Examples
Here there are some examples of ranked lists of genes. These examples are available at the Network Miner web tool as online examples. Go to Network Miner, run these jobs and see the results!
Example 1
Select your data → BD-GWASplink.txt
Select your seed datalist (optional) → BD-associatedgenesUniprot.txt
Select interactome:
Order your list → Ascending
Maximum number of external proteins → 1
Select threshold of significance (p-value) → 0.05
Job name: Genome-Wide Association Study in Bipolar Disorder
Job description: Genotypic data comes from the Wellcome Trust Case Control Consortium. GWAS was performed using the basic association test of Plink toolset. Here, genes were ranked acording the adjusted p-value (BD-GWASplink.txt). Moreover, genes previously associated with Bipolar Disorder obtained from Uniprot database are used as seed genes (BD-associatedgenesUniprot.txt).
Example 2
Select your data → FA-differentialExpression-statistic.txt
Select your seed datalist (optional) → Empty
Select interactome:
Order your list → Descending
Maximum number of external proteins → 1
Select threshold of significance (p-value) → 0.05
Job name: Genes Down-regulated in Fancony Anemia
Job description: Expression data comes form a recent study of the gene expression in Fancony Anemia (Vanderwerf et al. 2009; GEO:GSE16334). Differential gene expression of control versus case samples was carried out using the Limma option in Differential expression analysis. Here, genes are ranked according the statistic (FA-differentialExpression-statistic.txt).
Example 3
Select your data → FA-differentialExpression-statistic.txt
Select your seed datalist (optional) → Empty
Select interactome:
Order your list → Ascending
Maximum number of external proteins → 1
Select threshold of significance (p-value) → 0.05
Job name: Genes Up-regulated in Fancony Anemia
Job description: Expression data comes form a recent study of the gene expression in Fancony Anemia (Vanderwerf et al. 2009; GEO:GSE16334). Differential gene expression of control versus case samples was carried out using the Limma option in Differential expression analysis. Here, genes are ranked according the statistic (FA-differentialExpression-statistic.txt).
Example 4
Select your data → K562.txt
Select your seed datalist (optional) → Empty
Select interactome:
Order your list → Ascending
Maximum number of external proteins → 1
Select threshold of significance (p-value) → 0.05
Job name: Essential genes in cancer cell line K562
Job description: This data comes form a recent study of the gene essentiality in different cancer cells (Luo et al. 2008). Here, genes are ranked according the RIGER, which accounts gene essentiality (K562.txt).
Example 5
Select your data → JURKAT.txt
Select your seed datalist (optional) → Empty
Select interactome:
Order your list → Ascending
Maximum number of external proteins → 1
Select threshold of significance (p-value) → 0.05
Job name: Essential genes in cancer cell line JURKAT
Job description: This data comes form a recent study of the gene essentiality in different cancer cells (Luo et al. 2008). Here, genes are ranked according the RIGER, which accounts gene essentiality (JURKAT.txt).