Statistical analysis of global gene expression data: some practical considerations
| Autor: | Eugene Kolker, Ted Holzman |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Technology Assessment
Biomedical Computer science Biomedical Engineering Bioengineering Similarity measure computer.software_genre Bioinformatics Sensitivity and Specificity Animals Humans Statistical analysis Oligonucleotide Array Sequence Analysis Models Statistical Models Genetic Gene Expression Profiling Reproducibility of Results Equipment Design Sequence Analysis DNA Data Interpretation Statistical Gene chip analysis Key (cryptography) Data mining Focus (optics) computer Algorithms Biotechnology |
| Zdroj: | Current Opinion in Biotechnology. 15:52-57 |
| ISSN: | 0958-1669 |
| Popis: | Applying appropriate error models and conservative estimates to microarray data helps to reduce the number of false predictions and allows one to focus on biologically relevant observations. Several key conclusions have been drawn from the statistical analysis of global gene expression data: it is worth keeping core information for each experiment, including raw and processed data; biological and technical replicates are needed; careful experimental design makes the analysis simpler and more powerful; the choice of the similarity measure is nontrivial and depends on the goal of an experiment; array information must be complemented with other data; and gene expression studies are ‘hypothesis generators’. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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