Handling next generation sequence data
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1 Handling next generation sequence data a pilot to run data analysis on the Dutch Life Sciences Grid Barbera van Schaik Bioinformatics Laboratory - KEBB Academic Medical Center Amsterdam
2 Very short intro on high throughput sequencing Sanger sequencing High throughput sequencing
3 DNA building blocks >chr1 taaccctaaccctaaccctaaccctaaccctaaccctaaccctaacccta accctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaac cctaacccaaccctaaccctaaccctaaccctaaccctaaccctaacccc taaccctaaccctaaccctaaccctaacctaaccctaaccctaaccctaa ccctaaccctaaccctaaccctaaccctaacccctaaccctaaccctaaa ccctaaaccctaaccctaaccctaaccctaaccctaaccccaaccccaac cccaaccccaaccccaaccccaaccctaacccctaaccctaaccctaacc ctaccctaaccctaaccctaaccctaaccctaaccctaacccctaacccc taaccctaaccctaaccctaaccctaaccctaaccctaacccctaaccct aaccctaaccctaaccctcgcggtaccctcagccggcccgcccgcccggg tctgacctgaggagaactgtgctccgccttcagagtaccaccgaaatctg tgcagaggacaacgcagctccgccctcgcggtgctctccgggtctgtgct gaggagaacgcaactccgccggcgcaggcgcagagaggcgcgccgcgccg gcgcaggcgcagacacatgctagcgcgtcggggtggaggcgtggcgcagg cgcagagaggcgcgccgcgccggcgcaggcgcagagacacatgctaccgc gtccaggggtggaggcgtggcgcaggcgcagagaggcgcaccgcgccggc gcaggcgcagagacacatgctagcgcgtccaggggtggaggcgtggcgca ggcgcagagacgcaagcctacgggcgggggttgggggggcgtgtgttgca ggagcaaagtcgcacggcgccgggctggggcggggggagggtggcgccgt gcacgcgcagaaactcacgtcacggtggcgcggcgcagagacgggtagaa cctcagtaatccgaaaagccgggatcgaccgccccttgcttgcagccggg cactacaggacccgcttgctcacggtgctgtgccagggcgccccctgctg gcgactagggcaactgcagggctctcttgcttagagtggtggccagcgcc ccctgctggcgccggggcactgcagggccctcttgcttactgtatagtgg tggcacgccgcctgctggcagctagggacattgcagggtcctcttgctca aggtgtagtggcagcacgcccacctgctggcagctggggacactgccggg ccctcttgctccaacagtactggcggattatagggaaacacccggagcat ATGCTGTTTGGTCTCAgtagactcctaaatatgggattcctgggtttaaa agtaaaaaataaatatgtttaatttgtgaactgattaccatcagaattgt actgttctgtatcccaccagcaatgtctaggaatgcctgtttctccacaa agtgtttacttttggatttttgccagtctaacaggtgaagccctggagat 3 tcttattagtgatttgggctggggcctggccatgtgtatttttttaaatt tccactgatgattttgctgcatggccggtgttgagaatgactgcgcaaat
4 Sanger sequencing Mix of "standard" nucleotides and labelled dideoxynucleotides (chain-terminating nucleotides) Gel or capillary sequencing One sequence at the time Robots: up to 384 samples in one run Bentley 2006, Curr opinion in genetics
5 Overview sequencing methods Synthetic chain-terminator chemistry (Sanger sequencing) Sequencing by hybridisation Pyrosequencing Base-by-base sequencing by synthesis Sequencing by ligation Nanopore technology Single-molecule sequencing by synthesis in real time
6 People and labs Sequence facility Marja Jakobs Ted Bradley Frank Baas Laboratory Division Bioinformatics laboratory - KEBB Angela Luyf, Silvia D Olabarriaga Tristan Glatard Barbera van Schaik Antoine van Kampen Roche (454) sequencer
7 Pyrosequencing - Roche FLX (454) Sample preparation Nature Methods 2007 advertisement 454.com
8 Pyrosequencing - Roche FLX (454) Sequencing process Nature Methods
9 Pyrosequencing - Roche FLX (454) Summary One sequence per bead Amplification in oil/water emulsion Fix bead in container (picotiterplate) Put plate with containers in machine Wash one nucleotide at the time over plate -> light emission Take picture Wash next nucleotide over plate Nature Methods 2008 and 454.com
10 Data pre-processing Binary to Fasta CACTC TGCGT >seqa CACTC CAGGA AACAG CGACA TGCGT >E9108QN01BVB2T length=238 xy=0649_3411 region=1 run=r_2008_05_06_17_51_52_ CACTCCAGGAAACAGCTATGACCTCTGCCTGGAAAGCCAGGTGCCTGTGGGCAGAGCCCA GGACCACAGGGCCAGGGGTATCTCGTGTTCCTGTCCTGGCCGCGGATCTTCTTCTCCATC TCAGCGTCTGTCAGAGTCTCCAGCAGTGGGCACCACTGGTCCGCATCGCCCGTGTTCCGG ATGGCAATCTCCACTGTGGGCAGAGGGTTCTCGCTACGAGGAGGGAGGCAGTGAGAGG
11 Further analysis Mutation detection: BLAST against reference Virus discovery: BLAST against virus database Gene expression: BLA(S)T against gene reference set Chip-on-sequencing: BLA(S)T against genome sequence Pre processing BLAST Quality check BLAT Feature count
12 High throughput sequence data explosion One sequence run: 2 GB (>400,000 reads) Per day: 6 GB (1,200,000 reads) Per week (5d): 30 GB (6,000,000 reads) Per year: 1500 GB (312,000,000 reads) This becomes worse when the Roche system is upgraded!
13 Pilot: run bioinformatics tools on the Grid Experience with earlier projects Many computation intensive tasks This pilot: BLAST as (small) test case Advantages of Grid Sharing of data storage and computing power Parallel computing (multiple jobs at same time) Disadvantage of Grid Complex system to work with Currently bioinformatician friendly systems are available End-user interface for Grid usage Workbench for building workflows System to run workflows on the Grid
14 Outline Components Dutch Life Sciences Grid VBrowser Workflows Taverna Moteur GASW webservices Interaction between the components Discussion Experiences so far and considerations Wish list for Life Sciences Grid Current status and future work
15 Interaction between the components Taverna workflow management system export import Scufl file (XML) VBrowser lsgrid
16 Virtual Laboratory for escience Bioinformatics
17 Dutch Life Sciences Grid Roll out GRID infrastructure in the Netherlands Sharing of data storage and computer power
18 VBrowser SARA AMC
19 Workflows We want to create a bioinformatics pipeline for sequence analysis Modular building blocks that perform a single task Connect blocks to create a program Sequence files Pre-processing BLAST BLAST files
20 Taverna
21 Workflow management systems Difference between Taverna and Moteur Sequence files Sequence files AMC Pre-processing Pre-processing Job on Grid node BLAST BLAST NCBI BLAST files BLAST files Job on Grid node
22 Generic Application Service Wrapper (GASW) Configuration files (XML) GASW services
23 Example config file for wrapping a perl script with GASW <description> <executable name="sff2fasta.pl"> <access type="lfn"/> <value value="/grid/lsgrid/angela/sequence_wf/michel_28_10_2008/perlscripts/sff2 fasta.pl"/> <input name="tarfile" option="no0"> <access type="lfn"/> </input> <input name="sfffile" option="no1"> <access type="lfn"/> </input> <output name="out_sff2fasta.txt" option = "no2"> <template value="/grid/lsgrid/angela/sequence_wf/michel_28_10_2008/sff2fasta_out/%s _fasta.fna"/> <access type="lfn"/> </output> <output name="out_sff2fasta.txt" option = "no3"> <template value="/grid/lsgrid/angela/sequence_wf/michel_28_10_2008/sff2fasta_out/%s
24 Interaction between the components Taverna workflow management system export import Scufl file (XML) VBrowser Grid certificate: I am me lsgrid
25 Screenshot VBrowser/Moteur (1)
26 Screenshot VBrowser/Moteur (2) 26
27 Outline Components Dutch Life Sciences Grid VBrowser Workflows Taverna Moteur GASW webservices Interaction between the components Discussion Experiences so far and considerations Wish list for Life Sciences Grid Current status and future work
28 Experiences so far and considerations Request certificate for the Life Sciences Grid Learn how all components work Wrap our applications for use in Grid workflows Ship databases and blast executables to the Grid
29 Wish list for Life Sciences Grid related to sequence analysis Public databases GenBank Bioinformatics tools BLAST EMBOSS BioPerl
30 Outline Components Dutch Life Sciences Grid VBrowser Workflows Taverna Moteur GASW webservices Interaction between the components Discussion Experiences so far and considerations Wish list for Life Sciences Grid Current status and future work
31 Status Current status Wrapped with GASW: Perl scripts for pre-processing of Roche sequence data BLAST and BLAT Build a workflow of these components in Taverna Ran workflow successfully on the Life Sciences Grid with Moteur Future work Submit workflows for multiple sequence runs Real (computation intensive) application Examine how we can build a system for end-users NBIC Bioassist - sequencing platform
32 Angela Luijf Bioinformatics Laboratory Tristan Glatard Creatis-LRMN Lyon France Barbera van Schaik Bioinformatics Laboratory Silvia D Olabarriaga Bioinformatics Laboratory s.d.olabarriaga@amc.nl Frank Baas Neurogenetics Sequencing facility f.baas@amc.nl Antoine van Kampen Bioinformatics Laboratory a.h.vankampen@amc.nl
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