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BarleyBase Quick Tour

This is a quick tour of the major functions of Barleybase. Please click the links, and corresponding pages will pop-up. Do not close this page during your tour. Some of the popup pages may need further action at the page to try out functions on that page. You may download our Power Point tutorial on data analysis and submission work flow.

I. Data Access

1. Sequence-Level Data Access

  • Exemplar Annotation - Annotation of Barley1_11969, exemplar for  Contig11969_at  on Barley1 GeneChip.
  • Probe Set Expression - Expression of Contig11969_at in BB4.
  • BLAST GeneChips - Search the BarleyBase databases for matching exemplars from Barley1. Barley1_11969 exemplar sequence from last page is used  as sample input automatically.
  • Microarray Platform Translator - Matching sequences between platforms, and non-microarray sequences.
2. Experiment-Level Data Access
  • Browse Experiment - Search experiment by names, experiment type and factors, GeneChip type etc. Or select one experiment such as BB4.
  • Actions on an experiment:
    a. Download - Batch download the complete data sets in raw, processed CSV and MAGE-ML formats. You can also download Barley1 GeneChip exemplar and probe sequences.
    b. Browse Hybridizations and view expression boxplots from experiment.
    c. Visualization of hybridizations or treatment means with scatterplots and MvA plots.
    d .Browse Samples from experiment.
    e. Continue to do gene-centric data analysis as detailed in next section.

II. Gene-Centric Data Analysis

This type of analysis is divided into 4 major steps:

1. Create Gene Lists

         Creating Gene Lists with following filters is the first step in most gene-centric analysis.

A. Expression Profile-Based Filters 

They are mainly used to identify differentially-expressed genes (probe sets).

a. Single Experiment Expression Profile Filter -- Work on one experiment a time with a single filter or a composite filter.

b. Cross-Experiment Expression Profile Filter -- Cross-experiment probe set querying.

 B.  Function2Expression -- Gene Functional Annotation to Expression Profile

This is a collection of gene list creation methods, based on several types of gene functional annotations.

a. GO2Expression --  Browse and search Gene Ontology tree, and retrieve probe sets or genes from selected GO classes.

b. Pathway2Expression -- Find probe sets corresponding to enzymes from your interested metabolic or regulatory pathways. Available for the Arabidopsis ATH1 GeneChip only. Based on KEGG and TAIR pathway data.

c. Domain2Expression -- Creates Gene lists corresponding to predicted InterPro protein functional domains. Most of the functional domain information comes from UniProt, TIGR.  For other non-characterized exemplars, BarleyBase conducts in-house annotation on with InterproScan.

d. GeneFamily2Expression -- Find probe sets corresponding to a given gene family. Available for the Arabidopsis ATH1 GeneChip.

f. Keyword2Expression -- Find probe sets matching single or several terms in exemplar annotation.

g. BLAST2Expression-- Finding  probe sets whose exemplars have similarity to your own sequences. Cross-Platform is another form of BLAST2Expression.

 C. Import Gene List

You may input a list of probe sets or exemplar names and retrieve their expression from selected experiment. You can input any free text containing the probe set names.

2. Manage Gene Lists

Manage Gene List-- Management, analysis, visualization, export/import gene list. Compare two gene lists and create new gene list.

3. Pattern Recognition on Gene Lists

Analyze Gene List by Hierarchical Clustering, K-Means partition, Sammon's MDS, PCA, or SOM.

4. View Gene List Analysis Result

View Gene List Analysis Result-- All pattern recognition results are saved automatically for future access.

5. Functional Interpretation of Gene Lists

FuncExpression-- Functional interpretation of large scale gene expression data by gene ontology, pathway.

III. Data Visualization for Different Data Levels

1. Experiment Level Visualization helps in understanding data and in quality assessment:

2. Hybridization Level Visualization by scatter plots and MVA plots to show reproducibility/variability among hybridizations.

3. Gene List Visualization please follow links in II.2, shown as Expression line graph or heatmap for probe sets.

4. Single Gene or Probe Set Visualization: For an example, please view the Contig15950_at page

5. Probe Level Visualization: Bar-plots for raw PM/MM intensities for probes of the probe sets, such as Contig15950_at page.

 

 

 

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