Difference between revisions of "LRPath (analysis)"

Revision as of 18:15, 9 December 2020

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

1. 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.