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Rindsel : a R package for Selection Indices

Rindsel : a R package for Selection Indices. S. Perez-Elizalde, J. Crossa, J. Ceron-Rojas, and G. Alvarado Biometrics and Statistics Unit CIMMYT and Colegio de Postgraduado , Montecillos , Edo. de Mexico, Mexico. SELECTION INDICES (SI). Phenotypic selection indices

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Rindsel : a R package for Selection Indices

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  1. Rindsel: a R package for Selection Indices S. Perez-Elizalde, J. Crossa, J. Ceron-Rojas, and G. Alvarado Biometrics and Statistics Unit CIMMYT and Colegio de Postgraduado, Montecillos, Edo. de Mexico, Mexico

  2. SELECTION INDICES (SI) Phenotypic selection indices • Smith selection index • Restrictive Kempthorne & Nordskog selection index • Eiegen Selection Index Method • Restrictive eigen selection index method Molecular selection indices • Lande and Thompson (1990) molecular SI. • Molecular ESIM (Ceron-Rojas et al., 2008).

  3. SMITH SELECTION INDEX Two basic linear combinations Selection Index=SI Breeding value Phenotypic values Genotypic values Economic weights (constant) Coefficients

  4. ESIM where and are the eigenvalue and eigenvector of , respectively. The selection response is thus maximizing R is equivalent to maximizing the variance of the SI therefore the selection response is

  5. LANDE and THOMPSON where each mj (j=1, 2, …, N; N= number of molecular scores) is the sum of the products of the MQTL effects multiplied by the coded values of their corresponding MM

  6. MESIM Consider According to BULMER (1980), maximizing is equivalent to maximizing the covariance is invariant to scale changes, it is possible to incorporate two restrictions, and in MESIM and solutions are Since and

  7. Thus,the values that maximize under restrictions are the eigenvalues and eigenvectors of matrix Q

  8. HowtoinstallRindsel • Packages lme4 and Hmisc have to be installed • FromthemenuPackagesselectinstallpackage(s) from local zip file … 2) SelectthefileRindsel_1.0.zip fromthedirectorywhereislocated

  9. HelpforRindsel • Fromthemenuhelpof R callthehtmlhelp browser • Selectthe link packages and searchforRindsel • Or, typehelp.search() in the R commadpromt

  10. Load Rindsel • FromthePackagesmenuselect Load Package. Available packages are displayed. Select Rindsel • Now, you can use the functions of the package. On the command prompt, write IndexName() to display the main menu

  11. Lande and ThomponSelectionIndex ForhelpabouttheLandeand Thompson selection index funtion, onthe R commandpromptwrite >?LTIndex Or use the htlm help browser

  12. Example: Lande & Thompson 2. On the R command line or in a script write LTIndex() if you execute the function without arguments as above defaults options will be used

  13. 3. A window will automatically open requesting the phenotypic data file (field desig and entry x trait responses). Browse the selected file.

  14. 4. Next browse the weigths file In the firs column of the spreadsheet are the traits names, the second the indicator variable o the selected traits, the third one the economic weights (LTIndex) and the fourth one the desired effect of selection (MESIMIndex)

  15. The R routine begins to calculate de geneticand phenotypic covariance (correlation) matrices. 5. After finished the calculation a window will request for the markers file Select the file and browse it

  16. 6. Browsethe molecular scores file The file containsthe scores and itsrelated marker

  17. 7. Finally, the output file is displayed. There are three output files. A plain text file which contains the selected traits, a copy of this file in csv format is also generated. A third file contains all the traits and their selection index values. For the MESIM selection index we proceed in the same way. Example: select the 10 percent of traits with the highest values of the MESIM index. Use covariance matrices already calculated. MESIMIndex(selval=10, rawdata=FALSE)

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