Genomes On Rails

•

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Originally given at RailsConf, this talk outlines how the Wellcome Trust Sanger Institute is using Ruby and Rails as part of their new sequencing platform.

Genomes on Rails
has_many :sequences

Hello

➊
Previously

➋
Production

➌
Process

➊ Previously

The human genome

15 years to decode
3 billion letters

$3 billion

$3 billion ++

Race for the prize

Open data

Open source

Perl

Lots of Perl

Lots of Perl
~4500 modules

Onwards!

40 species

Map evolutionary
space

Compare genomes

compare species
Compare genomes

compare species
Compare genomes

compa re indi viduals

More Perl
~1500 modules

Quantum leap!

1000 personal
genomes

beyond 23andme
1000 personal
genomes

Hypertension

Diabetes

Coronary heart disease

Bipolar disorder

Malaria

➋ Production

Register projects

Register samples

Sample prep

Sequencing

Analysis

Change!

Flexible data capture

Virtual fields

Sample

Name
Organism
Concentration

class Sample < ActiveRecord::Base
has_many :descriptors
has_many :descriptor_values
end

Key value pairs

Faster than you’d think

Change!

V1 V2

Sample Sample

Name Name
Organism Organism
Concentration Concentration
Origin
Quality metric

Rationalize!

V1 V2

Sample Sample

Name Name
Organism Organism
Concentration Concentration
Origin
Quality metric

Mapping!

V1 V3

Sample Sample

Name Name
Organism Species
Concentration Concentration
Origin Origin
Quality metric

Pipeline management

Workﬂow

Task 1 Task 2 Task 3

Name Name Name
Operator Serial number Passed
Instrument Kit

Throughput!

320Tb 450 CPU

320Tb 450 CPU Archive

75 Tb

pilot study!

Multiple apps

Multiple instances

Loosely coupled

Loose coupling is hard

Deployment

Maintenance

Monitoring

Hard to maintain
separation

Support novel science

Single code base

nginx reverse proxy

fairnginx

Mongrel

Fast deployment

Automate everything

Play well with others!

Interoperability!

Legacy databases

RESTful services

Generate API stubs

SCALE!

Trillionics

2 X

150Tb per week

Over 6 months

More hardware

400 additional nodes

additional 360 Tb

Towards a
Virtual Institute

Lots of data

Lots of data, lots of
people

Lots of data, lots of
people, lots of compute

Lots of data, lots of
people, lots of compute,
lots of uses

Lots of data, lots of
people, lots of compute,
lots of uses, lots and lots
and lots and lots...

➌ Process

Concept Requirements Development Product

takes too lon
g
Concept Requirements Development Product

takes too lon
g
Concept Requirements Development Product

the se change

Plan Development

REVIEW Concept

What we need Get ready

Focused

Project owner is key

Weekly releases

More flexible

Less time

Better transparency

Less software

Sequencing informatics

Thank you

GREENISGOOD.CO.UK

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Genomes On Rails

1. Genomes on Rails has_many :sequences

3. ➊ Previously ➋ Production ➌ Process

4. ➊ Previously

5. The human genome 15 years to decode 3 billion letters

7. $3 billion ++

8. Race for the prize

9.

10.

12. Open source

14. Lots of Perl

15. Lots of Perl ~4500 modules

18.

19.

20.

21. Map evolutionary space

22. Compare genomes

23. compare species Compare genomes

24. compare species Compare genomes compa re indi viduals

25. More Perl ~1500 modules

26.

27.

28.

29. Quantum leap!

30. 1000 personal genomes

31. beyond 23andme 1000 personal genomes

32. Hypertension

34. Coronary heart disease

35. Bipolar disorder

37. ➋ Production

38. Register projects Register samples Sample prep Sequencing Analysis

39.

40.

41.

43. Flexible data capture

44. Virtual fields

45. Sample Name Organism Concentration

46. class Sample < ActiveRecord::Base has_many :descriptors has_many :descriptor_values end

47. Key value pairs

48. Faster than you’d think

49.

50.

52. V1 V2 Sample Sample Name Name Organism Organism Concentration Concentration Origin Quality metric

53.

54.

55. Rationalize!

56. V1 V2 Sample Sample Name Name Organism Organism Concentration Concentration Origin Quality metric

58. V1 V3 Sample Sample Name Name Organism Species Concentration Concentration Origin Origin Quality metric

59. Pipeline management

60. Workﬂow Task 1 Task 2 Task 3 Name Name Name Operator Serial number Passed Instrument Kit

61.

62.

63.

64. Throughput!

65.

66. 320Tb 450 CPU

67. 320Tb 450 CPU Archive

68. 75 Tb

69.

70.

71.

72.

73. pilot study!

74. Multiple apps

75. Multiple instances

76. Loosely coupled

77. Loose coupling is hard

79. Maintenance

81. Hard to maintain separation

82. Support novel science

83. Single code base

84. nginx reverse proxy

87. Fast deployment

88. Automate everything

89.

90. Play well with others! Interoperability!

91. Legacy databases

92. RESTful services

93. Generate API stubs

94.

96. Trillionics

97. 2 X

98. 150Tb per week

99. Over 6 months

100. More hardware

101. 400 additional nodes

102. additional 360 Tb

103. Towards a Virtual Institute

104. Lots of data

105. Lots of data, lots of people

106. Lots of data, lots of people, lots of compute

107. Lots of data, lots of people, lots of compute, lots of uses

108. Lots of data, lots of people, lots of compute, lots of uses, lots and lots and lots and lots...

109. ➌ Process

110. Concept Requirements Development Product

111. takes too lon g Concept Requirements Development Product

112. takes too lon g Concept Requirements Development Product the se change

113. Plan Development REVIEW Concept What we need Get ready

115. Project owner is key

116. Weekly releases

117. More flexible

119. Better transparency

120. Less software

121. Sequencing informatics

123. GREENISGOOD.CO.UK