chr7.22197_chr7_19843149_19850749_+_2.R 

fitVsDatCorrelation=0.927285553361654
cont.fitVsDatCorrelation=0.215653904863433

fstatistic=11207.1526083840,68,1060
cont.fstatistic=1633.89541642792,68,1060

residuals=-1.18938558377107,-0.0880796861460947,-0.00321513034762365,0.080641642520894,0.800436411276855
cont.residuals=-0.698280492694298,-0.264804435525701,-0.111410110526518,0.133596864223692,2.12146482791

predictedValues:
Include	Exclude	Both
chr7.22197_chr7_19843149_19850749_+_2.R.tl.Lung	54.7572167587541	50.4796838883815	79.7343885611068
chr7.22197_chr7_19843149_19850749_+_2.R.tl.cerebhem	59.494378018529	53.883809680536	70.718546834549
chr7.22197_chr7_19843149_19850749_+_2.R.tl.cortex	54.9551004938627	50.8707356833613	73.9998183870338
chr7.22197_chr7_19843149_19850749_+_2.R.tl.heart	56.1975328938454	54.7308304035764	87.322150477387
chr7.22197_chr7_19843149_19850749_+_2.R.tl.kidney	55.2772358810891	47.1573932502874	74.141815749669
chr7.22197_chr7_19843149_19850749_+_2.R.tl.liver	56.4533760278209	47.4821693005709	72.8039285269407
chr7.22197_chr7_19843149_19850749_+_2.R.tl.stomach	57.6909593153936	53.7409075718686	71.9376962601592
chr7.22197_chr7_19843149_19850749_+_2.R.tl.testicle	58.7401157881588	52.1175961259418	79.151873827099


diffExp=4.2775328703726,5.61056833799302,4.0843648105014,1.46670249026904,8.11984263080167,8.97120672725,3.95005174352501,6.622519662217
diffExpScore=0.977325697161431
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	67.0371895251101	68.4970328295273	62.2629353645975
cerebhem	68.5031468935778	60.8683000452902	63.6066924252726
cortex	62.6504196875468	63.233204288372	59.3903114744923
heart	69.7525684127488	58.6922122818003	70.4577856714363
kidney	69.0548659547722	62.7626136250185	63.7482971130914
liver	67.4954798804145	64.9049253738606	62.475324427891
stomach	63.737944323844	64.336744790296	60.1470018561609
testicle	65.3613157122797	68.1361272683376	60.4185149914914
cont.diffExp=-1.45984330441713,7.63484684828764,-0.582784600825164,11.0603561309485,6.29225232975367,2.59055450655396,-0.598800466452019,-2.7748115560579
cont.diffExpScore=1.42451332100864

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=0.525437500878128
cont.tran.correlation=-0.433261643119294

tran.covariance=0.000921237050538735
cont.tran.covariance=-0.000878055945473331

tran.mean=54.0018150676236
cont.tran.mean=65.3140056807998

weightedLogRatios:
wLogRatio
Lung	0.322281541612028
cerebhem	0.399808180656835
cortex	0.306435831895018
heart	0.106196593259576
kidney	0.624825432459578
liver	0.683051165624638
stomach	0.285096750652951
testicle	0.480073547030186

cont.weightedLogRatios:
wLogRatio
Lung	-0.0908252543649396
cerebhem	0.492496669271957
cortex	-0.0383533222629414
heart	0.717975915721534
kidney	0.40004587892309
liver	0.164082058318503
stomach	-0.0388945240401883
testicle	-0.174653276564212

varWeightedLogRatios=0.0359123304667022
cont.varWeightedLogRatios=0.104350831598369

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.86901085814951	0.0720924684861953	53.6673377870307	1.75992577776710e-304	***
df.mm.trans1	0.136269057223177	0.0615279985201223	2.21474874042281	0.0269893715331838	*  
df.mm.trans2	0.0356970359652819	0.0536382287087789	0.665514817036443	0.505866053362834	   
df.mm.exp2	0.268224845578054	0.0673523813395429	3.98241072169156	7.28747303700445e-05	***
df.mm.exp3	0.085962517692873	0.0673523813395429	1.27630999800157	0.202125521145182	   
df.mm.exp4	0.0159167148268478	0.0673523813395428	0.236320001019815	0.813230023576505	   
df.mm.exp5	0.0140931260924744	0.0673523813395429	0.209244659389650	0.834297455677108	   
df.mm.exp6	0.0602202735597312	0.0673523813395429	0.894107563267041	0.371467303067014	   
df.mm.exp7	0.217695392221989	0.0673523813395429	3.23218552770278	0.00126632447655495	** 
df.mm.exp8	0.109477904551649	0.0673523813395428	1.62544964816818	0.104364040170246	   
df.mm.trans1:exp2	-0.185252197529529	0.0612985583231648	-3.02212976287114	0.00257030573209772	** 
df.mm.trans2:exp2	-0.202965745867089	0.0409955265877679	-4.9509242290755	8.58846960038911e-07	***
df.mm.trans1:exp3	-0.082355193471694	0.0612985583231648	-1.34350946783314	0.179394597758522	   
df.mm.trans2:exp3	-0.0782456530321277	0.0409955265877679	-1.90863880878833	0.0565785718660447	.  
df.mm.trans1:exp4	0.0100469694678708	0.0612985583231648	0.163902214712838	0.869839369002465	   
df.mm.trans2:exp4	0.064939506847741	0.0409955265877679	1.58406324428376	0.113477607637378	   
df.mm.trans1:exp5	-0.00464112298960235	0.0612985583231648	-0.0757134118087156	0.9396613922857	   
df.mm.trans2:exp5	-0.0821732826393169	0.040995526587768	-2.00444510606275	0.0452763969775503	*  
df.mm.trans1:exp6	-0.0297143520775424	0.0612985583231648	-0.484747975978308	0.627955282737995	   
df.mm.trans2:exp6	-0.121436972236196	0.040995526587768	-2.96220057025515	0.00312262862109021	** 
df.mm.trans1:exp7	-0.165504088248134	0.0612985583231648	-2.69996705918596	0.00704505579262751	** 
df.mm.trans2:exp7	-0.155091857074531	0.040995526587768	-3.78314099082232	0.000163525529421881	***
df.mm.trans1:exp8	-0.039264180540644	0.0612985583231648	-0.640540032501973	0.521960012063506	   
df.mm.trans2:exp8	-0.0775462313680375	0.0409955265877679	-1.89157788233352	0.0588196488662381	.  
df.mm.trans1:probe2	0.114770162676572	0.0462793966460682	2.47994077265748	0.0132948750091155	*  
df.mm.trans1:probe3	0.0333733001956778	0.0462793966460682	0.7211265188029	0.470990690259329	   
df.mm.trans1:probe4	-0.149526160107876	0.0462793966460682	-3.23094445788501	0.00127178119517149	** 
df.mm.trans1:probe5	-0.0387476788214228	0.0462793966460682	-0.837255487960531	0.402637697476851	   
df.mm.trans1:probe6	-0.0174701244438499	0.0462793966460682	-0.377492484991896	0.70588321610467	   
df.mm.trans1:probe7	1.19241527349094	0.0462793966460682	25.7655751783067	4.58299094058661e-114	***
df.mm.trans1:probe8	0.48163340006485	0.0462793966460682	10.4070803633904	3.22527380001926e-24	***
df.mm.trans1:probe9	0.197245658243004	0.0462793966460682	4.26206200896445	2.20580458160753e-05	***
df.mm.trans1:probe10	0.0577615545493092	0.0462793966460682	1.24810517714942	0.212268163329203	   
df.mm.trans1:probe11	-0.171014130962022	0.0462793966460682	-3.69525411642442	0.000230896082370665	***
df.mm.trans1:probe12	-0.150415339935161	0.0462793966460682	-3.25015775563142	0.00118969274449241	** 
df.mm.trans1:probe13	-0.181916074699277	0.0462793966460682	-3.93082209110287	9.0147165023027e-05	***
df.mm.trans1:probe14	-0.198923210876037	0.0462793966460682	-4.29831037766862	1.87947672097222e-05	***
df.mm.trans1:probe15	-0.158710820771621	0.0462793966460682	-3.42940557296797	0.000628184381370598	***
df.mm.trans1:probe16	-0.112037139650324	0.0462793966460682	-2.42088591835266	0.0156498849435294	*  
df.mm.trans1:probe17	-0.173645242642245	0.0462793966460682	-3.75210688182119	0.000184859243810427	***
df.mm.trans1:probe18	-0.128201034699003	0.0462793966460682	-2.77015354541998	0.00570087328059503	** 
df.mm.trans1:probe19	-0.238648268797494	0.0462793966460682	-5.15668496334575	2.99803225150524e-07	***
df.mm.trans1:probe20	-0.166971234163787	0.0462793966460682	-3.60789565691049	0.000323091888842531	***
df.mm.trans1:probe21	-0.122647792329278	0.0462793966460682	-2.65015970859028	0.00816518277950998	** 
df.mm.trans1:probe22	-0.165525535432616	0.0462793966460682	-3.57665716125274	0.000363723109597982	***
df.mm.trans2:probe2	0.091100851756078	0.0462793966460682	1.96849696319059	0.0492711435752869	*  
df.mm.trans2:probe3	-0.0316539616691662	0.0462793966460682	-0.683975245210018	0.494140292154408	   
df.mm.trans2:probe4	0.195550326805481	0.0462793966460682	4.22542947785155	2.59005081137378e-05	***
df.mm.trans2:probe5	-0.0292698008853937	0.0462793966460682	-0.632458567021539	0.52722367082328	   
df.mm.trans2:probe6	0.195849133555634	0.0462793966460682	4.23188606051703	2.51799331039873e-05	***
df.mm.trans3:probe2	0.455057635526801	0.0462793966460682	9.83283423089878	6.79074664886357e-22	***
df.mm.trans3:probe3	0.151074898697133	0.0462793966460682	3.26440942721253	0.00113200020182146	** 
df.mm.trans3:probe4	0.64899828687731	0.0462793966460682	14.0234820224790	4.13806231782212e-41	***
df.mm.trans3:probe5	0.123092921649041	0.0462793966460682	2.65977801289029	0.00793718356379098	** 
df.mm.trans3:probe6	0.750539173701733	0.0462793966460682	16.2175660897580	5.27344910069335e-53	***
df.mm.trans3:probe7	0.614341875876598	0.0462793966460682	13.2746301896482	2.58176660482432e-37	***
df.mm.trans3:probe8	0.430464469924381	0.0462793966460682	9.30142787332454	7.69102261280861e-20	***
df.mm.trans3:probe9	0.580463015238413	0.0462793966460682	12.5425795776386	9.52955820239926e-34	***
df.mm.trans3:probe10	0.294461180890857	0.0462793966460682	6.36268409337342	2.94443334692099e-10	***
df.mm.trans3:probe11	-0.135657277392675	0.0462793966460682	-2.93126719931429	0.00344828820526255	** 
df.mm.trans3:probe12	0.895617403329033	0.0462793966460682	19.3524001658549	1.09143676839754e-71	***
df.mm.trans3:probe13	0.182079877708538	0.0462793966460682	3.93436152811225	8.8848043704e-05	***
df.mm.trans3:probe14	-0.0764672438587121	0.0462793966460682	-1.65229560885402	0.0987704562044	.  
df.mm.trans3:probe15	-0.0103339001792208	0.0462793966460682	-0.223293753335886	0.823349911795248	   
df.mm.trans3:probe16	1.65367309509044	0.0462793966460682	35.7323823328395	3.65153309315467e-184	***
df.mm.trans3:probe17	-0.0283196763825357	0.0462793966460682	-0.611928383576749	0.54071636836206	   
df.mm.trans3:probe18	-0.0591071556509585	0.0462793966460682	-1.27718077448143	0.201818112953649	   
df.mm.trans3:probe19	-0.0532222685936713	0.0462793966460682	-1.15002079652637	0.250394692309909	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.2653423610297	0.188046543760018	22.6823757339197	3.62377314448758e-93	***
df.mm.trans1	-0.0182092861567474	0.160490099855521	-0.113460494903674	0.909686965863826	   
df.mm.trans2	-0.0301507139982411	0.139910364201590	-0.215500218088192	0.829418799152122	   
df.mm.exp2	-0.117798142999429	0.175682464352473	-0.670517364573674	0.502674099368	   
df.mm.exp3	-0.100402828965807	0.175682464352473	-0.571501710975364	0.567780756905669	   
df.mm.exp4	-0.238424104440692	0.175682464352473	-1.35713091980734	0.17502851312222	   
df.mm.exp5	-0.0813532027136102	0.175682464352473	-0.463069567093451	0.643409556804966	   
df.mm.exp6	-0.0504591762899055	0.175682464352473	-0.287218058306997	0.774001496322562	   
df.mm.exp7	-0.078552262686612	0.175682464352473	-0.447126370728794	0.654875164595873	   
df.mm.exp8	-0.000529091410838136	0.175682464352473	-0.00301163472853282	0.997597633451953	   
df.mm.trans1:exp2	0.139430294327709	0.159891626298665	0.87202999653818	0.383389486121563	   
df.mm.trans2:exp2	-0.000279770485347182	0.106933043719094	-0.00261631461723022	0.997912977623094	   
df.mm.trans1:exp3	0.0327256762718607	0.159891626298665	0.204674109766897	0.837866042129135	   
df.mm.trans2:exp3	0.0204419484895531	0.106933043719094	0.191165871451792	0.848432249825987	   
df.mm.trans1:exp4	0.278130814649141	0.159891626298665	1.73949581405604	0.0822378592618872	.  
df.mm.trans2:exp4	0.0839407246845831	0.106933043719094	0.784983965340874	0.432638373771127	   
df.mm.trans1:exp5	0.111007017167521	0.159891626298665	0.694264107115708	0.487668722506668	   
df.mm.trans2:exp5	-0.00607765350330796	0.106933043719094	-0.0568360657466515	0.954686495444042	   
df.mm.trans1:exp6	0.0572722742546336	0.159891626298665	0.358194331876101	0.720269207070716	   
df.mm.trans2:exp6	-0.00340773911342387	0.106933043719094	-0.0318679707871759	0.974583340527168	   
df.mm.trans1:exp7	0.0280847872593505	0.159891626298665	0.175648893625550	0.860603335714944	   
df.mm.trans2:exp7	0.0158927613731659	0.106933043719094	0.148623482699278	0.88187901072175	   
df.mm.trans1:exp8	-0.0247878609401055	0.159891626298665	-0.155029137634786	0.876827860679318	   
df.mm.trans2:exp8	-0.00475376086737455	0.106933043719094	-0.0444554901089544	0.964549703535046	   
df.mm.trans1:probe2	-0.127181162213268	0.120715530614110	-1.05356089283844	0.292324093416438	   
df.mm.trans1:probe3	0.0377861618103508	0.120715530614110	0.313018230695943	0.754328386912927	   
df.mm.trans1:probe4	-0.150752445772015	0.120715530614110	-1.24882395003443	0.212005197499574	   
df.mm.trans1:probe5	-0.208392469203252	0.120715530614110	-1.72631034418775	0.0845829744574865	.  
df.mm.trans1:probe6	-0.0811367382153251	0.120715530614110	-0.67213172822554	0.501646309618429	   
df.mm.trans1:probe7	0.0314065058766137	0.120715530614110	0.260169554959837	0.7947835143497	   
df.mm.trans1:probe8	-0.126025452170007	0.120715530614110	-1.04398706221878	0.296729399472998	   
df.mm.trans1:probe9	0.142245574877369	0.120715530614110	1.17835355694276	0.238920141924879	   
df.mm.trans1:probe10	-0.176443294315789	0.120715530614110	-1.46164535265825	0.144134796518898	   
df.mm.trans1:probe11	-0.0196487811102210	0.120715530614110	-0.162769289173172	0.870731113439073	   
df.mm.trans1:probe12	-0.164076528284063	0.120715530614110	-1.35919982664505	0.174372373087935	   
df.mm.trans1:probe13	-0.0948398052278666	0.120715530614110	-0.785647089031482	0.432249842781012	   
df.mm.trans1:probe14	-0.00614757304581716	0.120715530614110	-0.0509261154264319	0.959393989965534	   
df.mm.trans1:probe15	-0.0409740826305827	0.120715530614110	-0.339426769879047	0.734355491090465	   
df.mm.trans1:probe16	-0.0187572422524729	0.120715530614110	-0.155383836338623	0.876548309398866	   
df.mm.trans1:probe17	-0.168525777690913	0.120715530614110	-1.39605713393777	0.16298959483423	   
df.mm.trans1:probe18	-0.115517189625083	0.120715530614110	-0.956937264305745	0.338817115833273	   
df.mm.trans1:probe19	-0.218991538499672	0.120715530614110	-1.8141123796218	0.0699430512746963	.  
df.mm.trans1:probe20	-0.143487926323001	0.120715530614110	-1.18864511958852	0.234845570070956	   
df.mm.trans1:probe21	-0.108433172547952	0.120715530614110	-0.898253704360369	0.369254291702066	   
df.mm.trans1:probe22	0.0405857171856918	0.120715530614110	0.336209574519716	0.736779374756615	   
df.mm.trans2:probe2	0.0139553611392629	0.120715530614110	0.115605349769566	0.907987218797597	   
df.mm.trans2:probe3	-0.079244875628	0.120715530614110	-0.656459655396959	0.511670897234271	   
df.mm.trans2:probe4	-0.0189209658443913	0.120715530614110	-0.156740112462213	0.87547952010676	   
df.mm.trans2:probe5	0.0246741162656231	0.120715530614110	0.204398855226827	0.838081062367964	   
df.mm.trans2:probe6	-0.150494112400591	0.120715530614110	-1.24668393234068	0.212788825646746	   
df.mm.trans3:probe2	-0.0360972615427972	0.120715530614110	-0.299027485189033	0.764977689219051	   
df.mm.trans3:probe3	-0.101342554633518	0.120715530614110	-0.839515463486453	0.401369411143873	   
df.mm.trans3:probe4	-0.0750066208631184	0.120715530614110	-0.621350214686882	0.534502816353035	   
df.mm.trans3:probe5	-0.102923264245347	0.120715530614110	-0.852609964283386	0.394068235858674	   
df.mm.trans3:probe6	-0.0762003581671395	0.120715530614110	-0.63123906078604	0.528020314047408	   
df.mm.trans3:probe7	-0.206050367193934	0.120715530614110	-1.70690851579497	0.0881319278393424	.  
df.mm.trans3:probe8	-0.0916053997715171	0.120715530614110	-0.758853473993755	0.448108915510377	   
df.mm.trans3:probe9	0.00928338343866747	0.120715530614110	0.0769029750475399	0.938715243322377	   
df.mm.trans3:probe10	-0.101388575884485	0.120715530614110	-0.83989670068711	0.401155699826689	   
df.mm.trans3:probe11	-0.154362933888508	0.120715530614110	-1.27873301060124	0.201270977482869	   
df.mm.trans3:probe12	-0.135847559478601	0.120715530614110	-1.12535279253225	0.260694305525966	   
df.mm.trans3:probe13	-0.0292016995545624	0.120715530614110	-0.241905075560750	0.808900507606463	   
df.mm.trans3:probe14	-0.0336666819575071	0.120715530614110	-0.278892714021437	0.780381559996877	   
df.mm.trans3:probe15	-0.0400996615252953	0.120715530614110	-0.332183119448659	0.739816663371948	   
df.mm.trans3:probe16	-0.146670112478051	0.120715530614110	-1.21500615315944	0.224634310899699	   
df.mm.trans3:probe17	-0.0274788885977387	0.120715530614110	-0.227633415998311	0.819975137696883	   
df.mm.trans3:probe18	-0.0881880578691364	0.120715530614110	-0.730544424735587	0.465218900334246	   
df.mm.trans3:probe19	-0.189858337593451	0.120715530614110	-1.57277474263331	0.116069400716939