mlmm.gwas v1.0.2 (2018/03/28)
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Initial release on CRAN
mlmm.gwas v1.0.3 (2018/05/03, Olivier Guillaume)
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* Correction of a bug in eBIC_allmodels with FM or FMI models.
* Correction of a bug in the manhattan.plot function.
* R3.5 support
mlmm.gwas v1.0.4 (2018/07/18, Olivier Guillaume and Alexandra Duhnen)
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Important changes (bug correction and changes of functionality):
* BLUE estimation in Estimation_allmodels have been modified for more coherence, with same constraints for all effects (AD)
* Correction of a bug in the genotypes.boxplot function, the tukey classes symbols were wrong in some cases (OG)
* Correction of a bug in the run_entire_gwas_pipeline function, cofactors were not used for effects estimation (AD)
* The package dependency is now R (>= 3.3.0) instead of R (>= 3.4.0).
Minor changes:
* Chromosome are now ordered in alphanumerical order in Manhattan plot instead of alphabetical order (ie. 10 now comes after 9). (OG)
* Special characters in marker names are now supported, especialy ":" that use to cause problem. (OG)
* Unwanted graphical windows opened during mlmm_allmodels execution are now closed immediatly. The window is opened by the sommer:mmer2 function. A way to remove it entierely is yet to be found. (OG)
* The marker order in the table generated by the Estimation_allmodels is now the same as the marker selection order in MLMM instead of alphabetical order (OG)
* Correction of a small bug in the Estimation_allmodels function were underscore were injected in cofactor names (OG)
mlmm.gwas v1.0.5 (2019/05/21, Clément Mabire)
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* Correction of a bug in mlmm_allmodels function, calling the mmer function instead of mmer2 function from sommer package (CM)
* Correction in the mlmm_allmodels function, adding in cofactor the marker with the lowest p-value instead of minimizing the RSS (CM)
mlmm.gwas v1.0.6 (2019/08/05, Clément Mabire)
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* Correction of a bug in fromeBICtoEstimation function, problem in estimation of effects for additivity-dominance models (CM)
* Correction in the eBIC_allmodels function, adding the lambda argument (TF)