readme.aireml
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readme.aireml [2012/05/29 17:06] – shogo | readme.aireml [2014/11/25 11:32] – shogo | ||
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====== AIREMLF90 ====== | ====== AIREMLF90 ====== | ||
- | \\ | ||
- | A modification of REMLF90 for estimating variances with the Average-Information algorithm. Initially written by Shogo Tsuruta in 03/ | ||
===== Summary ===== | ===== Summary ===== | ||
- | AIREMLF90 uses a second derivative REML algrithm | + | 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. | ||
===== Options ===== | ===== Options ===== | ||
Line 12: | Line 13: | ||
Convergence criterion (default 1d-10). | Convergence criterion (default 1d-10). | ||
< | < | ||
- | OPTION maxrounds | + | OPTION maxrounds |
</ | </ | ||
- | Maximum rounds (default 5000). When it is negative, the program calculates BLUP without | + | Maximum rounds (default 5000). When the number = 0, the program calculates BLUP without |
< | < | ||
OPTION EM-REML 10 | OPTION EM-REML 10 | ||
</ | </ | ||
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 | ||
</ | </ | ||
- | Tolerance (or precision) (default 1d-14) for positive definite matrix and g-inverse subroutines. Convergence may be much faster by changing this value. | + | Tolerance (or precision) (default 1d-14) for positive definite matrix and g-inverse subroutines.\\ |
+ | Convergence may be much faster by changing this value. | ||
< | < | ||
OPTION sol se | OPTION sol se | ||
</ | </ | ||
- | Store solutions and 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 | ||
+ | < | ||
+ | OPTION constant_var 5 1 2 ... | ||
+ | </ | ||
+ | 5: effect number\\ | ||
+ | 1: first trait number\\ | ||
+ | 2: second trait number\\ | ||
+ | implying the covariance between traits 1 and 2 for effect 5. | ||
**Heterogeneous residual variances for a single trait** | **Heterogeneous residual variances for a single trait** | ||
Line 40: | Line 61: | ||
OPTION hetres_pol 4.0 0.1 0.1 | OPTION hetres_pol 4.0 0.1 0.1 | ||
</ | </ | ||
- | Initial values of coefficients for heterogeneous residual variances | + | Initial values of coefficients for heterogeneous residual variances |
- | **Heterogeneous residual variances for multiple traits** | + | **Heterogeneous residual variances for multiple traits**\\ |
+ | Convergence will be very slow with multiple trait heterogeneous residual variances | ||
< | < | ||
OPTION hetres_pos 10 10 11 11 | OPTION hetres_pos 10 10 11 11 | ||
+ | </ | ||
+ | or | ||
+ | < | ||
+ | OPTION hetres_pos 10 11 12 13 | ||
</ | </ | ||
Specify the position of covariables (trait first). | Specify the position of covariables (trait first). | ||
+ | "10 10" or "10 11" could be linear for first and second traits.\\ | ||
+ | "11 11" or "12 13" could be quadratic. | ||
< | < | ||
OPTION hetres_pol 4.0 4.0 0.1 0.1 0.01 0.01 | OPTION hetres_pol 4.0 4.0 0.1 0.1 0.01 0.01 | ||
</ | </ | ||
- | Initial values of coefficients for heterogeneous residual variances | + | Initial values of coefficients for heterogeneous residual variances |
+ | "4.0 4.0" are intercept for first and second traits.\\ | ||
+ | "0.1 0.1" could be linear and "0.01 0.01" could be quadratic.\\ | ||
+ | To transform back to the original scale, use exp(a0+a1*X1+a2*X2). | ||
+ | < | ||
+ | OPTION SNP_file snp | ||
+ | </ | ||
+ | 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.) | ||
+ | |||
+ | ===== Tricks ===== | ||
+ | When the covariance matrix is close to non-positive definite, the AIREMLF90 may not converge. | ||
+ | There are two options you might want to try: | ||
+ | |||
+ | 1. change the tolerance value (xx) in the option: | ||
+ | |||
+ | OPTION tol xx | ||
+ | |||
+ | to a very strict value (e.g., 1d-20) or a lenient value (1d-06). | ||
+ | |||
+ | 2. use an option to use EM-REML inside AI-REML: | ||
+ | |||
+ | OPTION EM-REML xx | ||
+ | |||
+ | where xx is the number of iterations for EM-REML you expect to get a good starting value for AI-REML. After running xx rounds with EM-REML, the AIREMLF90 program will automatically switch from EM-REML to AI-REML using the last estimate from EM-REML as a starting value for AI-REML. | ||
readme.aireml.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1