Microarray Dataset: quick miningand gene profile analysis usingonline toolsDr. Etienne Z. GNIMPIEBASioux Falls, March 2013...
Plan Gene expression measurement Microarray process Gene expression data stores Data mining / quering Data analysis ...
Gene expressionmeasurementHigher-plex techniques:SAGEDNA microarrayTiling arrayRNA-SeqNGSLow-to-mid-plex techniques:Report...
What is a Microarray?“A DNA microarray is a multiplex technologyconsisting of thousands of oligonucleotidespots, each cont...
Hypotheses Microarrays are usually hypothesis-generating:◦ They highlight specific genes or features that areparticularly...
Microarray process (1/3)• Image analysis(genepix)• Normalization (R)• Pre-treatment• Differential expression• Clustering• ...
Microarray process (2/3)
Microarray process (3/3)High densityfilters(macroarrays)Glass slides(microarrays)OligonucleotideschipsDetail: Detail: Deta...
Gene expression datamanagementDatabaseMicroarrayExperimentSetsSampleProfilesDate ReportedArrayExpress at EBI 24,838 708,91...
Data mining / querying Problem specification Query Extraction Storage Load Pretreat / prepare for analysis
Data analysis (1/3) Question-Answer◦ Experimental condition profile: groupcomparison◦ Annotation profile: systems biologi...
Data analysis (2/3) 3 Questions◦ What is the right dataset (experimental condition)?◦ Is dataset is ready for analysis (q...
Data analysis (3/3)Boxplot
Example: ATP13A2 profile in stressconditions Specification: ATP13A2 profile instress conditions Data querying:◦ GEO◦ Arr...
Significant differential expression!!!Kerry Bemis slides
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Session ii g1 overview genomics and gene expression mmc-good

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  • I can not say that I'm into Statistician 20 min. I give you just a few items to give rapid analysis of microarray.
  • The following experimental techniques are used to measure gene expression and are listed in roughly chronological order, starting with the older, more established technologies. They are divided into two groups based on their degree of multiplexity.
  • The following experimental techniques are used to measure gene expression and are listed in roughly chronological order, starting with the older, more established technologies. They are divided into two groups based on their degree of multiplexity.
  • The following experimental techniques are used to measure gene expression and are listed in roughly chronological order, starting with the older, more established technologies. They are divided into two groups based on their degree of multiplexity.
  • ArrayTrack™ provides an integrated solution for managing, analyzing, and interpreting microarray gene expression data. Specifically, ArrayTrack™ is MIAME (Minimum Information About A Microarray Experiment)-supportive for storing both microarray data and experiment parameters associated with a pharmacogenomics or toxicogenomics study. Many statistical and visualization tools are available with ArrayTrack™ which provides a rich collection of functional information about genes, proteins, and pathways for biological interpretation.  The primary emphasis of ArrayTrack™ is the direct linking of analysis results with functional information to facilitate the interaction between the choice of analysis methods and the biological relevance of analysis results. Using ArrayTrack™, users can easily select a statistical method applied to stored microarray data to determine a list of differentially expressed genes. The gene list can then be directly linked to pathways and gene ontology for functional analysis.
  • Boxplots are useful for determining where the majority of the data lies
  • Session ii g1 overview genomics and gene expression mmc-good

    1. 1. Microarray Dataset: quick miningand gene profile analysis usingonline toolsDr. Etienne Z. GNIMPIEBASioux Falls, March 2013Etienne.gnimpieba@usd.edu
    2. 2. Plan Gene expression measurement Microarray process Gene expression data stores Data mining / quering Data analysis Example: ATP13A2 profile in stressconditions
    3. 3. Gene expressionmeasurementHigher-plex techniques:SAGEDNA microarrayTiling arrayRNA-SeqNGSLow-to-mid-plex techniques:Reporter geneNorthern blotWestern blotFluorescent in situhybridizationReverse transcription PCR
    4. 4. What is a Microarray?“A DNA microarray is a multiplex technologyconsisting of thousands of oligonucleotidespots, each containing picomoles of aspecific DNA sequence.” Used to quantitate mRNA or DNA Many applications:◦ mRNA or DNA levels◦ SNP identification◦ ChIP-on-Chip
    5. 5. Hypotheses Microarrays are usually hypothesis-generating:◦ They highlight specific genes or features that areparticularly interesting for follow-up experiments◦ There are many interesting exceptions Biomarkers Pathway analyses This does not reduce the importance ofexperimental design◦ the low statistical power of array studies make gooddesign even more important and very challenging
    6. 6. Microarray process (1/3)• Image analysis(genepix)• Normalization (R)• Pre-treatment• Differential expression• Clustering• Data mining• Annotation
    7. 7. Microarray process (2/3)
    8. 8. Microarray process (3/3)High densityfilters(macroarrays)Glass slides(microarrays)OligonucleotideschipsDetail: Detail: Detail:Size: 12cm x 8cm Size: 5,4cm x 0,9cm Size: 1,28cm x 1,28cm•2400 clones bymembrane•radioactive labelling•1 experimentalcondition by membrane•10000 clones by slide•fluorescent labelling•2 experimentalconditions by slide•300000oligonucleotides byslide•fluorescent labelling•1 experimentalcondition by slide
    9. 9. Gene expression datamanagementDatabaseMicroarrayExperimentSetsSampleProfilesDate ReportedArrayExpress at EBI 24,838 708,914 October 28, 2011ArrayTrack™ 1,622 50,953 February 11, 2012caArray at NCI 41 1,741 November 15, 2006Gene Expression Omnibus -NCBI25,859 641,770 October 28, 2011Genevestigator database 2,500 65,000 January 2012MUSC database ~45 555 April 1, 2007Stanford Microarray database 82,542 Not reported October 23, 2011UNC Microarray database ~31 2,093 April 1, 2007UNC modENCODE Microarraydatabase~6 180 July 17, 2009UPenn RAD database ~100 ~2,500 September 1, 2007UPSC-BASE ~100 Not reported November 15, 2007SAGEGEOGUDMAP (421)MGIBIOGPS
    10. 10. Data mining / querying Problem specification Query Extraction Storage Load Pretreat / prepare for analysis
    11. 11. Data analysis (1/3) Question-Answer◦ Experimental condition profile: groupcomparison◦ Annotation profile: systems biological involved◦ Clustering profile: co-regulation◦ Time course profile: time variation◦ … Descriptive◦ Boxplot (SD, MEAN, MEDIAN, )◦ Scatter plot Predictive / inference (clustering) Modeling (machine learning, simulation)
    12. 12. Data analysis (2/3) 3 Questions◦ What is the right dataset (experimental condition)?◦ Is dataset is ready for analysis (quality)?◦ What is the expression profile for a given gene?◦ Significant differential expression in groupscomparison Tools◦ ArrayExpress (EBI)◦ Boxplot◦ GEO2R (LIMMA, profile graph,)◦ ….
    13. 13. Data analysis (3/3)Boxplot
    14. 14. Example: ATP13A2 profile in stressconditions Specification: ATP13A2 profile instress conditions Data querying:◦ GEO◦ Array Express◦ Gene Atlas Data analysis:◦ Online: GEO2R, Genospace, …◦ Desktop: R, ArrayTrack, …
    15. 15. Significant differential expression!!!Kerry Bemis slides

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