readme.thrgibbs1
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
readme.thrgibbs1 [2012/05/29 13:02] – shogo | readme.thrgibbs1 [2019/03/29 23:20] – [Options] shogo | ||
---|---|---|---|
Line 1: | Line 1: | ||
- | =====THRGIBBS1F90===== | + | ====== THRGIBBS1F90 ====== |
- | // | + | |
- | Gibbs sampler for threshold-linear mixed models | + | |
=====Summary===== | =====Summary===== | ||
- | Based on THRGIBBSF90 written by DeukHwan Lee at the University of Georgia, | + | Gibbs sampler for threshold-linear mixed models. The original program (THRGIBBSF90) was written by DeukHwan Lee in 2001 based on GIBBS2F90 |
- | Rewritten by Shogo Tsuruta, 2004 | + | \\ |
- | last modified 09/ | + | THRGIBBS1F90 implements Gibbs sampler for mixed threshold-linear models involving multiple categorical and linear variables. Thresholds and variances can be estimated |
- | + | \\ | |
- | + | See PREGSF90 with genotypes (SNP) for options. | |
- | =====Functionality===== | + | |
- | THRGIBBS1F90 | + | |
- | involving multiple categorical and linear variables. Thresholds and variances | + | |
- | can be computed | + | |
=====Parameters===== | =====Parameters===== | ||
Line 21: | Line 15: | ||
OPTION cat 0 0 2 5 | OPTION cat 0 0 2 5 | ||
</ | </ | ||
- | 0s indicate that the first and second traits are linear. | + | " |
- | 2 and 5 indicate that the third and fourth traits are categorical with 2 and 5 categories. | + | "2" |
< | < | ||
OPTION fixed_var all | OPTION fixed_var all | ||
</ | </ | ||
- | Store all samples for solutions in " | + | Store all samples for solutions in " |
- | assuming that (co)variances | + | |
< | < | ||
OPTION fixed_var all 1 2 3 | OPTION fixed_var all 1 2 3 | ||
- | Store all samples for solutions in " | ||
</ | </ | ||
+ | Store all samples for solutions in " | ||
< | < | ||
OPTION fixed_var mean | OPTION fixed_var mean | ||
</ | </ | ||
- | Only posterior means and SD for solutions are calculated for all effects in " | + | Only posterior means and SD for solutions are calculated for all effects in " |
< | < | ||
OPTION fixed_var mean 1 2 3 | OPTION fixed_var mean 1 2 3 | ||
- | Only posterior means and SD for solutions are calculated for effects 1, 2, and 3 in " | ||
</ | </ | ||
+ | Only posterior means and SD for solutions are calculated for effects 1, 2, and 3 in " | ||
< | < | ||
OPTION solution all | OPTION solution all | ||
</ | </ | ||
- | Store all samples for solutions in " | + | Caution: this option will create a huge output solution file when you run many rounds and/or use a large model. |
+ | Store all samples for solutions in " | ||
< | < | ||
OPTION solution all 1 2 3 | OPTION solution all 1 2 3 | ||
</ | </ | ||
- | Store all samples for solutions in " | + | Caution: this option will create a huge output solution file when you run many rounds and/or use a large model. |
+ | Store all samples for solutions in " | ||
< | < | ||
OPTION solution mean | OPTION solution mean | ||
</ | </ | ||
- | Only posterior means and SD for solutions are calculated for all effects in " | + | Only posterior means and SD for solutions are calculated for all effects in " |
< | < | ||
OPTION solution mean 1 2 3 | OPTION solution mean 1 2 3 | ||
</ | </ | ||
- | Only posterior means and SD for solutions are calculated for effects 1, 2, and 3 in " | + | Only posterior means and SD for solutions are calculated for effects 1, 2, and 3 in " |
< | < | ||
- | OPTION | + | OPTION |
</ | </ | ||
- | 10000 is the number of samples run previously. | + | The program saves every " |
- | The user can restart the program from the last run. | + | |
< | < | ||
- | OPTION prior 10 | + | OPTION cont 10000 |
+ | </ | ||
+ | " | ||
+ | When using " | ||
+ | OPTION prior 5 2 -1 5 | ||
</ | </ | ||
- | 10 is the degree of belief for the priors specified in the parameter file. | + | The (co)variance |
+ | Degree of belief for all random effects should be specified using the following structure: | ||
+ | OPTION prior eff1 db1 eff2 db2 ... effn dbn -1 dbres\\ | ||
+ | effx correspond to the effect number and dbx to the degree of belief for this random effect, -1 corresponds to the degree of belief of the residual variance.\\ | ||
+ | In this example 2 is the degree of belief for the 5th effect, and 5 is the degree of belief for the residual.\\ | ||
< | < | ||
OPTION seed 123 -432 | OPTION seed 123 -432 | ||
Line 72: | Line 74: | ||
OPTION thresholds 0.0 1.0 2.0 | OPTION thresholds 0.0 1.0 2.0 | ||
</ | </ | ||
- | Set the fixed the thresholds | + | Set the fixed thresholds. No need to set 0 for binary traits. |
- | No need to set 0 for binary traits | + | |
< | < | ||
OPTION residual 1 | OPTION residual 1 | ||
</ | </ | ||
- | Set the residual variance | + | The residual variance can be set to 1 but not necessary for categorical traits more than 2 categories. For binary traits, |
< | < | ||
- | OPTION | + | OPTION |
</ | </ | ||
- | Negative values of the last category in the data set indicate censored records. " | + | Specify checking pos-def for fixed effects where x.x is a tolerance (default=1d-08). |
< | < | ||
- | OPTION | + | OPTION |
</ | </ | ||
- | Change | + | Negative values for the categorical trait in the data set indicate censored records. "1 0" determines that the first categorical trait is censored and the second uncensored. |
+ | < | ||
+ | OPTION SNP_file snp | ||
+ | </ | ||
+ | Specify the SNP file name to use genotype data. | ||
+ | ==== Save intermediate results for "cold start" ==== | ||
+ | |||
+ | OPTION save_halfway_samples n | ||
+ | |||
+ | This option can help the 'cold start' (to continue the sampling when the program accidentally stops before completing the run). An integer | ||
+ | |||
+ | To restart, add '' | ||
+ | |||
+ | === Tips === | ||
+ | * Small //n// will make the program slow because of frequent file writing. The //n// should be a multiple of the interval (the 3rd number you will input in the beginning of the program). | ||
+ | * If the program stops during burn-in, the restart will fail because '' | ||
+ | * The cold start may add tiny numerical errors to the samples. Samples from the cold start wouldn' | ||
+ | * If, unfortunately, | ||
+ | |||
+ | === Example === | ||
+ | Put the following option in your parameter file. | ||
+ | |||
+ | OPTION save_halfway_samples 100 | ||
+ | |||
+ | Run '' | ||
+ | |||
+ | '**** saving halfway samples in every | ||
+ | |||
+ | In this case, we assume the number of total samples is 3000, the burn-in is 0, and the interval is 10. | ||
+ | |||
+ | | ||
+ | 3000 0 | ||
+ | Give n to store every n-th sample? (1 means store all samples) | ||
+ | 10 | ||
+ | |||
+ | Make sure the intermediate results are saved to files. | ||
+ | |||
+ | 100 rounds | ||
+ | G | ||
+ | 2758. | ||
+ | 1900. | ||
+ | 2019. | ||
+ | G | ||
+ | 225.5 -91.35 | ||
+ | | ||
+ | | ||
+ | R | ||
+ | 1755. | ||
+ | 868.7 | ||
+ | 817.0 | ||
+ | * Last seeds = 1877469549 | ||
+ | * Number of samples kept = 100 | ||
+ | solutions stored in binary file: " | ||
+ | solutions stored in file: " | ||
+ | |||
+ | Stop the program. In this case, program stops in the round 880. | ||
+ | |||
+ | | ||
+ | forrtl: error (69): process interrupted (SIGINT) | ||
+ | Image PC Routine | ||
+ | thrgibbs1f90 | ||
+ | thrgibbs1f90 | ||
+ | |||
+ | Make sure there are the following 5 files. | ||
+ | |||
+ | binary_final_solutions | ||
+ | |||
+ | Browse the file '' | ||
+ | |||
+ | Saved on 2017-03-10 10:53:22 | ||
+ | |||
+ | State in the current run: | ||
+ | last round = 800 | ||
+ | sampled in this run | ||
+ | total number of samples = | ||
+ | number of burn-in | ||
+ | interval | ||
+ | |||
+ | Suggestion for the input in next run: | ||
+ | total number of samples = | ||
+ | number of burn-in | ||
+ | interval | ||
+ | |||
+ | When you restart the program, do not forget to put the following option | ||
+ | in your parameter file. | ||
+ | | ||
+ | |||
+ | Put the option '' | ||
+ | |||
+ | OPTION cont 1 | ||
+ | |||
+ | Run '' | ||
+ | |||
+ | '*** continuous sampling selected *** previous # samples = 1 | ||
+ | |||
+ | **NOTE: Although the message may say the previous number of sample is 1, you can ignore it. The program recognizes it is the cold start mode and works correctly.** | ||
+ | |||
+ | Input the three numbers that are shown in '' | ||
+ | |||
+ | | ||
+ | 2200 0 | ||
+ | Give n to store every n-th sample? (1 means store all samples) | ||
+ | 10 | ||
+ | |||
+ | The program will start from the round 801 as expected. | ||
+ | |||
+ | | ||
+ | G | ||
+ | | ||
+ | | ||
+ | | ||
+ | G | ||
+ | | ||
+ | | ||
+ | | ||
+ | R | ||
+ | | ||
+ | | ||
+ | | ||
+ | |||
+ | Just wait the analysis. You can interrupt the program again. The final results will be basically the same to ones from a non-stop analysis. | ||
readme.thrgibbs1.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1