Hi - I am interested in solving variance components for the data below with respect to the response variable, Expression within R.
However, the covariates aren't independent and they also have a class (of which the total variance explained by covariates in that class I am most interested in). Very naively, I have tried to look at each individual covariates variance like this > lm<-lmer(Expression ~ 1 + (1|rs11834524) + (1|rs7074431), data=input_new) > lm Linear mixed-effects model fit by REML Formula: Expression ~ 1 + (1 | rs11834524) + (1 | rs7074431) Data: input AIC BIC logLik MLdeviance REMLdeviance 108.4 116.5 -51.22 102.5 102.4 Random effects: Groups Name Variance Std.Dev. rs11834524 (Intercept) 0.485538 0.69681 rs7074431 (Intercept) 0.013720 0.11713 Residual 0.128853 0.35896 number of obs: 109, groups: rs11834524, 3; rs7074431, 3 Fixed effects: Estimate Std. Error t value (Intercept) 9.9524 0.4098 24.29 My assumption is that this is telling me that rs11834524 explains 0.485538 of the variance and rs7074431 explains 0.013720 of the variance in Expression when looked at independently. However, I would like to know how to write a model where I know how much of the total variance (in Expression) is described by covariates rs11834524, rs1682421, rs13383869 and rs9457141 (call it class A) and covariates rs9459617, rs7074431, rs12450785, rs592724 (call it class B). Assuming an additive model within the class. The caveats are that there is missing data and again that there may be correlation between all the covariates. Such that a theoretical result may be that Class A: Explains 60% of the total variance in expression (response) Class B: Explains 10% of the total variance in expression Thanks for the help! I am sorry I am R challenged here...I really appreciate the guidance! Stephen > dump("input_new", file=stdout()) input_new <- structure(list(Individual = structure(1:109, .Label = c("NA06984", "NA06985", "NA06986", "NA06989", "NA06993", "NA06994", "NA07000", "NA07022", "NA07037", "NA07045", "NA07051", "NA07055", "NA07056", "NA07345", "NA07346", "NA07347", "NA07357", "NA07435", "NA11829", "NA11830", "NA11831", "NA11832", "NA11839", "NA11840", "NA11843", "NA11881", "NA11882", "NA11892", "NA11893", "NA11894", "NA11917", "NA11918", "NA11919", "NA11920", "NA11930", "NA11931", "NA11992", "NA11993", "NA11994", "NA11995", "NA12003", "NA12005", "NA12006", "NA12043", "NA12044", "NA12056", "NA12057", "NA12144", "NA12145", "NA12146", "NA12154", "NA12155", "NA12156", "NA12234", "NA12239", "NA12248", "NA12249", "NA12264", "NA12272", "NA12273", "NA12274", "NA12275", "NA12282", "NA12283", "NA12286", "NA12287", "NA12340", "NA12341", "NA12342", "NA12343", "NA12347", "NA12348", "NA12383", "NA12399", "NA12400", "NA12414", "NA12489", "NA12546", "NA12716", "NA12718", "NA12748", "NA12749", "NA12750", "NA12751", "NA12760", "NA12761", "NA12762", "NA12763", "NA12775", "NA12776", "NA12777", "NA12778", "NA12812", "NA12813", "NA12814", "NA12815", "NA12827", "NA12828", "NA12829", "NA12830", "NA12842", "NA12843", "NA12872", "NA12873", "NA12874", "NA12875", "NA12889", "NA12891", "NA12892" ), class = "factor"), Expression = c(9.46026823453575, 10.0788903323991, 9.20330296497174, 10.038741467793, 9.33092349416463, 11.0273957217919, 10.5498875891745, 9.81137299592747, 11.2023261987976, 9.90559354069027, 10.1524696609679, 10.3171767665993, 9.02155519577685, 9.84917871051438, 10.658877473136, 9.88895551011107, 8.62335008726357, 9.21529114100886, 10.7896248923916, 10.1302992505869, 8.64584282787018, 9.56057795866654, 9.89810004078774, 10.2557482141576, 8.95588077688637, 9.56452454115857, 9.26525135092154, 10.5438780642797, 9.8468571349548, 10.7416169225352, 10.5623721612979, 10.6565276881443, 9.67758493445612, 9.75385553511462, 8.997797236767, 11.0106882086179, 10.362578597992, 9.2745507212906, 10.7453355016181, 9.75998268015348, 9.45003620116962, 10.055504292376, 10.7072220720564, 10.0934686444392, 10.0472832129727, 10.1185615033486, 10.3340911031131, 9.70618910683157, 10.5953304905529, 10.4246307909547, 9.91463202635336, 10.249081562168, 10.9252022586474, 10.295544143525, 11.4838109797985, 10.5286570234792, 9.78692800868132, 10.0397050809162, 9.27914623343747, 10.37600233389, 9.27341681588134, 9.40195375611303, 10.8979822929135, 9.03922228977389, 10.3911745662505, 10.4345408213054, 9.8548491618724, 10.1897729275437, 10.2881888849609, 8.9656977165014, 9.81595398472166, 10.1856794532084, 9.3763789479684, 10.1712420020647, 10.2964594680427, 10.3515965292101, 8.94492585275159, 11.2529257614993, 9.25146912450726, 10.1904309237525, 10.7490591053023, 10.3883924463568, 10.097023765247, 10.0824730785217, 10.0828512817661, 10.6371064852226, 10.5831044752098, 10.4484786486601, 8.50264408341596, 10.3468670812262, 9.46061433005316, 8.90027436167269, 9.73630671555279, 9.40555522408144, 10.3220768104446, 8.55132985773453, 10.1678182524815, 10.6145417864386, 10.4169948161073, 10.0253039670548, 10.2568017077865, 10.5045847076951, 9.75993936712448, 8.99997092895909, 10.6742222414794, 10.8640943324257, 10.4295384371541, 10.1987862649656, 10.6744617172313), rs11834524 = structure(c(1L, 2L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 2L, 3L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 3L, 3L, 3L, 2L, 1L, 1L, 3L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 1L, 2L, 1L, 1L, 3L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 3L, 1L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L), .Label = c("AA", "AG", "GG"), class = "factor"), rs1682421 = structure(c(1L, 2L, 1L, 2L, 2L, 3L, 2L, 2L, 3L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 3L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 3L, 1L, 1L, 2L, 3L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, NA, 3L, 2L, 3L, 2L, 2L), .Label = c("CC", "CT", "TT"), class = "factor"), rs13383869 = structure(c(2L, 2L, 2L, 2L, 2L, NA, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 1L, 2L, 2L, 3L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 3L, 2L, NA, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 3L, 2L, 2L, 1L, 1L, 2L, 3L, 2L, 2L, 3L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 3L, 1L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 1L, 1L, 2L, 2L, NA, 2L, 1L, 1L, 2L, 2L, 1L, 1L), .Label = c("AA", "AG", "GG"), class = "factor"), rs9457141 = structure(c(1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 3L, 1L, 3L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 1L, 2L, 1L, 2L, 3L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, NA, 2L, 1L, 2L, NA, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("CC", "CT", "TT"), class = "factor"), rs9459617 = structure(c(1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 3L, 1L, 3L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 1L, NA, 1L, 3L, 3L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("CC", "CT", "TT"), class = "factor"), rs7074431 = structure(c(2L, 3L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 1L, 1L, 3L, 2L, 1L, 2L, 3L, 2L, 1L, 2L, 1L, 3L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 3L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 1L, 2L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L), .Label = c("CC", "CT", "TT"), class = "factor"), rs12450785 = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 1L, 3L, 1L, 3L, 3L, 2L, 2L, 1L, 2L, 3L, 2L, 3L, 1L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 1L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 1L, 3L, 2L, 2L, 3L, 2L, 2L, 3L, 3L, 2L, 2L, 3L, 2L, 2L, 3L, 1L, 3L, 2L, 2L, 1L, 3L, 2L, 3L, 1L, 3L, 2L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 2L, 3L, 2L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 2L), .Label = c("AA", "AG", "GG"), class = "factor"), rs592724 = structure(c(1L, 2L, 1L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 3L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 3L, 1L, 3L, 2L, 1L, 1L, 2L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 3L, 1L, 3L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 3L, 1L, 3L, 3L, 2L, 2L, 1L, 1L, 3L, 2L, 2L, 2L, 1L, 3L, 2L, 3L, 1L, 3L, 3L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 3L, 2L, 2L, 2L), .Label = c("CC", "CT", "TT"), class = "factor"), Grp = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "1", class = "factor")), .Names = c("Individual", "Expression", "rs11834524", "rs1682421", "rs13383869", "rs9457141", "rs9459617", "rs7074431", "rs12450785", "rs592724", "Grp"), row.names = c(NA, -109L), class = "data.frame") Stephen B. Montgomery Postdoctoral Researcher, Population and Comparative Genomics Wellcome Trust Sanger Institute Hinxton, Cambridge CB10 1SA Skype: stephen.b.montgomery -- The Wellcome Trust Sanger Institute is operated by Genome Research Limited, a charity registered in England with number 1021457 and a company registered in England with number 2742969, whose registered office is 215 Euston Road, London, NW1 2BE. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.