chr7.22321_chr7_69955097_69957137_-_1.R 

fitVsDatCorrelation=0.883302815956454
cont.fitVsDatCorrelation=0.275900055389141

fstatistic=8521.29404991712,43,485
cont.fstatistic=2018.48415787462,43,485

residuals=-0.581323095398753,-0.0884835249923866,-0.00476988953032769,0.0862867546066632,0.771636717678872
cont.residuals=-0.757736542743379,-0.218929509760896,-0.0462862592784707,0.156420720873030,1.38722970016138

predictedValues:
Include	Exclude	Both
chr7.22321_chr7_69955097_69957137_-_1.R.tl.Lung	62.9722427834434	83.4517293917652	70.1574184323893
chr7.22321_chr7_69955097_69957137_-_1.R.tl.cerebhem	64.2048265516636	80.6628260766634	66.8710133679245
chr7.22321_chr7_69955097_69957137_-_1.R.tl.cortex	59.8597691091139	70.9649255820312	64.8818948885898
chr7.22321_chr7_69955097_69957137_-_1.R.tl.heart	59.5927875602839	71.5629576422537	68.5982699458975
chr7.22321_chr7_69955097_69957137_-_1.R.tl.kidney	62.6993986327836	81.2394379162092	74.5827368977801
chr7.22321_chr7_69955097_69957137_-_1.R.tl.liver	57.900376028353	81.4146410681797	74.0813988634623
chr7.22321_chr7_69955097_69957137_-_1.R.tl.stomach	61.3957260937935	82.8537459169999	69.5787101736256
chr7.22321_chr7_69955097_69957137_-_1.R.tl.testicle	61.2712555039771	76.1516941081187	73.66389741609


diffExp=-20.4794866083217,-16.4579995249997,-11.1051564729173,-11.9701700819698,-18.5400392834256,-23.5142650398267,-21.4580198232065,-14.8804386041416
diffExpScore=0.992826685755915
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,-1,0,0
diffExp1.4Score=0.5
diffExp1.3=-1,0,0,0,0,-1,-1,0
diffExp1.3Score=0.75
diffExp1.2=-1,-1,0,-1,-1,-1,-1,-1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	69.303088725052	70.5585149830956	64.0583905599898
cerebhem	65.7663574169172	83.1057110215549	70.1943872494009
cortex	70.6264604753728	70.2310872640604	73.4892342174177
heart	64.9199184560679	74.9860438839836	67.9076652529592
kidney	57.8446898380827	84.7608399548209	66.2328708331138
liver	69.9596807844483	73.4178740831762	80.5887942116683
stomach	75.5963528848892	67.3064342238223	68.1070625303686
testicle	64.2567798445276	72.170847019399	74.2816123575471
cont.diffExp=-1.25542625804358,-17.3393536046377,0.395373211312389,-10.0661254279157,-26.9161501167382,-3.45819329872792,8.28991866106696,-7.91406717487142
cont.diffExpScore=1.27623139026799

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

tran.correlation=0.439950381365155
cont.tran.correlation=-0.815350121178042

tran.covariance=0.000956218929564542
cont.tran.covariance=-0.00538313238558236

tran.mean=69.887396247852
cont.tran.mean=70.9256675537044

weightedLogRatios:
wLogRatio
Lung	-1.20611837215858
cerebhem	-0.975821440465113
cortex	-0.710862671572284
heart	-0.764947111085472
kidney	-1.10558893283345
liver	-1.44142287512787
stomach	-1.27903915324891
testicle	-0.91837147728599

cont.weightedLogRatios:
wLogRatio
Lung	-0.0762542874689278
cerebhem	-1.00694948045739
cortex	0.0238845344540845
heart	-0.611939158533006
kidney	-1.62334655482571
liver	-0.206118973165930
stomach	0.495660003746014
testicle	-0.490260238716785

varWeightedLogRatios=0.0646044414935945
cont.varWeightedLogRatios=0.433059088269863

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.19411828625328	0.0814481990456006	51.4943035622569	9.86421192573881e-199	***
df.mm.trans1	-0.0536360423234021	0.0652035427138692	-0.8225939893906	0.411143159616987	   
df.mm.trans2	0.177204402645714	0.0652035427138692	2.71771126644660	0.00680876805680987	** 
df.mm.exp2	0.0333697630969212	0.0873119858041477	0.382189945510734	0.702487889978788	   
df.mm.exp3	-0.134599081294312	0.0873119858041477	-1.54158767613229	0.123826001078839	   
df.mm.exp4	-0.186376033769458	0.0873119858041476	-2.13459849816639	0.0332945164413689	*  
df.mm.exp5	-0.0923772574535865	0.0873119858041477	-1.05801347435621	0.290575966462614	   
df.mm.exp6	-0.163106331957573	0.0873119858041477	-1.86808638533822	0.0623527950297217	.  
df.mm.exp7	-0.0242623111998493	0.0873119858041477	-0.277880648073597	0.78122239653911	   
df.mm.exp8	-0.167695536755643	0.0873119858041477	-1.92064737975158	0.0553621692276128	.  
df.mm.trans1:exp2	-0.0139854138583414	0.0684931568285977	-0.204187024016713	0.838293002970666	   
df.mm.trans2:exp2	-0.0673603109427716	0.0684931568285977	-0.983460451550495	0.32587121071655	   
df.mm.trans1:exp3	0.0839096879659787	0.0684931568285977	1.22508133441652	0.221139205789837	   
df.mm.trans2:exp3	-0.0274835431934969	0.0684931568285978	-0.401259694633052	0.688405664326528	   
df.mm.trans1:exp4	0.131216547864849	0.0684931568285977	1.91576142698773	0.0559831039825768	.  
df.mm.trans2:exp4	0.0326852489173638	0.0684931568285977	0.477204591389440	0.633431402195175	   
df.mm.trans1:exp5	0.0880350752988695	0.0684931568285977	1.28531198407419	0.199296699469362	   
df.mm.trans2:exp5	0.065509701754812	0.0684931568285977	0.956441559829813	0.339325689348389	   
df.mm.trans1:exp6	0.0791361723962957	0.0684931568285977	1.15538801335047	0.248500452605691	   
df.mm.trans2:exp6	0.138393080913494	0.0684931568285977	2.02053880009968	0.0438766098778438	*  
df.mm.trans1:exp7	-0.00109150222663654	0.0684931568285977	-0.0159359310794799	0.98729205805979	   
df.mm.trans2:exp7	0.0170708937099990	0.0684931568285977	0.249235025810219	0.803284502341153	   
df.mm.trans1:exp8	0.140312316052410	0.0684931568285977	2.04855963061445	0.0410429167854814	*  
df.mm.trans2:exp8	0.0761544892559935	0.0684931568285977	1.11185544340682	0.266751144652491	   
df.mm.trans1:probe2	0.0689414854912807	0.0468940587872025	1.47015394432215	0.142168476381977	   
df.mm.trans1:probe3	0.079632071087288	0.0468940587872025	1.69812707935232	0.0901251916119302	.  
df.mm.trans1:probe4	-0.0585294347334562	0.0468940587872025	-1.24812047084798	0.212589154603852	   
df.mm.trans1:probe5	-0.0116236771374079	0.0468940587872025	-0.247870997691929	0.804339126300636	   
df.mm.trans1:probe6	-0.0430317305630437	0.0468940587872025	-0.91763715225237	0.359264951719271	   
df.mm.trans2:probe2	-0.13623169759338	0.0468940587872025	-2.90509504011110	0.00383912718638817	** 
df.mm.trans2:probe3	0.191212106225276	0.0468940587872025	4.07753372539078	5.31908988422316e-05	***
df.mm.trans2:probe4	0.245398486541731	0.0468940587872025	5.23304002443698	2.48669672049894e-07	***
df.mm.trans2:probe5	0.354651059440376	0.0468940587872025	7.56281432259305	1.99258244355060e-13	***
df.mm.trans2:probe6	0.192101000300147	0.0468940587872025	4.09648909197366	4.91535155171931e-05	***
df.mm.trans3:probe2	-0.42668471084717	0.0468940587872025	-9.09890766298125	2.36426457235199e-18	***
df.mm.trans3:probe3	-0.422623430232159	0.0468940587872025	-9.0123022225471	4.66116504285738e-18	***
df.mm.trans3:probe4	-0.100944926788856	0.0468940587872025	-2.15261654460168	0.0318414310820856	*  
df.mm.trans3:probe5	-0.0352140673253655	0.0468940587872025	-0.750928118317955	0.453060097448009	   
df.mm.trans3:probe6	-0.199592216775442	0.0468940587872025	-4.25623675871519	2.49656264262547e-05	***
df.mm.trans3:probe7	0.225346091069219	0.0468940587872025	4.80542944878802	2.0623058864391e-06	***
df.mm.trans3:probe8	-0.0455818206294602	0.0468940587872025	-0.972016963519899	0.33152662405684	   
df.mm.trans3:probe9	0.82170239026517	0.0468940587872025	17.5225265527541	1.28695090480113e-53	***
df.mm.trans3:probe10	-0.485858254956756	0.0468940587872025	-10.3607635492057	7.39139458459007e-23	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.27374516614656	0.166993206923334	25.5923294419312	4.72593272418739e-92	***
df.mm.trans1	-0.0604763637523653	0.133686795142707	-0.452373502467528	0.651202198538867	   
df.mm.trans2	-0.0208615787201028	0.133686795142707	-0.156048162407018	0.87605998785541	   
df.mm.exp2	0.0198166712379246	0.179015726352845	0.110697934989608	0.911901675941531	   
df.mm.exp3	-0.123079823130793	0.179015726352844	-0.687536372576562	0.49207343972239	   
df.mm.exp4	-0.0628292382145545	0.179015726352844	-0.350970495691069	0.725762883677244	   
df.mm.exp5	-0.0307183982521643	0.179015726352844	-0.171596087550529	0.863826655063144	   
df.mm.exp6	-0.180409921759747	0.179015726352844	-1.00778811691747	0.31405871020773	   
df.mm.exp7	-0.0215538600086049	0.179015726352845	-0.120402047617435	0.90421453050561	   
df.mm.exp8	-0.201076839138884	0.179015726352845	-1.12323561306875	0.261893131037872	   
df.mm.trans1:exp2	-0.0721977246645157	0.140431489525099	-0.514113500530892	0.607406801071981	   
df.mm.trans2:exp2	0.143854387630710	0.140431489525099	1.02437414939617	0.306169235753651	   
df.mm.trans1:exp3	0.141995216131200	0.140431489525099	1.01113515644810	0.312455916609746	   
df.mm.trans2:exp3	0.118428509338779	0.140431489525099	0.843318758059696	0.399465912317926	   
df.mm.trans1:exp4	-0.00250575075750554	0.140431489525099	-0.0178432256609918	0.985771258994401	   
df.mm.trans2:exp4	0.123688887569541	0.140431489525099	0.880777438079045	0.37887453933979	   
df.mm.trans1:exp5	-0.150009419779668	0.140431489525099	-1.06820357946042	0.285960076613955	   
df.mm.trans2:exp5	0.214109676086080	0.140431489525099	1.52465573647436	0.127996773624191	   
df.mm.trans1:exp6	0.189839533520540	0.140431489525099	1.35183023524514	0.177059719752439	   
df.mm.trans2:exp6	0.220134978535426	0.140431489525099	1.56756137302156	0.117635712660044	   
df.mm.trans1:exp7	0.108472424217327	0.140431489525099	0.772422371820963	0.440240541674664	   
df.mm.trans2:exp7	-0.0256326681209098	0.140431489525099	-0.182527923100386	0.855244712558214	   
df.mm.trans1:exp8	0.125474604669391	0.140431489525099	0.893493368857031	0.372036158444565	   
df.mm.trans2:exp8	0.223670657282338	0.140431489525099	1.59273862321572	0.111870329643883	   
df.mm.trans1:probe2	0.092423367899267	0.0961468682461836	0.96127278594886	0.336894019766701	   
df.mm.trans1:probe3	0.0918246611119942	0.0961468682461836	0.955045783466161	0.340030313830079	   
df.mm.trans1:probe4	0.160121886952133	0.0961468682461837	1.66538848194349	0.0964810360470424	.  
df.mm.trans1:probe5	0.0388853207565201	0.0961468682461836	0.404436685935047	0.686069920463175	   
df.mm.trans1:probe6	0.0202755337682124	0.0961468682461836	0.210880854863593	0.833068816350176	   
df.mm.trans2:probe2	-0.0320456291773762	0.0961468682461837	-0.33329873101351	0.739052834682131	   
df.mm.trans2:probe3	0.0702596218081892	0.0961468682461836	0.730753097732624	0.465282836339537	   
df.mm.trans2:probe4	-0.0250491308951419	0.0961468682461836	-0.260529868024445	0.794565654847603	   
df.mm.trans2:probe5	0.0401330605297144	0.0961468682461836	0.417414121351866	0.676560240157179	   
df.mm.trans2:probe6	0.00364252401726823	0.0961468682461837	0.0378849991030552	0.969794961950693	   
df.mm.trans3:probe2	0.071406476958134	0.0961468682461836	0.742681256921422	0.458034232931379	   
df.mm.trans3:probe3	-0.0524392768917511	0.0961468682461837	-0.545408060067859	0.585723634722707	   
df.mm.trans3:probe4	-0.0360366825935585	0.0961468682461836	-0.374808698930127	0.707966578838754	   
df.mm.trans3:probe5	-0.138391360659454	0.0961468682461837	-1.43937460661853	0.150689498709494	   
df.mm.trans3:probe6	-0.0384895871069577	0.0961468682461836	-0.40032075728567	0.689096549218987	   
df.mm.trans3:probe7	0.00444091271829214	0.0961468682461836	0.0461888442057333	0.963178745910979	   
df.mm.trans3:probe8	-0.0323229262335488	0.0961468682461836	-0.336182829697438	0.736878395933455	   
df.mm.trans3:probe9	-0.0693360446780304	0.0961468682461836	-0.721147198476561	0.471166425814131	   
df.mm.trans3:probe10	-0.0349535490646065	0.0961468682461837	-0.363543292695796	0.716357487993923