BITs: Genome browsers and interpretation of gene lists.
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Module 5 Genome browsers and interpreting gene lists.

Module 5 Genome browsers and interpreting gene lists.

Part of training session "Basic Bioinformatics concepts, databases and tools" - http://www.bits.vib.be/training

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BITs: Genome browsers and interpretation of gene lists. Presentation Transcript

  • 1.
    • Basic bioinformatics concepts, databases and tools
    • Module 5
    • Genome browsers and
    • interpretation of gene lists
    • Dr. Joachim Jacob
    • http://www.bits.vib.be
    Updated 21 July 2011 http://dl.dropbox.com/u/18352887/BITS_training_material/Link%20to%20mod5-intro_H1_2011_genomebrowsers.pdf
  • 2. Integrating biological information
    • Genome databases and browsers
      • Integration on a species basis all biological information: Ensembl Genome Browser
        • http://www.ensembl.org/
    • Table Browsers
      • Retrieving biological (not only sequence) data applying various criteria: Biomart
    • http://www.biomart.org/
    • Interpreting gene lists
      • 'What is the biology behind my gene list': DAVID
    • http://david.abcc.ncifcrf.gov/
  • 3. Reference genome sequences provide a standard genome sequence per species
    • Genomes
      • From various sequence sources, a genome is assembled
        • By NCBI: currently assembly 37 in human (or 'build') (2010)
        • By Celera: commercial
      • Each build differs!
        • 1. Data freeze: all data for assembling (ignoring new data from that point)
        • 2. Assembly process and annotation
        • 3. Release of the Build: Reference Sequence Genom e
    http://www.ncbi.nlm.nih.gov/Genomes/
  • 4.  
  • 5. Finding your way in genomes
    • Annotation and terms
        • See also NCBI handbook
      • Locus = place on the genome, ~ a gene (different alleles)
      • Location:
        • Rough location by staining of chromosomes e.g. 18q12.1 -> chromosome 18, long arm (=q, small arm is p)
        • Exact bases on genomes (assembly must be mentioned!)
  • 6. Genome Browsers: main players
    • Three main players
      • MapViewer (NCBI)
      • UCSC Genome Browser
      • Ensembl Genome browser
    BITS UCSC Genome Browser training BITS Ensembl Genome Browser training
  • 7. Ensembl Genome browser
    • We will use this browser in this session
      • Information is combination of automatic annotation and manually curated s ources (ENS >< Havana (Vega) genes)
      • All entries can be accessed through the browser, each with its own clear identifiers
  • 8. 28 November 2009 [email_address] /10 http://www.ensembl.org Information about the genomes
  • 9. http://www.ensemblgenomes.org
  • 10. [email_address] /10 ! … or click on the figure feature!
  • 11. 28 November 2009 [email_address] /10
  • 12. 28 November 2009 [email_address] /10 [email_address]
  • 13. TAB SUMMARY DETAILED INFORMATION INFOR-MATION SELEC-TOR DATA MANAGER tab DAS
  • 14. Ensembl Genome browser
    • Usefulness:
      • One place for all information on a particular gene / structure / location / variation
      • But also:
        • Comparison to other species
    • The Ensembl Team has a lot of training movies and examples available. Check them out!
    http://www.ensembl.org/info/index.html http://www.ensembl.org/Help/Movie?id=188
  • 15. Ensembl Genome browser
    • Usefulness:
      • One place for all information on a particular gene / structure / location / variation
      • But also:
        • Comparison to other species
    • The Ensembl Team has a lot of training movies and examples available. Check them out!
    http://www.ensembl.org/info/index.html http://www.ensembl.org/Help/Movie?id=188
  • 16. Tracks are a way to display information on a genome sequence
    • The annotation on a genome-wide scale is displayed in tracks.
      • Relevant database content can be formatted in tracks and displayed on a reference genome
    Genome reference tracks Screenshot of Ensembl genome browser
  • 17. Tracks are a way to display information on a genome sequence
    • The annotation on a genome-wide scale is displayed in tracks, most used formats:
      • - each base receives a value: dense continuous data: WIG format (e.g. %GC)
      • - annotation has a start and a stop coordinate: bed format (e.g. gene annotations)
    • Example
      • Variations in genomes are reported in vcf format
    http://www.ensembl.org/info/website/upload/bed.html http://www.bits.vib.be/wiki/index.php/.vcf #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT 20 14370 rs6054257 G A 29 PASS NS=3;DP=14;AF=0.5;DB;H2 GT:GQ:DP:HQ 20 17330 . T A 3 q10 NS=3;DP=11;AF=0.017 GT:GQ:DP:HQ
  • 18. Biomart, your one stop portal to fetch information
    • Biomart http://www.biomart.org/
      • These questions are easy:
    Hey, can you tell me how many genes in mouse exist which regulate transcription and are located on Chromosome 19 ?
  • 19. Biomart, your one stop portal to fetch information
    • Biomart http://www.biomart.org/
      • These questions are easy:
    Hey, can you tell me how many genes in mouse exist which regulate transcription and are located on Chromosome 19 ? Ensembl Genes Genome sequence (Ensembl) Gene Ontology GO:0009299
  • 20. Biomart, your one stop portal to fetch information
    • Biomart http://www.biomart.org/
    Translated questions reflect in database choice and Filters Resulting genes are counted and the output set via Attributes
  • 21. Biomart is available for an increasing number of databases
    • Biomart
      • http://www.biomart.org/
  • 22. Gene lists resulting from different analyses can reveal their biology
    • DAVID - http://david.abcc.ncifcrf.gov/
  • 23. Gene lists resulting from different analyses can reveal their biology
    • DAVID - http://david.abcc.ncifcrf.gov/
    DEMO Alternatives g:Profiler http://biit.cs.ut.ee/gprofiler/ Babelomics http://www.babelomics.org/
  • 24. Galaxy allows you to store your data and to (re)analyse it conveniently
    • Galaxy - http://usegalaxy.org
  • 25. Galaxy allows you to store your data and to (re)analyse it conveniently
    • Galaxy - http://usegalaxy.org
    DEMO TOOLS RESULTS DATA SETS