chr1.958_chr1_86982448_86989004_+_2.R 

fitVsDatCorrelation=0.955574807168097
cont.fitVsDatCorrelation=0.271465535164567

fstatistic=8453.41434541883,58,830
cont.fstatistic=779.863884943525,58,830

residuals=-0.953927830175368,-0.0997783913457672,-0.0071836334733376,0.0938179515320497,0.778677427950392
cont.residuals=-1.08964918399842,-0.41413353860657,-0.187145978147442,0.249637193393627,1.81530606372376

predictedValues:
Include	Exclude	Both
chr1.958_chr1_86982448_86989004_+_2.R.tl.Lung	101.165283507594	43.1344080258358	59.4834556113147
chr1.958_chr1_86982448_86989004_+_2.R.tl.cerebhem	79.3091841141895	43.1424566180847	60.6755648196551
chr1.958_chr1_86982448_86989004_+_2.R.tl.cortex	88.5114025437372	43.4041883497181	65.4750635366848
chr1.958_chr1_86982448_86989004_+_2.R.tl.heart	86.6267687084655	42.150008344326	58.7622515711817
chr1.958_chr1_86982448_86989004_+_2.R.tl.kidney	102.194580907601	44.1378289649134	58.2742067473635
chr1.958_chr1_86982448_86989004_+_2.R.tl.liver	93.661324412485	42.6247158464471	59.8205753360992
chr1.958_chr1_86982448_86989004_+_2.R.tl.stomach	84.337080433749	42.0365922790458	61.8790061181387
chr1.958_chr1_86982448_86989004_+_2.R.tl.testicle	89.57994653996	41.7782385211835	60.7819978233817


diffExp=58.0308754817586,36.1667274961048,45.1072141940191,44.4767603641395,58.0567519426873,51.0366085660379,42.3004881547031,47.8017080187764
diffExpScore=0.997395678255592
diffExp1.5=1,1,1,1,1,1,1,1
diffExp1.5Score=0.888888888888889
diffExp1.4=1,1,1,1,1,1,1,1
diffExp1.4Score=0.888888888888889
diffExp1.3=1,1,1,1,1,1,1,1
diffExp1.3Score=0.888888888888889
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	79.7189593745804	70.5054514546436	84.1605779666522
cerebhem	69.4103034614011	86.7724033824533	73.9565960555241
cortex	73.3723045007283	87.9359251350584	75.9014364868972
heart	74.387854605808	61.6547100596506	80.9466773632386
kidney	72.5430666379375	60.1726179886812	62.0779224894903
liver	73.2017089386193	53.228410701638	64.9129558612783
stomach	77.4429240322354	52.343977419028	86.9761589429874
testicle	66.3418206194019	58.7419658380402	84.7169640008003
cont.diffExp=9.21350791993683,-17.3620999210521,-14.5636206343301,12.7331445461575,12.3704486492563,19.9732982369813,25.0989466132074,7.59985478136162
cont.diffExpScore=2.12107633875131

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,0,0,0,1,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,0,0,0,0,1,1,0
cont.diffExp1.3Score=0.666666666666667
cont.diffExp1.2=0,-1,0,1,1,1,1,0
cont.diffExp1.2Score=1.25

tran.correlation=0.489729433419596
cont.tran.correlation=-0.13385315866877

tran.covariance=0.000755353291966218
cont.tran.covariance=-0.00144464263612105

tran.mean=66.7371255073335
cont.tran.mean=69.8609002593691

weightedLogRatios:
wLogRatio
Lung	3.57216003611708
cerebhem	2.4773536507905
cortex	2.94068745549891
heart	2.95455765534439
kidney	3.53211718877066
liver	3.26399004019471
stomach	2.84547897563938
testicle	3.13778974026360

cont.weightedLogRatios:
wLogRatio
Lung	0.530214882701981
cerebhem	-0.97152296869036
cortex	-0.794151453722998
heart	0.79141605542919
kidney	0.783505680674996
liver	1.31717175595916
stomach	1.62701792055001
testicle	0.502966066289677

varWeightedLogRatios=0.133752158658505
cont.varWeightedLogRatios=0.848382277367624

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.17965487608913	0.0864709029479634	48.3359689051052	1.55828748047574e-243	***
df.mm.trans1	0.381187594269563	0.0748620389544863	5.09186764871996	4.38940613052576e-07	***
df.mm.trans2	-0.420180117438714	0.0663233373878523	-6.33532831711321	3.87941359418163e-10	***
df.mm.exp2	-0.263057980573888	0.0857207797368315	-3.06877727175947	0.00221925335062917	** 
df.mm.exp3	-0.223360473969567	0.0857207797368315	-2.60567478101924	0.00933360286979899	** 
df.mm.exp4	-0.166034352357929	0.0857207797368314	-1.93692069609803	0.0530940933228933	.  
df.mm.exp5	0.0536578523862538	0.0857207797368315	0.625960852794235	0.531512709876703	   
df.mm.exp6	-0.0946084988250682	0.0857207797368315	-1.10368220069303	0.27005089535013	   
df.mm.exp7	-0.247197290734943	0.0857207797368314	-2.88374990864357	0.00403132688714795	** 
df.mm.exp8	-0.175165019679640	0.0857207797368315	-2.04343707812047	0.0413244751453097	*  
df.mm.trans1:exp2	0.0196562676607100	0.0794652896246188	0.247356647834080	0.804693395168884	   
df.mm.trans2:exp2	0.263244556484023	0.0596591378215915	4.41247671515545	1.15663803003412e-05	***
df.mm.trans1:exp3	0.0897362103312163	0.0794652896246188	1.12925040297614	0.259118478513654	   
df.mm.trans2:exp3	0.22959540749387	0.0596591378215915	3.84845332797914	0.000127988637886555	***
df.mm.trans1:exp4	0.0108875779956027	0.0794652896246188	0.137010486553738	0.891055733133354	   
df.mm.trans2:exp4	0.142948226093627	0.0596591378215915	2.39608266752209	0.0167918159413627	*  
df.mm.trans1:exp5	-0.0435348500648537	0.0794652896246188	-0.547847371733059	0.58394400441821	   
df.mm.trans2:exp5	-0.030661646654968	0.0596591378215915	-0.513947196935037	0.60742570543829	   
df.mm.trans1:exp6	0.017538193467115	0.0794652896246188	0.220702567749550	0.825378309456507	   
df.mm.trans2:exp6	0.0827217593679678	0.0596591378215915	1.38657316194116	0.16594426247652	   
df.mm.trans1:exp7	0.0652632721731256	0.0794652896246187	0.821280240485108	0.411722490793139	   
df.mm.trans2:exp7	0.221416765764551	0.0596591378215915	3.71136382202991	0.000219894415621293	***
df.mm.trans1:exp8	0.0535408540182793	0.0794652896246188	0.67376403296581	0.500648925976001	   
df.mm.trans2:exp8	0.143219605425537	0.0596591378215915	2.40063149846098	0.0165860075438998	*  
df.mm.trans1:probe2	-0.200576626063355	0.0533069368357069	-3.7626740152325	0.000179928476522291	***
df.mm.trans1:probe3	-0.365448769175325	0.0533069368357069	-6.85555747278532	1.38612602574280e-11	***
df.mm.trans1:probe4	1.13251181145715	0.0533069368357069	21.2451113998086	2.5264131159576e-80	***
df.mm.trans1:probe5	-0.271827227692992	0.0533069368357069	-5.09928433011953	4.2258973697283e-07	***
df.mm.trans1:probe6	-0.428727512817103	0.0533069368357069	-8.04262143477593	3.02546884770093e-15	***
df.mm.trans1:probe7	0.0114271542387929	0.0533069368357069	0.214365238693261	0.830314899958569	   
df.mm.trans1:probe8	-0.256211795523169	0.0533069368357069	-4.80634999367566	1.82434998451756e-06	***
df.mm.trans1:probe9	-0.352702314476942	0.0533069368357069	-6.61644310127926	6.59245123887633e-11	***
df.mm.trans1:probe10	1.10232000004220	0.0533069368357069	20.6787346164642	6.04405359761502e-77	***
df.mm.trans1:probe11	-0.50248568519541	0.0533069368357069	-9.42627198302693	4.11903401606284e-20	***
df.mm.trans1:probe12	-0.634618250542057	0.0533069368357069	-11.9049843831388	2.77676101453419e-30	***
df.mm.trans1:probe13	-0.668083790403954	0.0533069368357069	-12.5327739701683	3.99587423988622e-33	***
df.mm.trans1:probe14	-0.495713796285634	0.0533069368357069	-9.29923619159426	1.22237296830001e-19	***
df.mm.trans1:probe15	-0.588779366866821	0.0533069368357069	-11.0450797178883	1.47634492266732e-26	***
df.mm.trans1:probe16	-0.567164040259163	0.0533069368357069	-10.6395916540313	7.17069673464724e-25	***
df.mm.trans1:probe17	0.722536409125913	0.0533069368357069	13.5542661427496	5.92366064730895e-38	***
df.mm.trans1:probe18	0.847652121124203	0.0533069368357069	15.9013473938051	6.7222301405027e-50	***
df.mm.trans1:probe19	0.897765405817074	0.0533069368357069	16.8414367642997	5.71514984022266e-55	***
df.mm.trans1:probe20	0.73796428503089	0.0533069368357069	13.8436820578401	2.29558203333908e-39	***
df.mm.trans1:probe21	0.817527744922102	0.0533069368357069	15.3362356468116	6.33725204771762e-47	***
df.mm.trans1:probe22	0.79594280172597	0.0533069368357069	14.9313175540189	7.88189165331797e-45	***
df.mm.trans2:probe2	-0.00180883475046398	0.0533069368357069	-0.033932445903595	0.972939178320334	   
df.mm.trans2:probe3	0.00540886477739978	0.0533069368357069	0.101466433797725	0.919204707886203	   
df.mm.trans2:probe4	0.00381896535102563	0.0533069368357069	0.0716410579507835	0.94290482314235	   
df.mm.trans2:probe5	0.0260585996507002	0.0533069368357069	0.488840687489011	0.625083628966752	   
df.mm.trans2:probe6	0.0392161554083653	0.0533069368357069	0.735667020771242	0.46214119998447	   
df.mm.trans3:probe2	0.0651666711631548	0.0533069368357069	1.22248013169468	0.221873138707112	   
df.mm.trans3:probe3	-0.00205141366287749	0.0533069368357069	-0.0384830527629077	0.969311797358505	   
df.mm.trans3:probe4	-0.268939468198006	0.0533069368357069	-5.0451120278564	5.57002900780588e-07	***
df.mm.trans3:probe5	-0.244648935305179	0.0533069368357069	-4.58943900789484	5.13133413899452e-06	***
df.mm.trans3:probe6	0.0776257611935873	0.0533069368357069	1.45620374760665	0.145714459078352	   
df.mm.trans3:probe7	-0.0685566724974274	0.0533069368357069	-1.28607413156604	0.198775840170272	   
df.mm.trans3:probe8	-0.126881806392586	0.0533069368357069	-2.38021191845329	0.0175275688240501	*  
df.mm.trans3:probe9	0.0736086398245434	0.0533069368357069	1.38084542451589	0.167698183719058	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.14522171918297	0.282354987483000	14.6808871914563	1.50046919876704e-43	***
df.mm.trans1	0.246308764793618	0.244448356051817	1.00761064124893	0.31393507063357	   
df.mm.trans2	0.0309749149785723	0.216566780958066	0.143027083108235	0.886303505988407	   
df.mm.exp2	0.198374720014706	0.279905596732248	0.70872009109724	0.478697197265368	   
df.mm.exp3	0.241248499331059	0.279905596732248	0.861892374241562	0.388995683343112	   
df.mm.exp4	-0.164419180824218	0.279905596732248	-0.587409407827947	0.557088536334908	   
df.mm.exp5	0.0515365382414514	0.279905596732248	0.184121142424852	0.853963394179461	   
df.mm.exp6	-0.106707033193392	0.279905596732248	-0.381225078880667	0.703133803936822	   
df.mm.exp7	-0.359726816594702	0.279905596732248	-1.28517193223117	0.199090709184729	   
df.mm.exp8	-0.372811853819271	0.279905596732248	-1.33191996934558	0.183252109881372	   
df.mm.trans1:exp2	-0.33684684041446	0.259479432876914	-1.29816393029596	0.194591615284742	   
df.mm.trans2:exp2	0.00922388529165668	0.194806050805310	0.0473490697723504	0.962246410146519	   
df.mm.trans1:exp3	-0.324209399547524	0.259479432876914	-1.24946087615860	0.211848779534461	   
df.mm.trans2:exp3	-0.0203301059552684	0.194806050805310	-0.104360751995257	0.916908280237084	   
df.mm.trans1:exp4	0.0952044230374482	0.259479432876914	0.366905469084362	0.713783051093937	   
df.mm.trans2:exp4	0.0302787750840376	0.194806050805310	0.155430362449564	0.876519840603178	   
df.mm.trans1:exp5	-0.145863571904546	0.259479432876914	-0.562139242741977	0.574172927007045	   
df.mm.trans2:exp5	-0.210009172515521	0.194806050805310	-1.07804234851722	0.281328062821408	   
df.mm.trans1:exp6	0.0214183582897575	0.259479432876914	0.0825435682986001	0.934234375666556	   
df.mm.trans2:exp6	-0.174390709686811	0.194806050805310	-0.895201709422759	0.370938802766793	   
df.mm.trans1:exp7	0.330760575776524	0.259479432876913	1.27470825764223	0.202769257302688	   
df.mm.trans2:exp7	0.0618736703398982	0.194806050805310	0.317616778760814	0.75085553076914	   
df.mm.trans1:exp8	0.189124888972699	0.259479432876914	0.728862734421084	0.466291236094444	   
df.mm.trans2:exp8	0.190276213372707	0.194806050805310	0.976746936689709	0.328979043188182	   
df.mm.trans1:probe2	0.0765914855647561	0.174064095202762	0.440018864749431	0.66003800021236	   
df.mm.trans1:probe3	-0.00855526389761478	0.174064095202762	-0.0491500782378412	0.960811519470208	   
df.mm.trans1:probe4	0.0684972471186089	0.174064095202762	0.393517382426391	0.694038451273563	   
df.mm.trans1:probe5	-0.0241921979865517	0.174064095202762	-0.138984423860481	0.889496172006291	   
df.mm.trans1:probe6	-0.172161551897371	0.174064095202762	-0.98906986933075	0.322917199400466	   
df.mm.trans1:probe7	0.194431686897671	0.174064095202762	1.11701202175661	0.26431242451574	   
df.mm.trans1:probe8	0.0172204564382366	0.174064095202762	0.0989316976495181	0.921216389067921	   
df.mm.trans1:probe9	-0.103612934149348	0.174064095202762	-0.5952573621151	0.551833708182316	   
df.mm.trans1:probe10	-0.0260202659449938	0.174064095202762	-0.149486692902885	0.881205923705633	   
df.mm.trans1:probe11	-0.0293703622780414	0.174064095202762	-0.168733030461157	0.866047746475387	   
df.mm.trans1:probe12	0.154838552707263	0.174064095202762	0.889549062527205	0.373965813479339	   
df.mm.trans1:probe13	-0.162566359211741	0.174064095202762	-0.93394538961279	0.350603680085258	   
df.mm.trans1:probe14	0.136291838489529	0.174064095202762	0.782998000424885	0.433851634202243	   
df.mm.trans1:probe15	0.0252391380878847	0.174064095202762	0.144999105407031	0.884746780455807	   
df.mm.trans1:probe16	0.134897380178485	0.174064095202762	0.77498682322364	0.438568171746342	   
df.mm.trans1:probe17	-0.100773917222617	0.174064095202762	-0.578947180952102	0.562781889430486	   
df.mm.trans1:probe18	-0.00906232219741464	0.174064095202762	-0.0520631333352133	0.958490915632638	   
df.mm.trans1:probe19	-0.212008317670280	0.174064095202762	-1.21798994458517	0.223573917521821	   
df.mm.trans1:probe20	-0.122003239314120	0.174064095202762	-0.700909852614936	0.483555721455776	   
df.mm.trans1:probe21	-0.192328608507450	0.174064095202762	-1.10492981498230	0.269510195984737	   
df.mm.trans1:probe22	-0.0490667540931951	0.174064095202762	-0.281889002071557	0.778098891641951	   
df.mm.trans2:probe2	0.101603516476753	0.174064095202762	0.583713237117614	0.559571846136483	   
df.mm.trans2:probe3	0.375156050983895	0.174064095202762	2.15527533433525	0.0314272174087355	*  
df.mm.trans2:probe4	0.102297412682718	0.174064095202762	0.587699677889086	0.556893743429488	   
df.mm.trans2:probe5	0.442978966233181	0.174064095202762	2.54491867330347	0.0111102949016252	*  
df.mm.trans2:probe6	0.170365027598362	0.174064095202762	0.978748818933103	0.327989290980241	   
df.mm.trans3:probe2	0.0498889971509602	0.174064095202762	0.28661279681399	0.774480342910316	   
df.mm.trans3:probe3	-0.183967516078645	0.174064095202762	-1.05689525381066	0.290866909327156	   
df.mm.trans3:probe4	-0.0311251079716144	0.174064095202762	-0.17881406234501	0.858127340851408	   
df.mm.trans3:probe5	-0.0976048636839215	0.174064095202762	-0.560740936091528	0.575125490930331	   
df.mm.trans3:probe6	0.232604284674261	0.174064095202762	1.33631398481868	0.181812892781803	   
df.mm.trans3:probe7	-0.13589589772635	0.174064095202762	-0.78072331670727	0.435187847497299	   
df.mm.trans3:probe8	0.139314317270680	0.174064095202762	0.800362171810314	0.423730012471822	   
df.mm.trans3:probe9	0.118776743730886	0.174064095202762	0.682373602623371	0.495193131752634