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gene_set_analysis [2012/04/23 18:12]
mbleda [Logistic model]
gene_set_analysis [2012/04/23 18:12]
mbleda
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   - **Ranking**:​ Firstly a **list of genes is ordered using experimental information** on their differential expression, according to the phenotype studied in the experiment, or to other type of value (e.g. large-scale genotyping, evolutionary analysis, etc.). For example, genes can be ordered on the basis of their differential expression among two experimental conditions (e.g. healthy versus diseased samples, etc.).   - **Ranking**:​ Firstly a **list of genes is ordered using experimental information** on their differential expression, according to the phenotype studied in the experiment, or to other type of value (e.g. large-scale genotyping, evolutionary analysis, etc.). For example, genes can be ordered on the basis of their differential expression among two experimental conditions (e.g. healthy versus diseased samples, etc.).
   - **Distribution of regulatory elements**: The second step involves the **study of the distribution of functional terms in different partitions of this list**. Using a fisher exact test to compare such partitions, FatiScan extracts significantly under- and over-represented functional terms in a set of genes. In the figure, rows transcription factor 1 (TF1), TF2 and TF3 represent the position of the genes that are targets of this TF across the ranking. In this case, TF1 is completely uncorrelated with the arrangement while TF2 and 3 are clearly associated to high expression in the experimental conditions B and A, respectively.   - **Distribution of regulatory elements**: The second step involves the **study of the distribution of functional terms in different partitions of this list**. Using a fisher exact test to compare such partitions, FatiScan extracts significantly under- and over-represented functional terms in a set of genes. In the figure, rows transcription factor 1 (TF1), TF2 and TF3 represent the position of the genes that are targets of this TF across the ranking. In this case, TF1 is completely uncorrelated with the arrangement while TF2 and 3 are clearly associated to high expression in the experimental conditions B and A, respectively.
-  - Finally, a **table with the significant terms** obtained upon the application of the test can be used to detect significant asymmetrical distributions of genes, responsible for diverse biological processes, across the list.+  - **table with the significant terms** obtained upon the application of the test can be used to detect significant asymmetrical distributions of genes, responsible for diverse biological processes, across the list
 +  - **Multiple testing correction**:​ The P-values from the test of each regulatory element, are adjusted for multiple testing by controlling the false discovery rate (FDR) (Benjamini et al., 1995; Storey andTibshirani,​ 2003).
  
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   - **Multiple testing correction**:​ The P-values from the test of each regulatory element, are adjusted for multiple testing by controlling the false discovery rate (FDR) (Benjamini et al., 1995; Storey andTibshirani,​ 2003).   - **Multiple testing correction**:​ The P-values from the test of each regulatory element, are adjusted for multiple testing by controlling the false discovery rate (FDR) (Benjamini et al., 1995; Storey andTibshirani,​ 2003).
    
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gene_set_analysis.txt · Last modified: 2012/04/23 18:13 by mbleda
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