chr5.17826_chr5_133974135_133974501_+_1.R fitVsDatCorrelation=0.769912544448983 cont.fitVsDatCorrelation=0.300304246258405 fstatistic=6741.94403101149,39,393 cont.fstatistic=3012.13080043189,39,393 residuals=-0.496714581565333,-0.0941394365621282,-0.00773117412931865,0.080664777685824,1.32685949812773 cont.residuals=-0.516132862212513,-0.161573366869025,-0.0188856569798660,0.121861716860856,1.45288114715701 predictedValues: Include Exclude Both chr5.17826_chr5_133974135_133974501_+_1.R.tl.Lung 80.490821219315 60.693218115618 61.4115798444281 chr5.17826_chr5_133974135_133974501_+_1.R.tl.cerebhem 60.94182926934 58.3107534169307 61.8382301780049 chr5.17826_chr5_133974135_133974501_+_1.R.tl.cortex 67.0597172584736 58.112195200523 63.2437311280452 chr5.17826_chr5_133974135_133974501_+_1.R.tl.heart 68.8954598329085 59.7174436756791 64.5725551807555 chr5.17826_chr5_133974135_133974501_+_1.R.tl.kidney 88.8847542583425 68.829951443003 61.7286727329771 chr5.17826_chr5_133974135_133974501_+_1.R.tl.liver 86.1985608218305 68.602489973668 61.4420801812928 chr5.17826_chr5_133974135_133974501_+_1.R.tl.stomach 66.479385224045 56.5485032084019 60.783661439373 chr5.17826_chr5_133974135_133974501_+_1.R.tl.testicle 75.8159514531216 59.7478745250387 64.7063170841777 diffExp=19.7976031036969,2.63107585240927,8.94752205795065,9.17801615722943,20.0548028153395,17.5960708481625,9.93088201564314,16.0680769280829 diffExpScore=0.990494662495357 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=1,0,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=1,0,0,0,1,1,0,1 diffExp1.2Score=0.8 cont.predictedValues: Include Exclude Both Lung 56.6086127876821 70.7533072881019 62.5143327738779 cerebhem 62.7820247043464 69.5278398182457 65.4623217704 cortex 62.5686133905139 62.1135578823777 62.6585270072563 heart 56.169283867217 60.5992511013519 67.4438916502478 kidney 62.7069176688046 66.9674539308766 65.7352135675109 liver 63.8434071794432 71.302845753503 68.2832977921326 stomach 66.0611791471658 63.7252389659218 64.0758721844308 testicle 60.4400852296169 73.9248338723536 72.9738543538683 cont.diffExp=-14.1446945004198,-6.74581511389933,0.455055508136148,-4.42996723413484,-4.26053626207197,-7.45943857405976,2.33594018124401,-13.4847486427367 cont.diffExpScore=1.09402002993177 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=-1,0,0,0,0,0,0,-1 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.892721918148219 cont.tran.correlation=0.015866980399149 tran.covariance=0.00891032912139234 cont.tran.covariance=0.000163956032683619 tran.mean=67.833056806015 cont.tran.mean=64.3809032867201 weightedLogRatios: wLogRatio Lung 1.19897211998118 cerebhem 0.180410305151548 cortex 0.592018869786751 heart 0.594897330681723 kidney 1.11472871086558 liver 0.991497776289148 stomach 0.665939927066429 testicle 1.00253164851133 cont.weightedLogRatios: wLogRatio Lung -0.925090873750697 cerebhem -0.427696117905532 cortex 0.0301659348348231 heart -0.308684904893959 kidney -0.274202852228681 liver -0.465403452452953 stomach 0.150215290619452 testicle -0.846337756718501 varWeightedLogRatios=0.117524993670422 cont.varWeightedLogRatios=0.141387928788381 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.18276749523097 0.0881323030946046 47.460095201881 8.23811589914936e-165 *** df.mm.trans1 0.208781333492826 0.0719597241460307 2.90136372770325 0.00392443282782909 ** df.mm.trans2 -0.0520123187062676 0.0719597241460307 -0.722797638866943 0.470234133447508 df.mm.exp2 -0.32519217333174 0.0977740116407171 -3.32595715236375 0.000964070300083406 *** df.mm.exp3 -0.255413648827233 0.0977740116407171 -2.61228566304288 0.00933870264211268 ** df.mm.exp4 -0.221951736223737 0.0977740116407171 -2.27004837481074 0.0237455091840423 * df.mm.exp5 0.21985438506881 0.0977740116407171 2.24859736630929 0.0250915024738109 * df.mm.exp6 0.190510661882695 0.0977740116407171 1.94847954671995 0.052068972789032 . df.mm.exp7 -0.251707095338889 0.0977740116407171 -2.57437626947146 0.0104073431952664 * df.mm.exp8 -0.127793209589262 0.0977740116407171 -1.30702635030312 0.191967994948353 df.mm.trans1:exp2 0.0469688081830184 0.0798321462082332 0.58834455058374 0.556639004444943 df.mm.trans2:exp2 0.285146735460108 0.0798321462082332 3.57182850522814 0.000398474632539237 *** df.mm.trans1:exp3 0.0728540178061984 0.0798321462082332 0.912589993712142 0.362017692837942 df.mm.trans2:exp3 0.211957226930867 0.0798321462082332 2.65503606001021 0.00825236954370697 ** df.mm.trans1:exp4 0.0663988612458883 0.0798321462082332 0.831730880348554 0.406065940988360 df.mm.trans2:exp4 0.205743938906395 0.0798321462082332 2.57720666020596 0.0103239377343218 * df.mm.trans1:exp5 -0.120656906215776 0.0798321462082332 -1.51138246867442 0.131494677333340 df.mm.trans2:exp5 -0.0940473580308657 0.0798321462082332 -1.17806375624117 0.239484041070642 df.mm.trans1:exp6 -0.122000335958044 0.0798321462082332 -1.52821064887596 0.127264674836144 df.mm.trans2:exp6 -0.0680137947267193 0.0798321462082332 -0.851959993024776 0.394755154708136 df.mm.trans1:exp7 0.0604558425077174 0.0798321462082332 0.757286949921466 0.449331759746438 df.mm.trans2:exp7 0.18097386517806 0.0798321462082332 2.26692972409899 0.0239372039306511 * df.mm.trans1:exp8 0.0679587656287847 0.0798321462082332 0.851270683009347 0.395137395828837 df.mm.trans2:exp8 0.112094863056066 0.0798321462082332 1.40413189899316 0.161069334764074 df.mm.trans1:probe2 -0.17397394038271 0.0488870058203586 -3.55869494282385 0.000418275667492913 *** df.mm.trans1:probe3 0.153443384520670 0.0488870058203586 3.13873557903131 0.00182485810463973 ** df.mm.trans1:probe4 0.278475519361935 0.0488870058203586 5.69630957529346 2.40260490461373e-08 *** df.mm.trans1:probe5 -0.194188366901244 0.0488870058203586 -3.97218777551675 8.47094989519053e-05 *** df.mm.trans1:probe6 -0.104624671645862 0.0488870058203586 -2.14013253399725 0.0329591628940643 * df.mm.trans2:probe2 -0.145392357506831 0.0488870058203586 -2.97404913774211 0.00312021940775828 ** df.mm.trans2:probe3 -0.0495574605055172 0.0488870058203586 -1.0137143740736 0.311342749092123 df.mm.trans2:probe4 0.0482527715781089 0.0488870058203586 0.987026527159788 0.324236913861354 df.mm.trans2:probe5 -0.101665316629657 0.0488870058203586 -2.07959794067239 0.0382101771434987 * df.mm.trans2:probe6 -0.0507161883198179 0.0488870058203586 -1.03741653776427 0.300179645211628 df.mm.trans3:probe2 -0.241523004859618 0.0488870058203586 -4.94043357343512 1.15547609368431e-06 *** df.mm.trans3:probe3 -0.46736340382553 0.0488870058203586 -9.56007421569068 1.31341246513643e-19 *** df.mm.trans3:probe4 -0.438679867026388 0.0488870058203586 -8.97334290912337 1.19665221668711e-17 *** df.mm.trans3:probe5 -0.181950552408107 0.0488870058203586 -3.72185920071904 0.000226615107201570 *** df.mm.trans3:probe6 -0.00211174687105208 0.0488870058203586 -0.0431964861749144 0.965566844333141 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.19515125300586 0.131731565949546 31.846211063889 6.645361149961e-111 *** df.mm.trans1 -0.188236413818065 0.107558373198060 -1.75008609949356 0.080883857269607 . df.mm.trans2 0.0874613537226083 0.107558373198060 0.813152441061521 0.416623006860789 df.mm.exp2 0.0399567402414573 0.14614305096254 0.273408417152172 0.78468290786652 df.mm.exp3 -0.0324362899573048 0.146143050962540 -0.221948903787557 0.824468947950359 df.mm.exp4 -0.238607995128577 0.14614305096254 -1.63270161363840 0.103332677003786 df.mm.exp5 -0.00292081646099561 0.14614305096254 -0.0199860098838657 0.984064675722876 df.mm.exp6 0.0397397967641713 0.146143050962540 0.271923957399504 0.785823284792673 df.mm.exp7 0.0251295158205632 0.14614305096254 0.171951493109340 0.863564172536583 df.mm.exp8 -0.0453644211566501 0.146143050962540 -0.310411072287509 0.756412927348087 df.mm.trans1:exp2 0.0635509184120997 0.119325301437260 0.532585442036482 0.594621572219884 df.mm.trans2:exp2 -0.0574287765065904 0.119325301437260 -0.481279123663356 0.6305859864877 df.mm.trans1:exp3 0.132538915764260 0.119325301437260 1.11073606492373 0.267361075998937 df.mm.trans2:exp3 -0.0977987030969817 0.119325301437260 -0.819597368864834 0.41294244132374 df.mm.trans1:exp4 0.230816909183490 0.119325301437260 1.93435010348455 0.0537875856476156 . df.mm.trans2:exp4 0.0836912485116213 0.119325301437260 0.70137051826871 0.48348691448037 df.mm.trans1:exp5 0.105231444633784 0.119325301437260 0.881887104966698 0.378376915274873 df.mm.trans2:exp5 -0.0520717259468152 0.119325301437260 -0.436384616838314 0.662797331580887 df.mm.trans1:exp6 0.0805323825323105 0.119325301437260 0.674897792524358 0.500137548964318 df.mm.trans2:exp6 -0.0320028393014153 0.119325301437260 -0.268198269067370 0.78868742355911 df.mm.trans1:exp7 0.129290610595755 0.119325301437260 1.08351379831824 0.279244724711902 df.mm.trans2:exp7 -0.129748097162160 0.119325301437260 -1.08734774267786 0.277549574559822 df.mm.trans1:exp8 0.110855825686466 0.119325301437260 0.929021962242875 0.353447957395061 df.mm.trans2:exp8 0.0892139580944948 0.119325301437260 0.747653322639226 0.45511641583379 df.mm.trans1:probe2 0.0658756044232889 0.0730715254812699 0.901522227562835 0.367862873600463 df.mm.trans1:probe3 0.0483522432186305 0.07307152548127 0.661711150823372 0.508544142160154 df.mm.trans1:probe4 0.0619886825613312 0.07307152548127 0.84832884154335 0.396771249997854 df.mm.trans1:probe5 0.068772113285122 0.07307152548127 0.941161592455737 0.347200196135819 df.mm.trans1:probe6 0.105967002572794 0.07307152548127 1.45018188514424 0.147805400679353 df.mm.trans2:probe2 -0.0379171836396673 0.07307152548127 -0.518905050769557 0.60411902274542 df.mm.trans2:probe3 -0.174562939251522 0.07307152548127 -2.38893246174622 0.0173683748560098 * df.mm.trans2:probe4 -0.0325445132968102 0.07307152548127 -0.445378867930603 0.656291207895631 df.mm.trans2:probe5 -0.036321875156436 0.07307152548127 -0.497072901067957 0.619415601120574 df.mm.trans2:probe6 0.000386609231172798 0.07307152548127 0.00529083290141377 0.995781230406034 df.mm.trans3:probe2 -0.00271731032341702 0.07307152548127 -0.0371869932305373 0.97035479097962 df.mm.trans3:probe3 0.0428349136843765 0.07307152548127 0.586205274931015 0.558074099078646 df.mm.trans3:probe4 0.129569571996655 0.07307152548127 1.77318827194687 0.0769719519516359 . df.mm.trans3:probe5 0.0463304437449817 0.07307152548127 0.634042377517592 0.526422029995939 df.mm.trans3:probe6 0.0301003524364978 0.07307152548127 0.411929985562068 0.680615323385959