Argonne National Laboratory

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1 The Use of ORACLE in Discovery of Distant Protein Sequence Similarities th Oracle Life Sciences Users Group Meeting June -, 00 Reston, VA Gyorgy Babnigg, Ph.D. Biosciences Division Protein Mapping Group Argonne National Laboratory A Laboratory Operated by The University of Chicago

2 Outline LIMS Data integration ORACLE0g Public interfaces Oracle 9. (Win00) Oracle 0 (RHEL ES.) Cluster computing Perl, ASP, C#, Java, C

3 Proteome Analysis Which proteins are expressed by a biological system under a given condition and point in time? Genome Condition Potential proteome Condition

Two-Dimensional Gel Electrophoresis (DE)

4 Two-Dimensional Gel Electrophoresis (DE) First dimension Second dimension Isoelectric focusing (ISO) ph NEPHGE ph 7 High MW Low ph High ph Low MW D liquid chromatography st dimension nd dimension

5 Analysis Peak detection Warping and matching Reports XML 5

6 Analysis Interface Front-end Back-end Interface with LIMS Gel Clustering ORACLE0g integration Export into ORACLE0g Statistical analysis Analysis interface ORACLE0g integration of final data 6

7 Statistical Analysis, Spot Visualization, and Reporting 0.5 7. 0. 9 55 7 8.5 7.6 05 0.0009 m 879 0.5 9 9. 0 7. 5. 9 7 0.

0 9 7.8. 8 5 6 0.000795 m 9. 7.8 9.5 76 0 5.5 5. 0.000578 m 5.7 05..6 8 96 78 6. 0 58 0.0005006 m 86.8 8. 56 5. 0. 8 8 0.

9. 7 9 8.567E-05 m 897 0.6 8. 7.9 0 55 68.6 6 9 5.

7 7 Statistical Analysis, Spot Visualization, and Reporting m m m m m m m m m m m m E-05 m E-05 m 75 Rati o Gels( ) STD CV Vol Gels( ) STD CV Vol Student t- test M Spot # KALL_DAK_IBU_0 Date: 09//0 Normalised Spot volume ORACLE0g Objects Images LIMS XML Scanner GUI

8 Gel Profiling (MW and pi) Propagation of profiling information Profiling based on cluster information Statistics for individual gels 8

9 Mass Spec Sample Annotation 9

10 Final Display 0

Expression Display Display of DE pattern: Ratioed image of groups of gels Display abundance Display position Display significant changes Color code

11 Expression Display Display of DE pattern: Ratioed image of groups of gels Display abundance Display position Display significant changes Color code changes Collection of ORFs with expression data: ORF Change MJ8 0. MJ MJ Gateway to: Averaged gel display Gene clusters KEGG metabolic pathways

12 Gene Clusters and Metabolic Pathways

13 LIMS Shewanella oneidensis: Oak Ridge National Laboratory Jet Propulsion Laboratory Pacific North-West Laboratory Geobacter sulfurreducens University of Massachusetts Methanococcus jannaschii University of Illinois Pyrococcus furiosus University of Georgia Protein Mapping Group (ANL) DE Quantification Samples for Mass Spec Mass spectrometry: Scripps Institute (John Yates) PNL ORNL Other collaborators: University of Chicago Argonne National Laboratory Integration of Data Display of data Internet

significant changes collaborators 00 samples 7000 gels (7 million spots) 0 experiments (750 gels) 500 identifications Intranet

14 PMG LIMS Samples from collaborators Sample preparation (denatured, native, membrane, etc) Separation First dimension Second dimension Staining Analysis Change of protein expression profile upon treatment Mass spec Identification of ORFs with significant changes collaborators 00 samples 7000 gels (7 million spots) 0 experiments (750 gels) 500 identifications Intranet sites (web-accessible). Sample and gel catalog (accessible to our collaborators). Statistical analysis (accessible to BIO domain users only)

15 Accounts Site B Site A Site C Web service Users Ontologies. Check session Web service. Try to utilize service Site E. Session. Digest service Site D 5

16 PMG Intranet Accounts 6

Permissions for Tables and Entries sample condition sample condition sample condition sample condition 5 sample5 condition5 6 sample6 condition6 7 sample7 condition7 8 sample8 condition8 9 sample9

17 Permissions for Tables and Entries sample condition sample condition sample condition sample condition 5 sample5 condition5 6 sample6 condition6 7 sample7 condition7 8 sample8 condition8 9 sample9 condition9 0 sample0 condition0 sample condition sample condition sample condition sample condition 5 sample5 condition bit entries (create, edit, and read) for: Groups Users Using BITAND for query 7

18 Easier Data Entry 8

19 Data Provenance/History 9

20 Strict Control of Data Entry. Search taxonomy DB. Insert species, strain, genotype. Color code. Validation in ORACLE 5. Insert (taxonomy ID) 0

21 Public and Private Databases

22 Control of Data Integration

23 Process Matrix and Performance Queries

24 Control of Certain Processes. Process can not start (approval req.). Send to my cell phone w/limited info. sent back (OK). Process checks for reply 5. Process proceeds

25 Discovery of Distant Relationships PSI-BLAST with lose parameters Large files Long execution times (e.g. result set can have entries, E = 0) 5

26 PSI-BLAST (first iteration) 6

27 PSI-BLAST (third iteration) rd iteration nd iteration ~,900,000 sequences Exponential growth N problem > 00 CPU years Collaboration with MCS Linux clusters (Chiba, Jazz, RC) 7

28 Traditional Cluster Computing. Distribution of jobs (equally). Job execution and output storage (local or global FS). Collection of output 8

29 Correlation of Result File Size and Query ORF Length File Size Tri-Psi run time Size of File (Byte) 0,000,000 5,000,000 0,000,000 5,000,000 0,000,000 5,000,000 0,000,000 5,000, ORF Length Time (s) ORF length Tri-Psi Results Tri-Psi run time on Chiba size (byte) 0,000,000 8,000,000 6,000,000,000,000,000, ORF length time (s) ORF length 9

30 Cluster Computing Using ORACLE0g HTTP (SQLNet) ORACLE 0g Individual jobs Monitoring 0

31 Web Services and the Linux Clusters Win00 Web Services Chiba City (56 nodes) SOAP/XML Jazz Cluster (0 nodes) ORACLE 0g SOAP/XML HTTP RCN Cluster (0 nodes) /7 Linux Web Services

32 Comparison of NR and NRSHA Databases File sizes Blastpgp execution time File size (MB) nr nrsha Execution time (s) nr nrsha Database type Blast database file sizes 0 0 Number of iterations Size of blastpgp output File size (MB) nr nrsha File size (MB).5 nr nrsha nr.phr nr.pin nr.pnd nr.pni nr.psd nr.psi nr.psq Processed files 0 Number of iterations

33 Compression of PSI-BLAST Results Compression Ratio Compression n = 75 average compression = Compression Ratio 5 sha gzip 9 gzip Compression Size of Original File (kbytes) Size of Original File (Mbytes)

34 On-line Queries (REGEX) 8 ORACLE 0g nodes 60 CPUs

35 REGEX Performance Performance comparison Regex performace 760 lines 9. MB Execution time seedtop perl Linear (seedtop) Linear (perl) Processing time (s) Number of sequences searched y = E-05x R = y = E-06x R = Java Method used Perl NCBI seedtop Java Intel P.6MHz RH 7. 5

36 REGEX Search Strategy Execution time of REGEX search (one slice) Read line Line REGEX Line REGEX verified Getting indeces Push into array Print result to file Call subroutine Count inserted into ORACLE (path) Read result from file Insert into ORACLE count (path) Time (s) ORACLE Insert (with UQ) ORACLE Insert (w/o UQ) Step RH7. RH

37 ORACLE-based Cluster Monitoring 7

RC Linux Cluster BLAST searches/minute.0.5.0.5.0.5.0 0.5 0.

cost 0 8 6 0 omics ccn matrix rcn0 rcn rcn searches/min/$000 Node name CPU Memory Disk Price omics P.

38 RC Linux Cluster BLAST searches/minute omics ccn matrix rcn0 rcn rcn searches/minute Throughput vs. cost omics ccn matrix rcn0 rcn rcn searches/min/$000 Node name CPU Memory Disk Price omics P.8Ghz.5G 5krpm SCSI $055 ccn xp 500Mhz 500M RAM.6krpm SCSI $6 matrix P 00Mhz G RAM 6krpm IDE $ rcn0 P 50Mhz 8M RAM 7.krpm IDE $ rcn P 66Mhz 0M RAM 5krpm IDE $6 rcn 86/Mhz 0M RAM 5krpm IDE $55 8

39 Rich Clients Secure Web Service 8 bit Application update Windows XP (.NET) Secure Web Service 8 bit session Secure Web Service 8 bit ORACLE 0g Secure Web Service 8 bit Remote update of application 0 kb 9

40 Acknowledgements This research is funded by the U. S. Department s Office of Biological and Environmental Research (under Contract No. W--09-ENG-8). Jeremy Weatherford Carol Giometti Fred Stevens Sandra Tollaksen Tripti Khare 0

Data management for Proteomics ABRF 2005

MASCOTIntegra Data management for Proteomics 1 Mascot Integra: Data management for proteomics What is Mascot Integra? What Mascot Integra is not Security and Electronic signatures in Mascot Integra Instrument