Description Usage Arguments Details Value Author(s) Examples

Create Limit-of-Detection Ratio (LOD) plot between measured abundance (x-axis) and p-value probability (y-axis).

1 |

`measured` |
Measured abundance |

`pval` |
P-value probability |

`ratio` |
How to group ROC points |

`qval` |
Q-value probability. (Default to |

`FDR` |
Chosen false-discovery-rate. Default to |

`title` |
Title of the plot. (Default to |

`xlab` |
Label for the x-axis. (Default to |

`ylab` |
Label for the y-axis. (Default to |

`legTitle` |
Title for the legend. (Default to |

`showConf` |
Display confidence interval. (Default to |

Create a Limit-of-Detection Ratio (LOD) plot between measured abundance (x-axis) and p-value probability (y-axis).

The LOD plot indicates the confidence in measurement relative to the magnitude of the measurement. For example, p-value should converge to zero as the sequencing depth increases.

The function also fits non-parametric curves for each sequin ratio group. The curves are modelled with local regression analysis, and are colored by the sequin group.

plotLODR is a simplification from the ERCC dashboard R-package. Further details on the statistical algorithm is available in the ERCC documentation at https://bioconductor.org/packages/release/bioc/html/erccdashboard.html.

The function prints a LODR plot and return associated statistics.

Ted Wong [email protected]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ```
library(Anaquin)
#
# Data set generated by DESeq2 and Anaquin. described in Section 5.6.3.3 of
# the user guide.
#
data(UserGuideData_5.6.3)
xlab <- 'Average Counts'
ylab <- 'P-value'
title <- 'LOD Curves'
# Sequin names
seqs <- row.names(UserGuideData_5.6.3)
# Expected log-fold
group <- UserGuideData_5.6.3$ExpLFC
# Measured average abundance
measured <- UserGuideData_5.6.3$Mean
# P-value
pval <- UserGuideData_5.6.3$Pval
# Q-value
qval <- UserGuideData_5.6.3$Qval
plotLOD(measured, pval, group, qval, xlab=xlab, ylab=ylab, title=title, FDR=0.1)
``` |

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