Microsoft Excel and Access

SECTION 1 MICROSOFT EXCEL 547 Part I Introduction  547

1. What Is Microsoft Excel? 547 2. What Can Microsoft Excel Do? 547 3. Featured Functions in Microsoft Excel for Microarray Analysis 548

Part II Step-By-Step Tutorial  550 1. Basic Data Analysis Streamline 550 2. Advanced Techniques 564

Part III Sample Data  568 SECTION 2 MICROSOFT ACCESS 568

Part I Introduction  568 1. What Is Microsoft Access? 569 2. What Can Microsoft Access Do? 569 3. Featured Functions in Microsoft Access for Biologists 569

Part II Step-By-Step Tutorial  570 1. Starting Microsoft Access 570 2. Assigning Probe Sets to Their Target Genes 571

3. Assigning Probe Sets to Their Orthologues in Another Species 572 4. Filtering for Large Entries 574 5. Cross-Referencing for Venn Diagram Construction 575

Part III Sample Data  577 SECTION 3 INTERCHANGE OF DATA BETWEEN MICROSOFT EXCEL AND ACCESS 577

Part I Introduction  578 1. Import 578 2. Export 578

Part II Step-By-Step Tutorial  578 1. Importing Tables 578 2. Exporting Queries 580

Part III Sample Data  580 REFERENCES 580

Recently developed gene expression platforms such as oligonucleotide and  cDNA microarrays are powerful and extremely specific techniques for the  identification of differentially regulated genes in a large variety of experimental models and human diseases. The search for new candidate genes  of  human  diseases  in  global  gene  expression  profiling  using  this  highthroughput microarray technology has been widely employed. Microarray profiling is a robust tool in simultaneous identification of expression  patterns of large groups of genes and elucidating the mechanisms underlying  complex  biological  processes  and  diseases.  This  approach  reveals  responses of thousand of genes to a given challenge or condition. To cope  with  these  overwhelming  datasets,  various  computing  algorithms  were  developed. The majority of these analytical programs and tools represents  complex statistical packages and requires specific bioinformatics training  of potential users. The biomedical scientists become dependent on the bioinformatics assistance, which reduces flexibility of the research and discovery processes. However, despite the complexity of the gene expression  data, tools familiar to every biologist for data storage, manipulation, and  analysis such as Microsoft Excel and Microsoft Access can be efficiently  employed for the basic genomic analyses. While waiting for the detailed  and finesse analysis from their bioinformaticians, biologists will be able to  evaluate major trends of expressional changes and make an educational  guess in what direction to proceed with their ongoing researches.