What are the key challenges in plant genomics? What efficient bioinformatics software technologies can be used to tackle them? The presentation introduces GENALICE MAP product characteristics, its quality of speed, an introduction to the revolutionary Population Calling Module and deployment options. For more information, please visit http://www.genalice.com/product/genalice-map/

1. GENALICE MAP
THE ANSWER TO THE NGS DATA ANALYSIS
CHALLENGES IN AGRICULTURAL BIOTECHNOLOGY
1

2. Today’s journey
▲ Brief company introduction
▲ Specific challenges in plant genomics
▲ Product characteristics
▲ The quality of speed
▲ Introduction Population Calling Module
▲ Deployment options
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3. COMPANY INTRODUCTION
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4. GENALICE organization
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Belfast, NI
Harderwijk, NL

5. 5
The mission

6. World food challenge
Further under pressure if complex DNA diseases become chronic
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2012
7 billion people
20 Gigacalories
2050
9 billion people
40 Gigacalories

7. GENALICE product pipeline
GENALICE LINK
GENALICE MAP
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STORAGE
NEXT-GENERATION
SEQUENCING
SECONDARY ANALISIS DOWNSTREAM ANALYSIS
Hi Seq 2000

8. Standard data processing and analysis approach
to increase speed and shorten analysis time
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9. Key ingredients
▲ Smart new algorithms – optimally making use of the modern hardware architecture
▲ Hidden resource – using the full potential of the hardware
▲ Bare essence – footprint and data stream reduction
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of our high speed data analysis capabilities

10. GENALICE MAP: a NGS data analysis suite
Faster – smaller – better – at lower cost
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Key components Alignment Variant calling Additional functionality:
▲ Population Calling
▲ Structural Variants
Analysis
▲ RNA-Seq mapping &
quantification
Description
Mapping
Individual reads
on right position
Statistical
correction of the
identified variants
Secondary Analysis

11. SPECIFIC CHALLENGES IN PLANT GENOMICS
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12. QUALITY
Plant Genomics
Specific challenges
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A
very
special
breed
COMPLEXITY
Polyploidy
Repetitive
areas
Species
diversity
REFERENCE
None available
Poor quality
Coverage issues
150 GB
SIZE
Storage
costs
Resource
requirements
Time
consuming

13. PRODUCT CHARACTERISTICS
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14. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
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15. Extensive quality validations
▲ Gold Standard (Array data)
▲ Silver Standard (GCAT – Genome in a Bottle data)
▲ True standard (Customer data)
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16. Erasmus University Medical Centre
Gold standard
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17. GIAB – Head to head against widely used workflows
Silver standard
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97.269%
Sensitivity
0% 25% 50% 75% 100%
0% 25% 50% 75% 100%
Precision Rate
Sensitivity
Precision Rate
97.2561%
99.021%
95.431%
98.343%
92.595%
95.852%
44.851%
85.409%
94.990%
95.435%
62.769%
BWA-MEM - GATK HC v3 ISAAC - ISAAC v01_13_06_20 GENALICE MAP v2.3
NovoAlign - GATK HC BWA-MEM - GATK HC v3 GENALICE MAP v2.3
GIAB150xExomedataGIAB30xExomedata

18. GIAB – Head to head against widely used workflows
Silver standard
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19. Customer validation projects in progress
True Standard
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KeyGene Rijk Zwaan
Many others
in Agbio
and Human
Genomics

20. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
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40
80
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160
BWA-MEM/GATK BWA-MEM/Platypus BWA-MEM/VarScan
125x
51x
162x
Speedgain(foldchanges)
30

21. 1101001,00010,000
BWA-MEM/GATK GENALICE MAP
TotalRuntime(minutes)
16:06:49 00:15:42
16:06:49 00:08:28
Over100x faster - from FASTQ to VCF in 8½ minutes*
using a simple general purpose server with a dual Intel Xeon E5 processor
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*NGS data preprocessing for one full tomato genome(40x coverage)
*Whole cultivated tomato genome (40x)

22. Over 100x faster - from FASTQ to VCF in 8 minutes*
using a simple general purpose server with a dual Intel Xeon E5 processor
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*Whole cultivated tomato genome (40x)

23. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
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CRAM

24. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
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Whole cultivated tomato genome (40x)

25. Additional features GAR file
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▲ Mate preservation (paired-end reads)
▲ Real-time re-alignment option
▲ Fast conversion to: SAM, BAM or FASTQ
▲ Direct access 3rd party software through API/plugins

26. All-in-one file
with real-time metrics and meta data
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▲ Mate preservation (paired-end reads)
▲ Real-time re-alignment option
▲ Fast conversion to: SAM, BAM or FASTQ
▲ Direct access 3rd party software through API/plugins

27. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
27

28. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
28

29. Product characteristics
▲ Quality
▲ Speed
▲ Footprint reduction
▲ Ease-of-use
▲ Observational
▲ Full-control
29

30. THE QUALITY OF SPEED
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31. Lycopersicon Neolycopersicon Arcanum Eriopersicon
Mappability depends on the reference genome used
in four different Tomato groups
S. lycopersicum cv Heinz v2.40
Best
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32. Sequential mapping opportunity
In order to increase the total number of mappable reads
Effect of 114-fold speed increase on tomato genome mapping:
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BWA/GATK
0 1 2 3 4 5 6 7 >13 hr
From >13 hour to only 1/2 hour for four different sequential references

33. Large scale projects
80 tomatoes project at KeyGene
SPEED BENEFITS
▲ Major time savings
▲ Major hardware cost savings
▲ Less hassle in planning
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GENALICE MAP used for tomato genome mapping at KeyGene
BWA / GATK – 750 cores
0 1 2 3 4 5 6 7 weeks
From 1.5 months running on 750 cores back to less than one day on 12 cores
ADDITIONAL BENEFITS
▲ Simplified workflow
▲ Opportunity for iterations
▲ Significant storage cost savings

34. The Quality of Speed
Blog post – genalice.com
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35. Cost-effectiveness
Number of nodes needed to process each sequencing run within 8 hours
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36. Cost-effectiveness
Annual electricity cost reduction (in US dollars)
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MAP vs. BWA-MEM/GATK

37. ‘The Green Speed’
Annual CO2 reduction (in tons)
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MAP vs. BWA-MEM/GATK

38. ‘The Green Speed’
Annual number of ‘saved trees’
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MAP vs. BWA-MEM/GATK

39. POPULATION CALLING MODULE
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40. 40

41. 41

42. 42

43. 43

44. 44

45. 45

46. 46

47. Extraordinary fast and linear scalable variant detection
A more than two orders of magnitude speed increase
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340x

48. DEPLOYMENT OPTIONS
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49. VAULT onsite
▲ 1 or 3-Year license based on speed & functionality
▲ Annual maintenance fee of 20%
(Self) service
▲ Offline (service only) and online
▲ Payment per sample analyzed or project
VAULT on cloud (AWS)
▲ Flexible license based on speed & functionality
▲ Annual maintenance fee of 20%
Application via 3rd party platforms
▲ Payment per sample analyzed
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GENALICE MAP deployment options
Now and in the future
Now:
Future:
S

50. Low cost
High speed
High quality