QTTWTcurves: QTTWTcurves

In daniel-gerhard/qpcrnlme: Nonlinear mixed model analysis of RT-PCR data

Description

Dataset from the Institute of plant nutrition (LUH). In the experiments an insertion has introduced into the genome of different rice lines. This insertion changes gene expression from the gene of interest. By using the quantitative RT-PCR the changes in gene expression of a target gene will analyse between different samples and the wild type. Content: ID of biological replicates Target: gene of interest and EF (elongation factor) gene of control Samples: rice lines with an insertion (different letters) and wild type (W)

Usage

data(QTTWTcurves)

Format

A data frame with 3780 observations on the following 6 variables.

Well

a factor with well IDs

Content

factor levels denoting biological replicates

Target

2 different genes 10g30610 and EF (control)

Sample

treatments Q, TT, WT

Cycle

cycle number

Fluorescence

observed fluorescence (proportional to PCR material)

Author(s)

Eline Biedermann <[e-mail]>

Examples

data(QTTWTcurves)
ggplot(QTTWTcurves, aes(x=Cycle, y=Fluorescence, colour=Sample,
group=Well)) + geom_line() + facet_wrap(~Target)

## Not run: 
qttwt <- qpcr_nlme(response="Fluorescence", cycle="Cycle", gene="Target", 
                   treatment="Sample", brep="Content", well="Well", 
                   data=QTTWTcurves, cutoff=10, nGQ=5, verbose=TRUE)
ddctcomp(qttwt, control_gene="EF", control_treatment=NULL, 
         conf.level=0.95, adjusted=TRUE, ratio_ddct=TRUE)

## End(Not run)

daniel-gerhard/qpcrnlme documentation built on May 14, 2019, 3:39 p.m.