Description Usage Arguments Value Examples

MAR.est estimates the proportion of missing peaks at random (MAR) caused by preprocessing tools with exactly two technical replicates per sample.

1 |

`abundance` |
The full abundance matrix without missing value, with features in rows and samples in columns. |

`sample` |
A vector of characters or integers. It is the sample name for each pair of replicates. |

`log.scale` |
A scalar or vector of proportions. It is the total percentage of missing peaks throughout the full matrix. |

`violin.plot` |
Logical, whether to generate violin and box plots to visualize abundance distribution of missing and nonmissing peaks. |

`MAR.Proportion` |
Estimated MAR proportion |

`plot` |
Violin and box plots generated by ggplot2 |

1 2 3 4 5 6 7 8 9 10 | ```
data('replicates')
# replicates contains mass specturm log abundance of 85 peptides
# with missing values for 4 pairs of technical replicates.
MAR=MAR.est(replicates,sample=rep(1:4,each=2),log.scale=FALSE,violin.plot=TRUE)
# Estimates the MAR proportion in the 4 pairs of replicates and output violin/box plots object.
print(MAR$plot)
# Print violin/box plots
``` |

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