PomaLimma {POMA} | R Documentation

## Implementation of limma R Package on Mass Spectrometry Data

### Description

PomaLimma() uses the classical limma package for MS data.

### Usage

    PomaLimma(
      data,
      contrast = NULL,
      covariates = FALSE,
      adjust = "fdr",
      cutoff = NULL
    )

### Arguments

`data` | A MSnSet object. First `pData` column must be the subject group/type.
`contrast` | A character with the limma comparison. For example, "Group1-Group2" or "control-intervention".
`covariates` | Logical. If it's set to `TRUE` all metadata variables stored in `pData` will be used as covariables. Default = FALSE.
`adjust` | Multiple comparisons correction method. Options are: "fdr", "holm", "hochberg", "hommel", "bonferroni", "BH" and "BY".
`cutoff` | Default is NULL. If this value is replaced for a numeric value, the resultant table will contains only those features with an adjusted p-value below selected value.

### Value

A data frame with limma results.

### Author(s)

Pol Castellano-Escuder

### References

Matthew E. Ritchie, Belinda Phipson, Di Wu, Yifang Hu, Charity W. Law, Wei Shi, Gordon K. Smyth, limma powers differential expression analyses for RNA-sequencing and microarray studies, Nucleic Acids Research, Volume 43, Issue 7, 20 April 2015, Page e47, https://doi.org/10.1093/nar/gkv007

### Examples

    data("st000284")

    st000284 %>%
      PomaNorm() %>%
      PomaLimma(contrast = "Healthy-CRC", adjust = "fdr")

[Package POMA version 1.0.0 Index]