chr17.10274_chr17_27407487_27415059_+_1.R fitVsDatCorrelation=0.878546233538514 cont.fitVsDatCorrelation=0.233785270116549 fstatistic=10944.3765168653,37,347 cont.fstatistic=2634.282940623,37,347 residuals=-0.312938680960275,-0.0773059268056824,-0.00464064492614506,0.0716537534225385,0.517005485898465 cont.residuals=-0.480957474118025,-0.181454924039791,-0.0524890197855605,0.122715208024595,0.95005126391897 predictedValues: Include Exclude Both chr17.10274_chr17_27407487_27415059_+_1.R.tl.Lung 48.7062418841027 64.5440882781975 71.4793275508708 chr17.10274_chr17_27407487_27415059_+_1.R.tl.cerebhem 52.5497322396523 62.3609008788477 71.0889097172146 chr17.10274_chr17_27407487_27415059_+_1.R.tl.cortex 46.6460035786906 56.6463881307265 62.5186984373847 chr17.10274_chr17_27407487_27415059_+_1.R.tl.heart 45.4831320265083 66.7441849043648 75.5866922352683 chr17.10274_chr17_27407487_27415059_+_1.R.tl.kidney 48.9793380839023 59.740632836119 72.346760668177 chr17.10274_chr17_27407487_27415059_+_1.R.tl.liver 47.8763075001012 52.5890010939126 75.4815903308261 chr17.10274_chr17_27407487_27415059_+_1.R.tl.stomach 47.6577894500782 65.388709448832 71.6813044779602 chr17.10274_chr17_27407487_27415059_+_1.R.tl.testicle 48.9156875583666 88.2014811195929 87.9746564505726 diffExp=-15.8378463940948,-9.81116863919532,-10.0003845520359,-21.2610528778565,-10.7612947522167,-4.71269359381134,-17.7309199987539,-39.2857935612263 diffExpScore=0.992331356230415 diffExp1.5=0,0,0,0,0,0,0,-1 diffExp1.5Score=0.5 diffExp1.4=0,0,0,-1,0,0,0,-1 diffExp1.4Score=0.666666666666667 diffExp1.3=-1,0,0,-1,0,0,-1,-1 diffExp1.3Score=0.8 diffExp1.2=-1,0,-1,-1,-1,0,-1,-1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 56.712644849197 58.5002849608862 57.5192092373614 cerebhem 54.5142577053273 58.5323729350072 60.4701508323268 cortex 53.7510212218584 60.6375659888027 59.3331611446434 heart 56.3421791367195 62.6646345913724 56.1327232202919 kidney 60.902263445068 58.4908735567592 58.4814645571033 liver 57.8739585168619 59.6372118892353 63.1117651635229 stomach 59.4155313834246 59.5431333912154 62.428251314114 testicle 63.8187815572847 59.7456607211261 61.9720899304351 cont.diffExp=-1.78764011168914,-4.01811522967986,-6.88654476694424,-6.32245545465289,2.41138988830883,-1.76325337237335,-0.127602007790777,4.07312083615864 cont.diffExpScore=1.77614575349493 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=0.0862732095219212 cont.tran.correlation=-0.202807709383819 tran.covariance=0.000594639418552003 cont.tran.covariance=-0.000270920432582043 tran.mean=56.4393511882497 cont.tran.mean=58.8176484906341 weightedLogRatios: wLogRatio Lung -1.13364811650720 cerebhem -0.692819126569013 cortex -0.765252662670522 heart -1.53759432699089 kidney -0.792609451688656 liver -0.367617551602769 stomach -1.27223532198440 testicle -2.46708267205058 cont.weightedLogRatios: wLogRatio Lung -0.125798494155890 cerebhem -0.286890336655742 cortex -0.487589015806059 heart -0.4344149231843 kidney 0.165196839115073 liver -0.122247996235053 stomach -0.00876497021751251 testicle 0.271920578354803 varWeightedLogRatios=0.42762557202423 cont.varWeightedLogRatios=0.072656236128366 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.81035638288942 0.068367759359932 55.7332347668328 3.31249951618722e-175 *** df.mm.trans1 0.0572821080441365 0.0569597257794495 1.00565982824312 0.315279983633602 df.mm.trans2 0.3968329867344 0.0569597257794495 6.96690479639868 1.63526151296227e-11 *** df.mm.exp2 0.0470197105635892 0.078478536460879 0.599141022297583 0.549469802671143 df.mm.exp3 -0.0397976424883339 0.078478536460879 -0.507114993258988 0.612396250834622 df.mm.exp4 -0.0908189693191483 0.078478536460879 -1.15724596067641 0.247967867982303 df.mm.exp5 -0.0838071744127478 0.078478536460879 -1.06789930332767 0.286308298167375 df.mm.exp6 -0.276508477549194 0.078478536460879 -3.52336434927060 0.000483128506099202 *** df.mm.exp7 -0.0115817117758998 0.078478536460879 -0.147578080558028 0.882761466678857 df.mm.exp8 0.108925692748493 0.078478536460879 1.38796794207282 0.166037322208798 df.mm.trans1:exp2 0.0289330994217646 0.0663264689947789 0.436222519610416 0.662946563642936 df.mm.trans2:exp2 -0.0814297495488867 0.0663264689947789 -1.22771121066760 0.220387565860553 df.mm.trans1:exp3 -0.00342229406354939 0.0663264689947789 -0.0515977122771119 0.958878931575802 df.mm.trans2:exp3 -0.0907226591840995 0.0663264689947789 -1.36781982455965 0.172253640652698 df.mm.trans1:exp4 0.0223533098683055 0.0663264689947789 0.337019446490738 0.736305988032555 df.mm.trans2:exp4 0.124337615774876 0.0663264689947789 1.87463041014083 0.0616834470888087 . df.mm.trans1:exp5 0.0893985198575074 0.0663264689947789 1.34785585924293 0.178584020126605 df.mm.trans2:exp5 0.00647105082492963 0.0663264689947789 0.0975636261511075 0.922335137250882 df.mm.trans1:exp6 0.259322043403913 0.0663264689947789 3.90978213274592 0.000111114152792028 *** df.mm.trans2:exp6 0.0716669412568862 0.0663264689947789 1.08051796429157 0.280661994308255 df.mm.trans1:exp7 -0.0101793912695335 0.0663264689947789 -0.153474041718319 0.87811367122992 df.mm.trans2:exp7 0.0245827874461938 0.0663264689947789 0.370633139661466 0.711136942868788 df.mm.trans1:exp8 -0.104634730731543 0.0663264689947789 -1.57757125198056 0.115575306531236 df.mm.trans2:exp8 0.203349533370333 0.0663264689947789 3.06588812056828 0.00234048387497203 ** df.mm.trans1:probe2 0.00456230956960392 0.0363285032281074 0.125584848375312 0.900133285025274 df.mm.trans1:probe3 0.0648143091155158 0.0363285032281074 1.78411724558387 0.0752783050594532 . df.mm.trans1:probe4 0.0699121166776221 0.0363285032281074 1.92444253039115 0.0551165780402074 . df.mm.trans1:probe5 0.00551445317499227 0.0363285032281074 0.151794119905434 0.879437533684532 df.mm.trans1:probe6 0.0368838219290182 0.0363285032281074 1.01528603304749 0.310676883058678 df.mm.trans2:probe2 -0.126961382550383 0.0363285032281074 -3.49481457447311 0.000535885076431755 *** df.mm.trans2:probe3 -0.0206267104732472 0.0363285032281074 -0.567783108038658 0.570549430389015 df.mm.trans2:probe4 -0.0772766593712124 0.0363285032281074 -2.12716331542730 0.0341114288074516 * df.mm.trans2:probe5 -0.090897244072545 0.0363285032281074 -2.50209163592013 0.0128058352000281 * df.mm.trans2:probe6 -0.0826464048501312 0.0363285032281074 -2.27497412517088 0.0235170489637262 * df.mm.trans3:probe2 0.0166825430311492 0.0363285032281074 0.459213607739333 0.646368311995313 df.mm.trans3:probe3 0.301670671429521 0.0363285032281074 8.30396643471175 2.28094621325389e-15 *** df.mm.trans3:probe4 -0.298605994202198 0.0363285032281074 -8.21960630547439 4.11749919901724e-15 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.08277498644705 0.139164975639949 29.3376617764092 5.39363696074842e-96 *** df.mm.trans1 -0.0681916378495964 0.115943522572145 -0.588145299856354 0.556817353484243 df.mm.trans2 -0.000399048472148193 0.115943522572145 -0.00344174873503509 0.997255865009816 df.mm.exp2 -0.0890174659347985 0.159745817576666 -0.55724442295384 0.577719700316819 df.mm.exp3 -0.0488009501671748 0.159745817576666 -0.305491254215492 0.76017520430726 df.mm.exp4 0.086611884112896 0.159745817576666 0.542185613537762 0.588038649995067 df.mm.exp5 0.0545213575182596 0.159745817576666 0.34130068846462 0.733083803058658 df.mm.exp6 -0.0532698069144465 0.159745817576666 -0.33346605077082 0.738983919722019 df.mm.exp7 -0.0176711329114755 0.159745817576666 -0.110620316572574 0.9119813877677 df.mm.exp8 0.0645501130563245 0.159745817576666 0.404080144541783 0.686402709587471 df.mm.trans1:exp2 0.0494825435790113 0.135009857400005 0.366510598055114 0.714207479727981 df.mm.trans2:exp2 0.0895658252646129 0.135009857400005 0.663402117367245 0.507513529186731 df.mm.trans1:exp3 -0.00483358261241311 0.135009857400005 -0.0358017014868201 0.971461062494974 df.mm.trans2:exp3 0.0846839266364256 0.135009857400005 0.627242545598176 0.530912753979523 df.mm.trans1:exp4 -0.0931656431729356 0.135009857400005 -0.690065488306578 0.490614263927214 df.mm.trans2:exp4 -0.0178462625624407 0.135009857400005 -0.13218488565295 0.894914668652807 df.mm.trans1:exp5 0.0167517840093049 0.135009857400005 0.124078229041254 0.901325177845019 df.mm.trans2:exp5 -0.0546822483798696 0.135009857400005 -0.405024117741701 0.685709357286273 df.mm.trans1:exp6 0.0735401246866236 0.135009857400005 0.544701891423679 0.586308443676094 df.mm.trans2:exp6 0.0725179213592227 0.135009857400005 0.537130567765641 0.59152167273564 df.mm.trans1:exp7 0.0642295971205804 0.135009857400005 0.475740056004075 0.634558937990649 df.mm.trans2:exp7 0.0353404884201336 0.135009857400005 0.261762282404517 0.793660028439101 df.mm.trans1:exp8 0.0535002166649214 0.135009857400005 0.396268966542287 0.692150179669539 df.mm.trans2:exp8 -0.0434851741483628 0.135009857400005 -0.322088882884498 0.747579312967795 df.mm.trans1:probe2 0.100953422770489 0.0739479443835383 1.36519579566518 0.173075938414033 df.mm.trans1:probe3 0.00646763765093989 0.0739479443835383 0.0874620343385727 0.930354711910651 df.mm.trans1:probe4 0.0656474523952945 0.0739479443835383 0.887752228172937 0.375288958220042 df.mm.trans1:probe5 0.0770340700344227 0.0739479443835383 1.04173375847850 0.29826037933529 df.mm.trans1:probe6 -0.0159640779926562 0.0739479443835383 -0.21588264725598 0.82920606727977 df.mm.trans2:probe2 -0.0574813907944989 0.0739479443835383 -0.7773223620168 0.437498212111928 df.mm.trans2:probe3 0.0452434935385389 0.0739479443835383 0.611828955026512 0.541051585560747 df.mm.trans2:probe4 -0.0444075601519811 0.0739479443835383 -0.600524605818073 0.548548677781506 df.mm.trans2:probe5 0.00896194932427624 0.0739479443835383 0.121192676807812 0.903608571787201 df.mm.trans2:probe6 -0.0857596181433428 0.0739479443835383 -1.15972957542325 0.246956280736790 df.mm.trans3:probe2 0.0104309524517901 0.0739479443835383 0.141058044800934 0.887905938776663 df.mm.trans3:probe3 0.0695208361623043 0.0739479443835383 0.94013209889551 0.347803779729107 df.mm.trans3:probe4 0.0717868737100806 0.0739479443835383 0.970775784351096 0.332336123072897