.trans2:probe4 -0.0465656131081074 0.0394481778033154 -1.18042494485496 0.238383662547494 df.mm.trans2:probe5 0.0334333639861463 0.0394481778033154 0.847526193803972 0.397101012889901 df.mm.trans2:probe6 -0.0384350102054513 0.0394481778033154 -0.974316491805638 0.330363129290898 df.mm.trans3:probe2 -0.430102330462706 0.0394481778033154 -10.9029707939148 5.149149899744e-25 *** df.mm.trans3:probe3 -0.219086678767234 0.0394481778033154 -5.55378450836381 4.51392068010757e-08 *** df.mm.trans3:probe4 -0.404579873829184 0.0394481778033154 -10.2559838339398 1.47466194640046e-22 *** df.mm.trans3:probe5 -0.323229847700484 0.0394481778033154 -8.19378398951848 2.07126402043286e-15 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.80757788227123 0.0938003721766588 40.5923536753163 1.45489174999013e-161 *** df.mm.trans1 0.0944963140403913 0.0808288983916467 1.16909070791143 0.242915364932303 df.mm.trans2 0.0881173081072308 0.0754901570621272 1.16726884055509 0.243649420937307 df.mm.exp2 0.0230360468733573 0.101492336774636 0.226973263257390 0.82053584055904 df.mm.exp3 0.0782606821536785 0.101492336774636 0.771099421303661 0.441006502336767 df.mm.exp4 0.102808790616925 0.101492336774637 1.01297096789890 0.311556246714467 df.mm.exp5 0.0956611267207767 0.101492336774637 0.942545316827141 0.346361537634514 df.mm.exp6 0.0790178069266397 0.101492336774636 0.778559341894931 0.43660182606029 df.mm.exp7 0.0230536338152092 0.101492336774636 0.227146546703321 0.820401171863327 df.mm.exp8 0.127491998047726 0.101492336774636 1.25617363930463 0.209630404121105 df.mm.trans1:exp2 -0.0468823487842493 0.0916141824148215 -0.51173680262702 0.609057597348226 df.mm.trans2:exp2 -0.0443395581288165 0.080533362124626 -0.550573786553214 0.58216790574801 df.mm.trans1:exp3 -0.113694610354089 0.0916141824148215 -1.24101539038234 0.215172840597044 df.mm.trans2:exp3 -0.0381234892710528 0.080533362124626 -0.473387528662424 0.636140081964085 df.mm.trans1:exp4 -0.0566833314225501 0.0916141824148215 -0.618717865820083 0.536379568202943 df.mm.trans2:exp4 -0.074360293824991 0.080533362124626 -0.923347689246078 0.356264393183321 df.mm.trans1:exp5 -0.108587175861078 0.0916141824148215 -1.18526600356923 0.236466444802294 df.mm.trans2:exp5 -0.0453894128795993 0.080533362124626 -0.563610057771571 0.573268241820228 df.mm.trans1:exp6 -0.0534914842876807 0.0916141824148215 -0.583877767368764 0.559561711481213 df.mm.trans2:exp6 -0.095003682951317 0.080533362124626 -1.17968107185564 0.238679233268130 df.mm.trans1:exp7 -0.0662261847018663 0.0916141824148215 -0.722881359154629 0.470085450928648 df.mm.trans2:exp7 0.0056530200990175 0.080533362124626 0.0701947609025611 0.94406626770695 df.mm.trans1:exp8 -0.143895554777154 0.0916141824148215 -1.57066898360351 0.116882172238937 df.mm.trans2:exp8 -0.0604528512733529 0.080533362124626 -0.750655997446147 0.453207263876272 df.mm.trans1:probe2 -0.0188331271706059 0.0534911582101198 -0.352079255727219 0.724924831534521 df.mm.trans1:probe3 0.0711132382410448 0.0534911582101198 1.32943911892323 0.184299829944133 df.mm.trans1:probe4 -0.0390814674963190 0.0534911582101198 -0.7306154662571 0.465350878721305 df.mm.trans1:probe5 0.0820437796984313 0.0534911582101198 1.53378207621068 0.125705799404466 df.mm.trans1:probe6 0.000105326197311074 0.0534911582101198 0.00196903938586149 0.998429707861228 df.mm.trans1:probe7 -0.0192547571324420 0.0534911582101198 -0.359961492267693 0.719025530587183 df.mm.trans1:probe8 0.086236913251047 0.0534911582101198 1.61217135946651 0.107545709029089 df.mm.trans1:probe9 0.0456760268187395 0.0534911582101198 0.853898631981729 0.393563626616909 df.mm.trans1:probe10 0.0476794198982368 0.0534911582101198 0.891351421312402 0.373162647642366 df.mm.trans1:probe11 0.0954117924856506 0.0534911582101198 1.7836927761194 0.0750704500978092 . df.mm.trans1:probe12 -0.00555271702940319 0.0534911582101198 -0.103806259112795 0.91736406745219 df.mm.trans2:probe2 -0.0431185612763003 0.0534911582101198 -0.806087636145872 0.420569497248925 df.mm.trans2:probe3 -0.0229717834700036 0.0534911582101198 -0.429450104254008 0.667777778668751 df.mm.trans2:probe4 0.0253438433426704 0.0534911582101198 0.473795000719869 0.635849656032702 df.mm.trans2:probe5 0.00292951016712816 0.0534911582101198 0.0547662504449929 0.956346219629715 df.mm.trans2:probe6 0.00901598816794952 0.0534911582101198 0.168550999261104 0.866216912444275 df.mm.trans3:probe2 -0.067419980969236 0.0534911582101198 -1.26039486197704 0.208105582677091 df.mm.trans3:probe3 -0.0232341591518092 0.0534911582101198 -0.434355133245435 0.664215001567685 df.mm.trans3:probe4 -0.0123440842268163 0.0534911582101198 -0.230768684767065 0.817587418119808 df.mm.trans3:probe5 -0.0348524482249653 0.0534911582101198 -0.651555311030295 0.51498272975525