Calculate Standard Error Heritability
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influences or stochastic variation. That's just a general definition to give you a feel for it. Actually we need to be more rigorous than that. There are two definitions of heritability. how to calculate heritability h2 A common simplification in all sorts of genetic studies and models is to how to calculate heritability coefficient assume that all alleles and all genotypes act independently of each other - this is called an ‘additive model.' So
How To Calculate Heritability From Concordance
for instance, if one allele of a particular SNP gives you a 1 cm increase in height, then being homozygous for that SNP should give you a 2 cm increase in height. Clearly,
How To Calculate Heritability Of A Trait
this model doesn't allow for dominant or recessive effects, even though we know these abound. It also doesn't allow for gene-gene interactions, where maybe that SNP only gives you a 1 cm increase in height if paired with another SNP. For these reasons, the additive model is a huge simplification, but a useful one. Now for the two definitions of heritability: ‘narrow sense heritability' (h2) is defined how to calculate standard error in excel as the proportion of trait variance that is due to additive genetic factors ‘broad sense heritability' (H2) is defined as the proportion of trait variance that is due to all genetic factors including dominance and gene-gene interactions. Both kinds of heritability are incredibly tricky to estimate and to interpret. In terms of estimation, a big problem is that people who share parts of their genome tend to share parts of their environment too. One simple way you might think to estimate heritability is to plot children's traits against the average of their parents, as shown in this example from Visscher 2008: In the example above, the slope is taken to be the heritability. The problem with this is that parent and child share a lot else besides half their genome. One approach to calculating heritability which largely avoids the confounding of genotype with shared environment is to compare the phenotypic concordance of monozygotic (MZ, identical) twins versus dizygotic (DZ, fraternal) twins. Both types of twins are expected to share virtually all environmental factors, including while in the womb, which is why this is a better study design than just comparing MZ twins to siblings. Comparing MZ to DZ twins let
GCTA Discussion Board SMR software SMR Discussion Board Reply Standard error calculation Share ThreadFacebookTwitterGoogle+TumblrLinkedInPinterestRedditMySpaceEmailGo toPrevious ThreadNext ThreadPlease make a selection first new « Prev1Next » phage Guest Standard error calculation Nov 15, 2013 11:37:13 GMT Quote Select PostDeselect PostLink
How To Calculate Standard Error In R
to PostBack to Top Post by on Nov 15, 2013 11:37:13 GMT Hello,I've searched how to calculate standard error without standard deviation extensively but have been unable to find an explanation of how GCTA computes standard error for its heritability results, and I don't calculate standard error regression feel comfortable using the reported value unless I understand the methodology behind their calculation. How is this done?Thank you! Terry Guest Standard error calculation Nov 16, 2013 13:55:38 GMT Quote Select PostDeselect PostLink to PostBack http://www.cureffi.org/2013/02/04/how-to-calculate-heritability/ to Top Post by on Nov 16, 2013 13:55:38 GMT Hi,I agree, it would be nice to know it! Jian Yang Administrator Posts: 328 Standard error calculation Nov 17, 2013 6:59:01 GMT Quote Select PostDeselect PostLink to PostMemberGive GiftBack to Top Post by Jian Yang on Nov 17, 2013 6:59:01 GMT SE of a variance component = the square root of the corresponding diagonal element of inverse(AI matrix). See GCTA http://gcta.freeforums.net/thread/13/standard-error-calculation AJHG paper (page 2) for AI matrix. Last Edit: Nov 17, 2013 7:00:24 GMT by Jian Yang Terry Guest Standard error calculation Nov 17, 2013 23:49:37 GMT Quote Select PostDeselect PostLink to PostBack to Top Post by on Nov 17, 2013 23:49:37 GMT Thanks Jiang! Is there a way of computing the SE of the environmental influences standardised to the total variance, as V(e)/V(P), from the GCTA output? Jian Yang Administrator Posts: 328 Standard error calculation Nov 18, 2013 3:26:45 GMT Quote Select PostDeselect PostLink to PostMemberGive GiftBack to Top Post by Jian Yang on Nov 18, 2013 3:26:45 GMT This can be calculated in the the same way as that for V(G) / Vp.Say x = V(G) and y = Vpvar(x/y) is approximately = (u_x/u_y)^2[var(x)/u_x^2 + var(y)/u_y^2 - 2*cov(x,y)/(u_x*u_y)], where u_x = E(x) and u_y = E(y). In practice, u_x (or u_y) is usually replaced by x (or y).SE = the square root of var(x/y)var(x), var(y) and cov(x,y) can be calculated from the variance-covariance matrix in the log file (the stuff printed out on the screen). Terry Guest Standard error calculation Nov 19, 2013 2:44:17 GMT Quote Select PostDeselect PostLink to PostBack to Top Post by on Nov 19, 2013 2:44:17 GMT Thanks again, Jian! That was very c
to the concepts in the particular subject fields and will require an understanding of both statistics and the concerned disciplines to fully appreciate their implications. Some of these topics are briefly http://www.fao.org/docrep/003/x6831e/x6831e13.htm covered in what follows. It may be noted that quite many developments http://link.springer.com/article/10.1186/1297-9686-36-3-363 have taken place in each of the topics mentioned below and what is reported here forms only a basic set in this respect. The reader is prompted to make further reading wherever required so as to get a better understanding of the variations possible with respect to data structure or in the how to form of analysis in such cases. 6.1 Genetics and plant breeding 6.1.1. Estimation of heritability and genetic gain The observed variation in a group of individuals is partly composed of genetic or heritable variation and partly of non-heritable variation. The fraction of total variation which is heritable is termed the coefficient of heritability in the broad sense. The genotypic variation itself can be sub-divided how to calculate into additive and nonadditive genetic variance. The ratio of additive genetic variance to the total phenotypic variance is called the coefficient of heritability in the narrow sense and is designated by h2. Thus, Conceptually, genetic gain or genetic improvement per generation is the increase in productivity following a change in the gene frequency induced mostly by selection. Heritability and genetic gain can be estimated in either of two ways. The most direct estimates are derived from the relation between parents and offspring, obtained by measuring the parents, growing the offspring, and measuring the offspring. The other way is to establish a half-sib or full-sib progeny test, conduct an analysis of variance and compute heritability as a function of the variances. Understanding the theoretical part in this context requires a thorough knowledge of statistics. Formulae given below in this section are intended only as handy references. Also, there is no attempt made to cover the numerous possible variations that might result from irregularities in design. Half-sib progeny test is used for illustration as it is easier to establish and so more common in forestry. Both heritability and gain estimates apply strictly only to
feedback return to old SpringerLink Download PDF Genetics Selection EvolutionJune 2004, 36:363Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REMLAuthorsAuthors and affiliationsTroy M FischerEmail authorArthur R GilmourJulius H.J. van der WerfOpen AccessResearchFirst Online: 15 May 2004Received: 21 October 2003Accepted: 09 January 2004DOI: 10.1186/1297-9686-36-3-363Cite this article as: Fischer, T.M., Gilmour, A.R. & van der Werf, J.H. Genet Sel Evol (2004) 36: 363. doi:10.1186/1297-9686-36-3-363 39 Citations 3k Views AbstractApproximate standard errors (ASE) of variance components for random regression coefficients are calculated from the average information matrix obtained in a residual maximum likelihood procedure. Linear combinations of those coefficients define variance components for the additive genetic variance at given points of the trajectory. Therefore, ASE of these components and heritabilities derived from them can be calculated. In our example, the ASE were larger near the ends of the trajectory.Keywordsrandom regressionheritabilityapproximate standard errorgenetic parameterresidual maximum likelihood(To access the full article, please see PDF)Copyright information© INRA, EDP Sciences 2004Authors and AffiliationsTroy M Fischer13Email authorArthur R Gilmour23Julius H.J. van der Werf131.School of Rural Science and AgricultureUniversity of New EnglandArmidaleAustralia2.NSW AgricultureOrange Agricultural InstituteOrangeAustralia3.Australian Sheep Industry CRCAustralia About this article Online ISSN 1297-9686 Publisher Name BioMed Central About this journal Reprints and Permissions Article actions Export citation .RIS Papers Reference Manager RefWorks Zotero .ENW EndNote .BIB BibTeX JabRef Mendeley Share article Email Facebook Twitter LinkedIn Cookies We use