readme.aireml
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readme.aireml [2013/07/17 16:25] – shogo | readme.aireml [2014/08/01 17:01] – shogo | ||
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===== Summary ===== | ===== Summary ===== | ||
A modification of REMLF90 for estimating variances with the Average-Information algorithm. Initially written by Shogo Tsuruta in 03/ | A modification of REMLF90 for estimating variances with the Average-Information algorithm. Initially written by Shogo Tsuruta in 03/ | ||
- | See PREGSF90 with genotypes (SNP) for options. | ||
\\ | \\ | ||
AIREMLF90 uses a second derivative REML algrithm with extra heuristics, as is described in Jensen et al. (1996-7). For most models, it converges in far fewer rounds than EM-REML as implemented in REMLF90. While typically REMLF90 takes 50-300 rounds to converge, AIREMLF90 converges in 5-15 rounds and to a higher accuracy. For selected models, AI-REML may fail to converge when the covariance matrix is close to non-positive definite. Adjust sensitivity of the program by setting the appropriate tolerance or setting good starting values. The final results will be saved in " | AIREMLF90 uses a second derivative REML algrithm with extra heuristics, as is described in Jensen et al. (1996-7). For most models, it converges in far fewer rounds than EM-REML as implemented in REMLF90. While typically REMLF90 takes 50-300 rounds to converge, AIREMLF90 converges in 5-15 rounds and to a higher accuracy. For selected models, AI-REML may fail to converge when the covariance matrix is close to non-positive definite. Adjust sensitivity of the program by setting the appropriate tolerance or setting good starting values. The final results will be saved in " | ||
+ | \\ | ||
+ | See PREGSF90 with genotypes (SNP) for options. | ||
===== Options ===== | ===== Options ===== | ||
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</ | </ | ||
Run EM-REML (REMLF90) for first 10 rounds to get initial variances within the parameter space (default 0). | Run EM-REML (REMLF90) for first 10 rounds to get initial variances within the parameter space (default 0). | ||
+ | < | ||
+ | OPTION use_yams | ||
+ | </ | ||
+ | Run the program with YAMS (modified FSPAK). The computing time can be dramatically improved. | ||
< | < | ||
OPTION tol 1d-12 | OPTION tol 1d-12 | ||
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OPTION sol se | OPTION sol se | ||
</ | </ | ||
- | Store solutions and those s.e. | + | Store solutions and those standard errors. |
< | < | ||
- | OPTION | + | OPTION |
</ | </ | ||
- | Set the missing value (default 0). | + | Store triangular matrices of standard errors and its covariances for correlated random effects such as direct-maternal effects and random-regression effects in " |
+ | < | ||
+ | OPTION residual | ||
+ | </ | ||
+ | y-hat and residuals will be included in " | ||
+ | < | ||
+ | OPTION missing -999 | ||
+ | </ | ||
+ | Specify | ||
**Heterogeneous residual variances for a single trait** | **Heterogeneous residual variances for a single trait** | ||
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Specify the SNP file name to use genotype data. | Specify the SNP file name to use genotype data. | ||
+ | < | ||
+ | As an alternative of SE, calculate SD for function of (co)variances by repeated sampling of parameters estimates from their asymptotic multivariate normal distribution, | ||
+ | \\ | ||
+ | ''< | ||
+ | A name for a particular function (e.g., '' | ||
+ | \\ | ||
+ | ''< | ||
+ | A formula to calculate a function of (co)variances to estimate SD. All terms of the function should be written with no spaces.\\ | ||
+ | \\ | ||
+ | Each term of the function corresponds to (co)variance elements and could include any random effects (G, PE, ...) and residual (R) (co)variances.\\ | ||
+ | \\ | ||
+ | Notation is with reference to the effect number and the trait number ('' | ||
+ | where '' | ||
+ | '' | ||
+ | \\ | ||
+ | Several functions could be added, with one OPTION line per function.\\ | ||
+ | \\ | ||
+ | Examples:\\ | ||
+ | \\ | ||
+ | '' | ||
+ | |||
+ | '' | ||
+ | |||
+ | '' | ||
+ | |||
+ | '' | ||
+ | \\ | ||
+ | The first function calculates the SD for the total variance for a maternal model with permanent maternal effect, where 2 and 3 are the effect number for the direct and maternal additive genetic effects respectively, | ||
+ | |||
+ | The second function calculates the heritability for the direct component. | ||
+ | |||
+ | The third function the total heritability. | ||
+ | |||
+ | The fourth function calculates the SD of the genetic correlation between traits 1 and 2 for the direct genetic effect (effect number 2) | ||
+ | < | ||
+ | Set the number of samples to calculate SE for function of (co)variances.\\ | ||
+ | default value 5000 | ||
+ | < | ||
+ | Indicate to store in file samples of (co)variances function for postprocessing (histogram, etc.) |
readme.aireml.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1