Rijk Zwaan develops vegetable varieties and sells the seeds they produce. Rijk Zwaan has over 1.000 varieties in 25 different vegetable crops. The company shares challenges of sequencing data and compares deployment of GENALICE MAP with BWA/GATK on storage footprint, analysis speed and shares first in house experiences. For more information on GENALICE MAP, please visit http://www.genalice.com/product/genalice-map/

1. NGS data processing
with GENALICE MAP
Remco Ursem

2. Rijk Zwaan Biotechnology
Research Facilities
Fijnaart, The Netherlands

3. Outline
• Rijk Zwaan
• Sequencing data challenge
• Comparing GENALICE MAP with
BWA/GATK
– Storage footprint
– Analysis speed
– First in house experiences
• Wrap-up

4. • Since 1924
• Independent
• 2,500 colleagues
Family company

5. Our organization

6. > 25 crops

7. Data deluge?
• Re-sequencing larger number of
accessions/lines
• Reference available for growing
amount of crops
• Multiple references available per
(sub)species
• Fast evolving versioning of
references

8. Yes!
• Storage footprint grows exponential
• Computational demand as well
• Looking for a solution we came in
contact with Genalice

9. Storage footprint

10. 10

11. Cucumber alignment file size
27,9 GB
0,99 GB
28 X
BAM
GAR

12. 12

13. 13

14. 14

15. GAR file

16. Lossless compression?
• No, but does it matter?
• Probably not when we have clean
high quality data.

17. Analysis

18. Variant calling pipeline
• Based on BWA / GATK (Broad)

19. Conclusions
• This variant calling pipeline does
need serious hardware!
• Not all steps can be easily
parallelized.
• Does not scale in our setup.

20. GENALICE Server
• 24 cores
• 128G RAM

21. Two test cases
• Cucumber sample
– 300 MB genome
– No problems with old pipeline
• Brassica sample
– 600 MB genome
– Unreliable calls detected

22. Elapsed time to Map/Call cucumber
BWA/GATK GENALICE
mapping 21:02 16
calling 2:24 1
total 23:26 17 83X

23. Comparing Cucumber SNP calling
0
100000
200000
300000
400000
500000
600000
700000
Total SNP's
Overlapping Genotypes
BWA/GATK GENALICE
Higher quality SNPs overlap.
GENALICE settings probably to stringent?
BWA/GATK to loose?
Both?

24. Comparing SNP zygosity
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Homozygous SNP's
Heterezygous SNP's
BWA/GATK GENALICE

25. Elapsed time to Map/Call Brassica
BWA/GATK Genalice
mapping 20:03 13
calling 1:18 1
total 21:21 14 92X

26. Comparing Brassica SNP calling
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
Total SNP's
Overlapping genotypes
To stringent, but something else going on?
BWA/GATK GENALICE

27. Whole genome duplications

28. Comparing SNP zygosity
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Homozygous SNP's
Heterozygous SNP's
BWA/GATK GENALICE

29. Comparing with marker assay results
0
100
200
300
400
500
600
700
800
Failed Markers
Passed markers
BWA/GATK GENALICE

30. Conclusions
• GENALICE makes it possible to do
wide parameters sweeps.
• This enables crop/assembly specific
pipeline fine tuning .

31. Integration with other tools
• BAM and VCF export functionality
and GAR-API suite available.
• IGV plugin works with GAR files.

32. More than SNPs
EliaStupka_etal_NGS-meeting 2012

33. More than SNPs
• GENALICE pipeline calls INDELs up to
126 base pairs.
• SV calling under development.

34. Wrap-up
• GENALICE pipeline is very fast!
• Feasible to rerun entire collection of
resequenced lines (e.g. new assembly)
• Higher quality variants found are
overlapping with BWA/GATK results.
• Fast mapping and calling makes it
possible to do parameter sweeps.
• This enables assembly or project specific
pipeline fine tuning .

35. Wrap-up (continued)
• GAR file is a very efficient format.
• GAR plugin for IGV and GAR-API
available.
• INDELs called up to 126 bases.
• Structural Variation detection is under
development.
• RNA-Seq mapping functionality
available, not yet tested at Rijk Zwaan.

36. Acknowledgements
Mar<jn van Elk
Bioinforma<cs group Tim Karten
Bas Tolhuis