Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Cassavabase SolGS presentation PAG 2016

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

  • Login to see the comments

  • Be the first to like this

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
  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 n Open  source  code
  20. 20. Thanks  to…
  21. 21. Many  thanks!! Background  image: