Difference between revisions of "LRPath (analysis)"

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Revision as of 18:15, 9 December 2020

Analysis title
Statistics-LRPath-icon.png 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.
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