Having a BLAST Data Mining in Oracle 10g:

Transcription

1 Having a BLAST Data Mining in Oracle 10g: Implementing A Bioinformatics Target Database John Burke, Ph.D. UCB Research, Inc.

2 Having a BLAST Data Mining in Oracle 10g Preview UCB Discovery Research Designing the Target Database Building the Target Database Looking Forward

3 UCB Discovery Research

4 UCB Pharma Discovery Research Biology Cl Structure O O N N OH Chemistry 2 HCl

5 UCB Pharma Discovery Research Discovery Research Sites Cambridge? Braine-l Alleud Lille

6 UCB Pharma Discovery Research Bioinformatics, Proteomics, and Genomics

7 UCB Pharma Discovery Research Bioinformatics, Proteomics, and Genomics SAN MALDI-TOF Q-TOF SIMS + ProteinMine GeneXpress Spotfire Sequencher and Omiga GCG and Seqweb Human genome browser (UCSC) Unigene TIGR GeneXpress Proteinscape Mascot Protein Prospector Biotools LS- Graph Protein db Proteome PSD SwisProt Genbank... Custom on Oracle 10g

8 Designing the Target Database

9 Designing the Target Database General Requirements Purpose: Scope: to store and manage target discovery research information efficiently and effectively corporate, global, multi-project, multi-user Content: gene and protein targets and ancillary information Functionality: BLAST search, Web access, Link to other DB and applications

10 Designing the Target Database Searchable fields Image Data Northern Hybridization image Clone alignment MC ENorthern Tissue ENorthern QPCR Western Hybridization 3-D Structure Small molecule hits (link to compound DB?) Text Data Gene name Source of identification EST selected cdna IMAGE clone UniGene Hs.# Transcript size Full-length cdna clone name cdna clone sequences Reading Frame ORF nucleotide number ORF aa Predicted Size Protein Sequence Protein homology Note Protein Function Mouse KO Key Literature

11 Data Model GENEALIAS # GENE_NAME # GENE_SYMBOL represents represents has GENE # GID * EST_SELECTED * GENE_SYMBOL * SOURCEID * UNIGENE_HS_NO o ASSAYID o PROTEINID IMAGE # IMAGEID * COMMENT * GENE_SYMBOL * PICTURE * TYPE has has expresses expressed by CDNA # CDNAID * FULL_LENGTH_CDNA * READING_FRAME * SEQUENCE o ORF_NT_NUMBER o ORF_PREDICTED_SIZE has PROTEIN # PROTEINID * GENE_SYMBOL * PROTEIN_FUNCTION * PROTEIN_HOMOLOGY * SEQUENCE * SOURCEID o COMPONENT o COMPOUNDID involved binds with involved contains contains is from SOURCE # SOURCEID o CELLID o EXPID o LITID o MOUSE_KO is from binds with COMPOUND # COMPOUNDID * COMMENT * COMPOUND_NAME * UCB_NUMBER is is is a CELL # CELLID * CELL_NAME o SPECIES a LITERATURE # LITID o DATE_PUBLISHED o JOURNAL o LIT_AUTHOR o LIT_TITLE o URL a EXPERIMENT # EXPID * RESEARCHER o CHIP o COMMENT o NOTEBOOB_REF o SPECIES involved with PROJECT # PROJECTID * PROJECT_MANAGER * PROJECT_NAME * REVIEW_DATE * STATUS invloved with THERAPEUTIC_AREA * AREA_NAME * FOCUS_GROUP * PROJECTID involved with involved with

12 Designing the Target Database Typical Queries Find all targets similar to this protein with size x in gate y or therapeutic area z. Find all targets with a specified (or unknown) function. Find all targets scheduled to be reviewed on a specified date. Find all projects and targets managed by a given person. Find all targets from Affy study x, or literature search, cell line y or species z.

13 Designing the Target Database Critical Factors in Choosing Oracle 10g Oracle already a UCB standard Confidence in Oracle product and support Smaller resource requirement Shorter development time Inclusion of BLAST in database No need to build interface between DB and BLAST No need to move data from DB to BLAST Ability to execute other queries combined with BLAST

14 Designing the Target Database Core NCBI BLAST Subroutines Subroutine blastp blastn blastx tblastn tblastx Description Compares an amino acid query sequence against a protein sequence database. Compares a nucleotide query sequence against a nucleotide sequence database. Compares a nucleotide query sequence translated in all reading frames against a protein sequence database. You could use this option to find potential translation products of an unknown nucleotide sequence. Compares a protein query sequence against a nucleotide sequence database dynamically translated in all reading frames. Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

15 Designing the Target Database System Architecture Web Client Web Client Web Client Application Server 10G OS: Windows XP Platform: HP Workstation Oracle Database 10G OS: Solaris 8 Platform: Sun Enterprise 250

16

17 Oracle System Components Installed 10g Database Data Mining Option 10g JDeveloper 10gAS Infrastructure Infrastructure database OracleAS Identity Management components OracleAS Metadata Repository 10gAS Middle Tier J2EE and Web Cache Portal

18 N-tiered Application Architecture Client Tier Web Browser Application Server Tier JSP Pages Jakarta Struts Framework BC4J Java Beans Portal EIS Tier Oracle 10g Database BLAST Data Mining

19 JSP Model 2 Architecture MVC Pattern User Action Servlet (Controller) Instantiates Web Browser Response Redirect Java Beans (Model) Data JSP (View) Web Container (Application Server) Oracle 10g Database (Database Server)

20 Page Flow

21 Classes - Jakarta Struts Framework

22 An Issue with SQL in Java Nested IN-Clause Statement failed in Java. OraclePreparedStatement pstmt = (OraclePreparedStatement)conn.prepareStatement("Select genesymbol from proteins where proteinid " + " IN(Select proteinid from projects_proteins where project_projectid " + " IN(Select projectid from projects where status LIKE :1))"); Identical SELECT statement worked in SQL Plus. Equivalent statement implemented as Stored Procedure.

23 An Issue with SQL in Java Equivalent Statement as Stored Procedure SELECT genesymbol FROM proteins,projects,projects_proteins,therapeutic_areas WHERE PROTEINS.PROTEINID = PROJECTS_PROTEINS.PROTEIN_PROTEINID AND PROJECTS_PROTEINS.PROJECT_PROJECTID = PROJECTS.PROJECTID AND PROJECTS.PROJECTID = THERAPEUTIC_AREAS.PROJECTID AND (PROJECTS.status = query OR query IS NULL) AND (THERAPEUTIC_AREAS.AREA_NAME = areaname OR areaname IS NULL) ;

24 JSP interacts with Database via Stored Procedures Use of stored procedures: Centralizes SQL, facilitating reuse Allows the DBA to tune SQL statements Leverages Oracle s dependency tracking mechanism Provides greater security since JSP user unable to directly modify base tables Provides precompiled code Offers better performance Stored procedures load once into the shared pool and remain there unless they become paged out.

25 BLASTN Stored Procedure PROCEDURE "BLASTNTARGETS" IS --DECLARE T_SEQ_ID blastn.t_seq_id%type; SCORE blastn.score%type; EXPECT blastn.expect%type; -- Using the default parameters in Blast CURSOR blastn_cursor is select * from TABLE(BLASTN_MATCH ((select seq_data from targets), CURSOR(select genesymbol,clonesequence from cdnas, genes where genes.cdnaid=cdnas.cdnaid))) t where t.score > 25; BEGIN --OPEN blastn_cursor; OPEN blastn_cursor; --delete the rows in the blastn table DELETE FROM BLASTN; LOOP FETCH blastn_cursor INTO T_SEQ_ID,SCORE,EXPECT; EXIT WHEN blastn_cursor%notfound; INSERT INTO BLASTN VALUES(T_SEQ_ID,SCORE,EXPECT); END LOOP; CLOSE blastn_cursor; END blastntargets;

26 An Issue with 10g AS Attempts to deploy application to AS gave server error. Identifying proper expertise and mode of resolution proved difficult. Teamwork ultimately solved problem. Oracle Life Sciences Oracle Customer Service OLSUG membership Oracle Consulting Practice Solution SIMPLE, but of course NOT OBVIOUS

27 An Issue with 10g AS

28 Request Page

29 BLAST Query Page

30 BLAST Query Page

31 BLAST Result Page

32 Request Page

33 Query Page

34 Query Page

35 Query Result Page

36 Looking Forward

37 Looking Forward Short Term Additional Features and Improvements Data input page Sexy new name for Target Database Integrated BLAST and query Report pages Integration with other systems Long Term Bioinformatics Portal Integrated Knowledge Base

38 UCB Team MIS Prasoon Kejriwal, Cambridge David Wei, Cambridge Bob Johnson, Cambridge Didier Generet, Braine Didier Chalon, Braine Research Karl Nocka, Cambridge Bob Coopersmith, Cambridge Zhidong Zhang, Cambridge Rich Fisher, Cambridge Pierre Chatelain, Braine

39 Special Thanks Prasoon Kejriwal Charlie Berger, Oracle Susie Stephens, Oracle Dev Nayak, Oracle Shiby Thomas, Oracle Shaloo Anand, Oracle Mahendra Navarange, MRC Clinical Sciences