Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Massive parallel processing of public high-thro...
Search
Tazro Inutano Ohta
July 22, 2014
Science
340
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Massive parallel processing of public high-throughput sequencing data and experiment of sharing data analysis environment
NIG/DDBJ supercomputer user meeting at National Institute of Genetics
Tazro Inutano Ohta
July 22, 2014
More Decks by Tazro Inutano Ohta
See All by Tazro Inutano Ohta
Yevis: System to support building a workflow registry with automated quality control
inutano
0
160
Standardization of biological sample information database
inutano
0
110
Describe data analysis workflow with workflow languages
inutano
5
6.2k
Container virtualization technologies and workflow languages improve portability and reproducibility of data analysis environment
inutano
3
380
次世代シーケンサーによるメタゲノム解析:桜の花びらに付着した環境DNAを解析する
inutano
0
130
Workflows that run everywhere and where to run them
inutano
0
200
The Sequence Read Archive search system to make use of public high-throughput sequencing data
inutano
0
330
Improve portability of bioinformatics software across HPC and cloud infrastructures
inutano
1
150
Container, Cloud, and HPC
inutano
0
200
Other Decks in Science
See All in Science
Inside the Mind of an LLM
baggiponte
0
200
AIを用いた PID制御で部屋 の温度制御をしてみた
nearme_tech
PRO
0
180
プロジェクト「Azayaka」のSARの数式とジオメトリ
syuchimu
0
380
20260220 OpenIDファウンデーション・ジャパン ご紹介 / 20260220 OpenID Foundation Japan Intro
oidfj
0
380
Cross-Media Technologies, Information Science and Human-Information Interaction
signer
PRO
3
32k
TypeScript で WebAssembly を用いた 型安全なプラグイン設計
nagano
2
570
データベース01: データベースを使わない世界
trycycle
PRO
1
1.3k
コーヒー豆様核 (Coffee-bean nuclei) における形態学的サブタイピングと精選・焙煎特性の同定
jagupath
PRO
0
120
水耕栽培を始める前に知っておきたい植物の科学
grow_design_lab
0
270
Van Dare naar Durf
voginip
0
260
機械学習 - 決定木からはじめる機械学習
trycycle
PRO
0
1.6k
CVPR2026_VGGTとその仲間たち
mickey_0226
0
980
Featured
See All Featured
How to Ace a Technical Interview
jacobian
281
24k
Intergalactic Javascript Robots from Outer Space
tanoku
273
27k
Paper Plane
katiecoart
PRO
2
52k
ラッコキーワード サービス紹介資料
rakko
1
3.9M
RailsConf 2023
tenderlove
30
1.5k
Agile Actions for Facilitating Distributed Teams - ADO2019
mkilby
0
220
A designer walks into a library…
pauljervisheath
211
24k
The Cost Of JavaScript in 2023
addyosmani
55
10k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
123
22k
SEO Brein meetup: CTRL+C is not how to scale international SEO
lindahogenes
1
2.8k
jQuery: Nuts, Bolts and Bling
dougneiner
66
8.5k
Have SEOs Ruined the Internet? - User Awareness of SEO in 2025
akashhashmi
0
400
Transcript
େྔ/(4σʔλͷฒྻॲཧͱڞ༻εύίϯʹ͓͚Δڥߏஙͷࠓޙʹ͍ͭͯ ใɾγεςϜݚڀػߏ ϥΠϑαΠΤϯε౷߹σʔλϕʔεηϯλʔ େా ୡ <
[email protected]
> ! prepared for ҨݚDDBJεύίϯϢʔβձ
July 22, 2014
Summary ‣ ҨݚεύίϯΛར༻͠ެ։/(4σʔλશͯʹରͯ͠ όονॲཧΛߦ͍ɼ%#ͷߏஙΛߦ͍ͬͯ·͢ ! ‣ σʔλղੳύΠϓϥΠϯͷڞ༗ɾ࠶࣮ߦΛߦ͏ͨΊͷ 7.ίϯςφΛར༻ͨ͠ڥߏஙͷௐࠪɾ։ൃΛߦ͍ͬͯ·͢
sra.dbcls.jp
‣ ެ։/(4σʔλʹରͯ͠'BTU2$Λ࣮ߦ݁͠ՌΛճऩɾूܭ ‣ %-Մೳͳσʔλશ͕ͯର ‣ ʙొ·Ͱྃ ‣ ૯σʔλ ‣
4FRVFODF3VO TJOHMFPSQBJSFE ‣ ૯σʔλαΠζ ‣ 5 Ԙجର ެ։NGSσʔλͷϦʔυΫΦϦςΟDB
‣ σʔλసૹ ‣ MGUQNHFUʹΑΔ(#ͷσʔλసૹ Y ‣ ಉ࣌ฒྻ࣮ߦ ‣ $16$16
Y طଘܭࢉػڥͱͷࠩ
‣ ιϑτΣΞͷόʔδϣϯཧͷ ‣ ڞ༻ڥͰΠϯετʔϧ͕͍͠߹͋Δ ‣ ݱঢ়౦େּݪ͞Μͷ-1.ΛΘͤͯ͘ͳͲͰճආ ‣ IUUQXXXLBTBIBSBXTMQN ‣ େྔͷσʔλʹରͯ͠ͻͱͭͻͱͭख࡞ۀʁ
՝: จʹॻ͔ΕͨύΠϓϥΠϯΛ࠶ݱ͢Δ͜ͱ͕ࠔ
‣ 7JSUVBM.BDIJOF 7. ίϯςφͰڥ͝ͱղੳύΠϓϥΠϯΛڞ༗ ‣ ΠϝʔδΛల։͙ͯ͢͠ʹղੳΛ࢝ΊΔ͜ͱ͕Ͱ͖Δ ‣ ڥߏஙͱΠϝʔδڞ༗ͷٕज़ௐࠪ։ൃΛߦ͍ͬͯ·͢ ‣ "NB[PO8FC4FSWJDFʹ͓͚Δ".*ͷڞ༗
‣ %PDLFS)VCʹ͓͚ΔίϯςφΠϝʔδͷڞ༗ ‣ ҨݚεύίϯͰ͜ΕΒͱޓੑΛ͍࣋ͨͤͨ σʔλղੳͷ࠶ݱੑΛ୲อ͢ΔͨΊͷղܾࡦ
ίʔυιϑτΣΞͱಉ͡Α͏ʹղੳڥΛެ։/ڞ༗
ίʔυιϑτΣΞͱಉ͡Α͏ʹղੳڥΛެ։/ڞ༗ $ docker run -d -p 8080:80 -t inutano/galaxy
‣ Πϝʔδڞ༗Ͱڥͷґଘ͕ͳ͘ͳΔͱબࢶ͕૿͑Δ ‣ ࣗͰߪೖͨ͠ܭࢉػ ‣ ҨݚεύίϯͳͲͷڞ༻ܭࢉػϦιʔε ‣ "NB[PO8FC4FSWJDF "84 ͳͲͷ*OGSBTUSVDUVSFBTB4FSWJDF
*BB4 ‣ ܾΊखಋೖͷίετͱϚγϯߏɼίετ ‣ "84ͷίετ͕͔ͳΓԼ͕ͬͨͨΊબࢶͱͯ͠ݱ࣮తʹ ‣ ϧʔνϯͳܭࢉҨݚεύίϯͰ ͨͩͳͷͰ ܭࢉػϓϥοτϑΥʔϜͷબ
ॳظಋೖίετ ҡ࣋ίετ ߏͷॊೈੑ ৴པੑ/Ӭଓੑ ൿಗੑ ಛ ݸผಋೖ ✕ ✕ ̋
˚ ̋ ࢿۚ͋Ε੍ͳ͠ ڞ༻ܭࢉػࢿݯ (NIGεύίϯ) ̋ ̋ ˚ ˚ ✕ DDBJͷDBͱ݁ IaaS (Ϋϥυ) ̋ ˚ ̋ ˚ ˚ ඞཁͳ࣌ʹඞཁͳ͚ͩ ίετʑԼ͕Δ ϢʔβࢹͰͷ֤ܭࢉػڥͷϝϦοτൺֱ
Summary ‣ ҨݚεύίϯΛར༻͠ެ։/(4σʔλશͯʹରͯ͠ όονॲཧΛߦ͏͜ͱͰ%#ͷߏஙΛߦ͍ͬͯ·͢ ! ‣ σʔλॲཧղੳύΠϓϥΠϯͷอଘӬଓԽ࠶࣮ߦΛߦ͏ͨΊͷ 7.ίϯςφΛར༻ͨ͠ڥߏஙͱެ։%#ͷௐࠪɾ։ൃΛߦ͍ͬͯ·͢