analyzeSingleLab: Analyze Single Lab Qualitative PCR Outcomes

In POD: Probability of Detection for Qualitative PCR Methods

Description

Compute the POD curve and the LOD value to validate a qualitative PCR method of a single laboratory.

Usage

analyzeSingleLab(x = NULL, X = NULL, S = NULL, N = NULL,
  qLOD = 95, b = 1)

Arguments

x	A matrix or dataframe with columns 'X', 'S' and 'N'.
X	Nominal DNA concentration.
S	Number of successfull PCR outcomes.
N	Total number of PCR experiments.
qLOD	The quantile(s) for the Limit Of Detection (LOD). Divided by 100 if greater than one.
b	Fixed value for the corrective parameter

Details

According to the suggestion of Uhlig et al. (2015), the corrective parameter b is set to 1 if it is close to 1 (simplified fit). However, if sensitivity is better than achievable according to the theoretical POD curve or average amplification probability is higher at higher dilution levels than at lower dilution levels, the b is estimated from the data (full fit). The value of b can be changed by the user. However, it is not recommended to do so. In particular unexperienced users struggle with decimal commas and decimal dots, transforming digits from strings into numeric values etc. To lower the burden, beginning with package version 1.2.0 this function automatically and only where necessary

• adds column names (with warning)

• transforms values in all columns from factor or character into numeric values

• thereby substituting decimal commas by decimal dots

• transforms columns 'S' and 'N' to integer (link{as.integer})

Value

A list with following items

x

Input data plus extra columns

b

The parameter b, as provided by the user

fit.glm.simple

Results for the simplified GLM

fit.glm.full

Results for the full GLM

where "fit.glm.simple" and "fit.glm.full" are lists with the following parameters

b

The parameter b (estimated from the model)

lambda

The parameter λ (estimated from the model)

model

The generalized linear model (GLM) fit to the data

lod

A named vector of LOD values

lodci

The 95% confidence interval of the LOD

warn

A character vector containing warnings that appeared during GLM fit

References

Uhlig et al. Accred Qual Assur (2015) 20: 75. https://doi.org/10.1007/s00769-015-1112-9

Examples

x <- cbind(
 X=c(0.1,1,2,5,10,20),
 S=c( 0,5,6,6,6,6 ),
 N=c( 6,6,6,6,6,6 )
)
obj <- analyzeSingleLab(x=x)

POD documentation built on July 2, 2020, 3:16 a.m.