chr3.15820_chr3_55945559_55948118_+_0.R fitVsDatCorrelation=0.942821610609127 cont.fitVsDatCorrelation=0.299977725748491 fstatistic=6208.68612392741,43,485 cont.fstatistic=748.006292938095,43,485 residuals=-0.610621770745782,-0.103682006733494,-0.00622816941030896,0.100390805950064,0.752585384613168 cont.residuals=-1.24872824262025,-0.380160633947629,-0.0535627601773987,0.279661845405592,2.28624326179512 predictedValues: Include Exclude Both chr3.15820_chr3_55945559_55948118_+_0.R.tl.Lung 90.7373956033472 107.867643555898 67.3142984121019 chr3.15820_chr3_55945559_55948118_+_0.R.tl.cerebhem 107.943108090484 127.636947567189 130.573607910852 chr3.15820_chr3_55945559_55948118_+_0.R.tl.cortex 99.9664146127722 228.8949235417 317.258184592138 chr3.15820_chr3_55945559_55948118_+_0.R.tl.heart 94.6854686273546 91.2063184585759 61.9287322606953 chr3.15820_chr3_55945559_55948118_+_0.R.tl.kidney 91.8218190983343 122.308227867222 66.5164460882217 chr3.15820_chr3_55945559_55948118_+_0.R.tl.liver 95.1347265871338 107.104365460264 68.2353190402609 chr3.15820_chr3_55945559_55948118_+_0.R.tl.stomach 102.233589254399 97.1175090795987 70.089495487857 chr3.15820_chr3_55945559_55948118_+_0.R.tl.testicle 90.5676839905452 90.4711719046815 63.6932171739255 diffExp=-17.1302479525504,-19.6938394767058,-128.928508928928,3.47915016877873,-30.4864087688875,-11.9696388731300,5.11608017480062,0.0965120858636652 diffExpScore=1.08170625383968 diffExp1.5=0,0,-1,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,0,-1,0,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=0,0,-1,0,-1,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=0,0,-1,0,-1,0,0,0 diffExp1.2Score=0.666666666666667 cont.predictedValues: Include Exclude Both Lung 107.559614483080 86.3563959181072 99.0094207426119 cerebhem 95.6349604738984 84.0597069700313 90.564071037824 cortex 111.802512011575 100.548787204885 80.4702081666754 heart 95.3674712539334 86.2782765415657 86.8945706859904 kidney 86.413661914162 79.5275559458583 96.2241748275418 liver 91.6881063753652 155.513939371353 84.5960460423334 stomach 70.7074658792845 91.8904644766665 118.085659811087 testicle 83.8036260825645 88.2404666125099 106.967160904068 cont.diffExp=21.2032185649727,11.5752535038671,11.2537248066897,9.08919471236774,6.88610596830372,-63.8258329959883,-21.182998597382,-4.43684052994537 cont.diffExpScore=4.91005692046281 cont.diffExp1.5=0,0,0,0,0,-1,0,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=0,0,0,0,0,-1,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,0,0,0,-1,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=1,0,0,0,0,-1,-1,0 cont.diffExp1.2Score=1.5 tran.correlation=0.321476032116279 cont.tran.correlation=0.0374387496721916 tran.covariance=0.00682339303402933 cont.tran.covariance=0.00186976166483184 tran.mean=109.106082081219 cont.tran.mean=94.7120632196775 weightedLogRatios: wLogRatio Lung -0.794540757787553 cerebhem -0.798611814593525 cortex -4.15792432694135 heart 0.16965570924589 kidney -1.33691234725492 liver -0.546868693479737 stomach 0.236239269331804 testicle 0.00480384670269333 cont.weightedLogRatios: wLogRatio Lung 1.00301890945662 cerebhem 0.580038171732875 cortex 0.494775263259278 heart 0.451485651602072 kidney 0.366849316754350 liver -2.52683278934026 stomach -1.1502707926404 testicle -0.229793103076268 varWeightedLogRatios=2.02926661592307 cont.varWeightedLogRatios=1.36554663832147 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.42851729651025 0.102081782426978 43.3820530090969 4.54555450575987e-169 *** df.mm.trans1 0.155530272774538 0.0817218052551265 1.90316736505011 0.05761050186909 . df.mm.trans2 0.246054275422466 0.0817218052551265 3.01087665225103 0.00274079901570521 ** df.mm.exp2 -0.320644768006131 0.109431064683656 -2.93010735967025 0.00354821279696793 ** df.mm.exp3 -0.701120433111683 0.109431064683656 -6.40695980742295 3.51748832208945e-10 *** df.mm.exp4 -0.0418013792481926 0.109431064683656 -0.381988234958989 0.702637404183504 df.mm.exp5 0.149443186957865 0.109431064683656 1.36563769519996 0.172685698750061 df.mm.exp6 0.0266336403904862 0.109431064683656 0.243382813349015 0.807811762541179 df.mm.exp7 -0.026092820637636 0.109431064683656 -0.238440708888882 0.811640006249413 df.mm.exp8 -0.122451211162866 0.109431064683656 -1.11898035093462 0.263702407492405 df.mm.trans1:exp2 0.494279507319186 0.0858447898792607 5.75782767963417 1.51360730328706e-08 *** df.mm.trans2:exp2 0.488929701812987 0.0858447898792608 5.6955081665487 2.13483558999987e-08 *** df.mm.trans1:exp3 0.797985136740473 0.0858447898792607 9.29567348074153 4.97478033980015e-19 *** df.mm.trans2:exp3 1.45347852927287 0.0858447898792608 16.9314705215909 7.27672280304558e-51 *** df.mm.trans1:exp4 0.0843923492057917 0.0858447898792607 0.983080619388645 0.326057909706919 df.mm.trans2:exp4 -0.125979397654008 0.0858447898792607 -1.46752526077815 0.142881389857825 df.mm.trans1:exp5 -0.137562808838768 0.0858447898792608 -1.60245961382453 0.109705055108946 df.mm.trans2:exp5 -0.0238038233527837 0.0858447898792607 -0.27728908634133 0.781676287123142 df.mm.trans1:exp6 0.0206908490761247 0.0858447898792607 0.241026265021163 0.809636617887772 df.mm.trans2:exp6 -0.0337348560941162 0.0858447898792607 -0.392974997569028 0.694510615010877 df.mm.trans1:exp7 0.145383534314665 0.0858447898792608 1.69356270216451 0.0909904927847869 . df.mm.trans2:exp7 -0.0788904531692167 0.0858447898792607 -0.918989414269344 0.358557920310486 df.mm.trans1:exp8 0.120579099661641 0.0858447898792608 1.40461756422531 0.160775132339340 df.mm.trans2:exp8 -0.0534224842930743 0.0858447898792608 -0.622314812211809 0.534027338147977 df.mm.trans1:probe2 -0.281045776347845 0.0587739098264529 -4.78181181374039 2.30773213142275e-06 *** df.mm.trans1:probe3 -0.190227055525881 0.0587739098264529 -3.23659011434805 0.00129241450470030 ** df.mm.trans1:probe4 -0.320325783663926 0.0587739098264529 -5.45013569132599 8.02379126280109e-08 *** df.mm.trans1:probe5 -0.078381434741558 0.0587739098264529 -1.33360933402256 0.182957886657890 df.mm.trans1:probe6 -0.347267905069667 0.0587739098264529 -5.90853843304072 6.50638630912252e-09 *** df.mm.trans2:probe2 0.0342929559507285 0.0587739098264529 0.58347242938216 0.559846537096557 df.mm.trans2:probe3 0.283040189571781 0.0587739098264529 4.81574546269833 1.96318075814591e-06 *** df.mm.trans2:probe4 -0.122439865039543 0.0587739098264529 -2.08323498302363 0.0377529665891775 * df.mm.trans2:probe5 0.158554522644571 0.0587739098264529 2.69770248589467 0.00722523812765588 ** df.mm.trans2:probe6 -0.252113707224129 0.0587739098264529 -4.28955140075874 2.16170547283299e-05 *** df.mm.trans3:probe2 -0.875171670542511 0.0587739098264529 -14.8904790089125 1.43736130848466e-41 *** df.mm.trans3:probe3 -1.09026478797571 0.0587739098264529 -18.5501490575500 1.89552790007761e-58 *** df.mm.trans3:probe4 -1.10071818579131 0.0587739098264529 -18.7280068493231 2.7320862637053e-59 *** df.mm.trans3:probe5 -1.03152503888372 0.0587739098264529 -17.5507302803166 9.49923984277345e-54 *** df.mm.trans3:probe6 -0.529967727602742 0.0587739098264529 -9.01705755440852 4.49115530378137e-18 *** df.mm.trans3:probe7 0.0365777614519509 0.0587739098264529 0.622346914812328 0.53400625106788 df.mm.trans3:probe8 -1.06698791520992 0.0587739098264529 -18.1541081469739 1.39975468403396e-56 *** df.mm.trans3:probe9 -0.867003430689277 0.0587739098264529 -14.7515016994676 5.9707175381377e-41 *** df.mm.trans3:probe10 0.317769267339072 0.0587739098264529 5.40663822225505 1.00955395105418e-07 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.61776893161278 0.292172749761096 15.8049268297219 1.09241943481856e-45 *** df.mm.trans1 0.0471130524147615 0.233899565516609 0.201424283583870 0.840451278163516 df.mm.trans2 -0.152385256355459 0.233899565516609 -0.651498672171061 0.515033215225548 df.mm.exp2 -0.0553048894456997 0.313207453061266 -0.176575904899944 0.85991523045447 df.mm.exp3 0.398176938648366 0.313207453061266 1.27128819814667 0.204235483941316 df.mm.exp4 0.0093067275623851 0.313207453061266 0.0297142595791442 0.976307162576509 df.mm.exp5 -0.272744373206243 0.313207453061266 -0.870810609838495 0.384288386022589 df.mm.exp6 0.585927396700416 0.313207453061266 1.87073261179964 0.0619841208557106 . df.mm.exp7 -0.533574974864704 0.313207453061266 -1.70358326294468 0.0890995542725567 . df.mm.exp8 -0.305293053877621 0.313207453061267 -0.974731127544091 0.330179549887147 df.mm.trans1:exp2 -0.0622019092043386 0.245700140763399 -0.253161878585316 0.80025039415435 df.mm.trans2:exp2 0.0283493615105457 0.245700140763399 0.115381950626741 0.908190139372191 df.mm.trans1:exp3 -0.359488156572978 0.245700140763399 -1.46311742213918 0.144082992304375 df.mm.trans2:exp3 -0.246016755658742 0.245700140763399 -1.00128862317441 0.317186584892258 df.mm.trans1:exp4 -0.129614426624185 0.245700140763399 -0.527530941665189 0.598066171910181 df.mm.trans2:exp4 -0.0102117529638364 0.245700140763399 -0.041561852313589 0.966865088298365 df.mm.trans1:exp5 0.0538449133316565 0.245700140763399 0.219148890856792 0.826626261336818 df.mm.trans2:exp5 0.190365078936354 0.245700140763399 0.774786202176697 0.438843562038078 df.mm.trans1:exp6 -0.745579974508987 0.245700140763399 -3.03451179227022 0.00253861214453128 ** df.mm.trans2:exp6 0.00232510161673947 0.245700140763399 0.00946316762178197 0.992453488535895 df.mm.trans1:exp7 0.114080894425296 0.245700140763399 0.464309438614248 0.642634407441698 df.mm.trans2:exp7 0.595689367523795 0.245700140763399 2.42445676129027 0.0156957521392054 * df.mm.trans1:exp8 0.0557240839136868 0.245700140763399 0.226797118392159 0.82067706386487 df.mm.trans2:exp8 0.326875845257959 0.245700140763399 1.33038525839808 0.184016568199550 df.mm.trans1:probe2 0.11224706687051 0.168219386847885 0.667265937498696 0.504919624223496 df.mm.trans1:probe3 -0.0145691161390399 0.168219386847885 -0.0866078304768414 0.931018985157266 df.mm.trans1:probe4 -0.0662743534711885 0.168219386847885 -0.393975716551137 0.693772124324509 df.mm.trans1:probe5 0.0597169108859597 0.168219386847885 0.354994225130303 0.722748235657352 df.mm.trans1:probe6 0.119491702466180 0.168219386847885 0.710332528879276 0.477839361403302 df.mm.trans2:probe2 -0.112474995972731 0.168219386847885 -0.668620888949249 0.504055442869923 df.mm.trans2:probe3 -0.0271952487231488 0.168219386847885 -0.161665365881642 0.871636703819298 df.mm.trans2:probe4 0.149746342318309 0.168219386847885 0.890184806426144 0.373808009566161 df.mm.trans2:probe5 -0.17673170113551 0.168219386847885 -1.05060245698864 0.293964407090651 df.mm.trans2:probe6 0.056242744100162 0.168219386847885 0.334341630617286 0.738266307792393 df.mm.trans3:probe2 -0.0117301601892774 0.168219386847885 -0.0697313217523764 0.944436252464865 df.mm.trans3:probe3 -0.0204462207955812 0.168219386847885 -0.121544972780515 0.903309736729578 df.mm.trans3:probe4 0.266410878559401 0.168219386847885 1.58371091199082 0.113911335986592 df.mm.trans3:probe5 0.078309021367399 0.168219386847885 0.465517220308328 0.641770070324705 df.mm.trans3:probe6 0.107052526198477 0.168219386847885 0.636386377363751 0.524824831677551 df.mm.trans3:probe7 0.0138865090413396 0.168219386847885 0.0825499920166555 0.934243423538177 df.mm.trans3:probe8 0.240649418729087 0.168219386847885 1.43056887341230 0.153197757433995 df.mm.trans3:probe9 0.069682206846913 0.168219386847885 0.414234103171022 0.678885802981887 df.mm.trans3:probe10 0.0833685897568141 0.168219386847885 0.495594421778515 0.620405068148797