BJWTct: BJWTct

Description Usage Format Author(s) Examples

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

1

Format

A data frame with 84 observations on the following 5 variables.

Well

a factor with well IDs

Content

factor levels denoting biological replicates

Target

3 different genes with Ef as control

Sample

3 treatments B, J, WT

Ct

a numeric response variable with estimated threshold cycles

Author(s)

Eline Biedermann <eline.biedermann@gmx.de>

Examples

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## only designs can be analyzed with qpcr()
## when all combinations
##   of factor levels and gene levels are available
##
## Here:
## - gene 06g16350 is not observed for Sample B
## - gene 01g67540 is not observed for Sample J
##
## Therefore the dataset is split into 2 parts:

data(BJWTct)

## B vs WT
BWT <- subset(BJWTct, Target != "06g16350" & Sample != "J")
BWT <- droplevels(BWT)
qpcr(data=BWT, response="Ct", gene="Target", control_gene="EF",
     fixed1="Sample", rep_id="Content", contrasts=TRUE)

## J vs WT
JWT <- subset(BJWTct, Target != "01g67540" & Sample != "B")
JWT <- droplevels(JWT)
qpcr(data=JWT, response="Ct", gene="Target", control_gene="EF",
     fixed1="Sample", rep_id="Content", contrasts=TRUE)

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