plotLOD: Create Limit-of-Detection Ratio (LOD) plot

Description Usage Arguments Details Value Author(s) Examples

View source: R/plotLOD.R

Description

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

Usage

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plotLOD(measured, pval, ratio, qval, FDR, title, xlab, ylab, legTitle, showConf)

Arguments

measured

Measured abundance

pval

P-value probability

ratio

How to group ROC points

qval

Q-value probability. (Default to NULL).

FDR

Chosen false-discovery-rate. Default to NULL).

title

Title of the plot. (Default to NULL).

xlab

Label for the x-axis. (Default to NULL).

ylab

Label for the y-axis. (Default to NULL).

legTitle

Title for the legend. (Default to 'Ratio').

showConf

Display confidence interval. (Default to FALSE).

Details

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.

Value

The function prints a LODR plot and return associated statistics.

Author(s)

Ted Wong [email protected]

Examples

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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)

Anaquin documentation built on Nov. 17, 2017, 1:02 p.m.