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https://github.com/ramiromagno/batsch
Real-Time PCR Data Sets by Batsch et al. (2008)
https://github.com/ramiromagno/batsch
qpcr r
Last synced: 8 days ago
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Real-Time PCR Data Sets by Batsch et al. (2008)
- Host: GitHub
- URL: https://github.com/ramiromagno/batsch
- Owner: ramiromagno
- License: cc-by-4.0
- Created: 2023-02-10T20:03:25.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-22T21:48:37.000Z (7 months ago)
- Last Synced: 2024-05-01T14:24:25.068Z (6 months ago)
- Topics: qpcr, r
- Language: R
- Homepage: https://rmagno.eu/batsch/
- Size: 2.89 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
library(tidyverse)
```
# batsch
[](https://CRAN.R-project.org/package=batsch)
[](https://github.com/ramiromagno/batsch/actions/workflows/R-CMD-check.yaml)
`{batsch}` provides real-time PCR data sets by Batsch et al. (2008) in tidy
format. There are five data sets bundled with this package, one for each PCR
target:
- `SLC6A14r` for *rat SLC6A14*
- `SLC22A13h` for *human SLC22A13*
- `EMTp` for *pig EMT*
- `ETTch` for *chicken ETT*
- `GAPDHh` for *human GAPDH*
Each data set comprises a five-point, four-fold dilution series. For each
concentration there are three replicates. Each amplification curve is 45 cycles
long.
## Installation
Install `{batsch}` from CRAN:
``` r
# Install from CRAN
install.packages("batsch")
```
You can instead install the development version of `{batsch}` from GitHub:
``` r
# install.packages("remotes")
remotes::install_github("ramiromagno/batsch")
```
## Usage
### Rat SLC6A14
```{r dpi=300, fig.width=8, fig.height=4}
library(batsch)
SLC6A14r |>
ggplot(mapping = aes(
x = cycle,
y = fluor,
group = interaction(dilution, replicate),
col = as.factor(dilution)
)) +
geom_line(linewidth = 0.5) +
labs(y = "Raw fluorescence", colour = "Dilution factor", title = "Rat SLC6A14") +
guides(color = guide_legend(override.aes = list(size = 0.5)))
```
### Human SLC22A13
```{r dpi=300, fig.width=8, fig.height=4}
SLC22A13h |>
ggplot(mapping = aes(
x = cycle,
y = fluor,
group = interaction(dilution, replicate),
col = as.factor(dilution)
)) +
geom_line(linewidth = 0.5) +
labs(y = "Raw fluorescence", colour = "Dilution factor", title = "Human SLC22A13") +
guides(color = guide_legend(override.aes = list(size = 0.5)))
```
### Pig EMT
```{r dpi=300, fig.width=8, fig.height=4}
EMTp |>
ggplot(mapping = aes(
x = cycle,
y = fluor,
group = interaction(dilution, replicate),
col = as.factor(dilution)
)) +
geom_line(linewidth = 0.5) +
labs(y = "Raw fluorescence", colour = "Dilution factor", title = "Pig EMT") +
guides(color = guide_legend(override.aes = list(size = 0.5)))
```
### Chicken ETT
```{r dpi=300, fig.width=8, fig.height=4}
ETTch |>
ggplot(mapping = aes(
x = cycle,
y = fluor,
group = interaction(dilution, replicate),
col = as.factor(dilution)
)) +
geom_line(linewidth = 0.5) +
labs(y = "Raw fluorescence", colour = "Dilution factor", title = "Chicken ETT") +
guides(color = guide_legend(override.aes = list(size = 0.5)))
```
### Human GAPDH
```{r dpi=300, fig.width=8, fig.height=4}
GAPDHh |>
ggplot(mapping = aes(
x = cycle,
y = fluor,
group = interaction(dilution, replicate),
col = as.factor(dilution)
)) +
geom_line(linewidth = 0.5) +
labs(y = "Raw fluorescence", colour = "Dilution factor", title = "Human GAPDH") +
guides(color = guide_legend(override.aes = list(size = 0.5)))
```
## Code of Conduct
Please note that the `{batsch}` project is released with a [Contributor Code of
Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By
contributing to this project, you agree to abide by its terms.
## References
- Anke Batsch, Andrea Noetel, Christian Fork, Anita Urban, Daliborka Lazic, Tina Lucas, Julia Pietsch, Andreas Lazar, Edgar Schömig & Dirk Gründemann. _Simultaneous fitting of real-time PCR data with efficiency of amplification modeled as Gaussian function of target fluorescence_. BMC Bioinformatics 9:95 (2008). doi: [10.1186/1471-2105-9-95](https://doi.org/10.1186/1471-2105-9-95).