LRPath (analysis)
From BioUML platform
- Analysis title
- LRPath
- Provider
- geneXplain GmbH
- Class
LRPath
- Plugin
- com.genexplain.stat (geneXplain Stat)
LRPath enrichment analysis
LRPath is a Gene Set Enrichment Analysis (GSEA) method that uses logistic regression models to discover categories that are significantly correlated with a predictor [1]. The predictor can be the (-log) P-value of differential expression or another quantity. By default, predictors are treated as P-values, which means they are -log-transformed and set to a maximum of java.lang.Double.MAX_EXPONENT if 0.
The analysis includes selection of significant genes. This requires that a quantity is specified and a cut-off by which significance is determined. The values used for this purpose can be provided in another column than the predictor.
Parameters
- Input table - Path to table with input data
- Species - Species of genes in the input table
- Classification - Classification you want to use. List of classifications may differ depending on software version and your subscription
- Predictor column - Column with the LR predictor variable
- Treat predictors as P-values - Indicates whether predictors shall be treated as P-values (-log-transformed and set to a maximum if 0)
- Significance column - Column with significance values
- Significance cutoff - Cutoff on significance values to select genes
- Significant is lower - If true, significant genes must have lower values than the cutoff
- Calculations only for classified genes - Do calculations only for classified genes, e.g. when the input gene set is much bigger than the annotation database
- Result table - Path for the result table
References
- Sartor MA, Leikauf GD, Medvedovic M. LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data. Bioinformatics. 2009;25(2):211-217.