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Cassavabase SolGS presentation PAG 2016

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Presentation of the Genomic selection web based tool SolGS at PAG 2016

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Cassavabase SolGS presentation PAG 2016

  1. 1. solGS:  A  Web-­based  Solution  for   Genomic  Selection Isaak  Y  Tecle,  Naama  Menda,  Guillaume   Bauchet,  Lukas  Mueller Tecle  et  al.  Bioinformatics  2014,  15:398
  2. 2. Phenotyped   &   genotyped  individuals Genomic  selection… Prediction  model Predicted   breeding Values  (GEBVs) Genotyped  selection   candidates Training  population
  3. 3. Challenges… n Data  volume,  storage n Data  structuring,  cleaning,  imputation n Statistical  analysis  complexity n visualization  and  sharing
  4. 4. solGS  webtool http://cassavabase.org/solgs
  5. 5. What  you  can  do  with  solGS… n Store  data n Chado  Natural  Diversity  schema n Compose  training  populations n Build  models  and  predict  breeding   values  of  selection  candidates n Test  model  accuracy  
  6. 6. What  you  can  do  with  solGS… n Explore  phenotype  data,  population   structure n Check  on  relationship  between  GEBVs   vs  observed  phenotypes n Calculate  selection  indices,  correlation   n Visualize  data  on  interactive  plots
  7. 7. What  is  the  statistical  approach   behind  solGS?
  8. 8. …preparing  data n Omits  individuals  completely  missing   phenotype  values n Adjusts  phenotype  values  for  block   effects n Averages  across  multiple  trials  after   adjusting  for  block  effects n Imputes  missing  marker  data n Median  substitution
  9. 9. …statistical  modeling n Univariate n RR-­BLUP n Endelman,  Plant  Genome  (2010) n GBLUP   n Marker-­based  realized  relationship  matrix n Prediction  accuracy n Based  on  10-­fold  cross-­validation
  10. 10. How  does  solGS  work?
  11. 11. Composing  a  training  population:   Fitting  a  prediction  model... 3  options
  12. 12. Fitting  a  prediction  model… Option  1:   Search  using  a  trait  name
  13. 13. Estimating  breeding  values  of   selection  candidates Applying  the  model…
  14. 14. Fitting  a  prediction  model… Option  2:   Search  for  trials
  15. 15. Estimating  breeding  values  of  a   selection  candidates  for  multiple   traits Applying  the  models…
  16. 16. Estimating  genetic  correlations
  17. 17. Calculating  selection  indices
  18. 18. Fitting  a  prediction  model… Option  3:   use  your  own  list  of  individuals
  19. 19. To  sum  up… n Store  data n Build  prediction  models n Estimate  breeding  values n Additional  analyses:   n Correlation  analysis n Population  structure n Selection  indices n http://cassavabase.org/solgs n Open  source  code
  20. 20. Thanks  to…
  21. 21. Many  thanks!! Background  image:  nextgencassava.org

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