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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# CalibraCurve
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[](https://bioconductor.org/checkResults/release/bioc-LATEST/CalibraCurve)
[](https://bioconductor.org/checkResults/devel/bioc-LATEST/CalibraCurve)
[](http://bioconductor.org/packages/stats/bioc/CalibraCurve/)
[](https://support.bioconductor.org/tag/CalibraCurve)
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Targeted mass-spectrometry-based techniques allow accurate quantitative measurements of analytes in complex matrices.
They are used in different fields like proteomics, lipidomics or metabolomics to validate results
from global analyses. Furthermore, they are used to develop robust assays with the potential
to absolutely quantify the analyte of interest.
During assay development, often experiments using concentration or dilution series are conducted.
Here, samples with known amount of the analyte of interest are generated and measured by mass
spectrometry, usually in relicates.
This kind of data is used by CalibraCurve to generate calibration curves, which can
be the basis for predicting concentrations from intensities in new data. However, a
linear relationship between concentration and intensity is often limited to a certain
range of concentrations, the so called linear range. CalibraCurve calculates the
linear range (lower and upper limits of quantification) using a well-designed algorithm.
Quality of the data and the accuracy of the produced calibration curve is assessed in
several computational steps.
Visualizations of the calibration curves and the underlying data basis are generated
and can be customized.
## Installation instructions
Get the latest stable `R` release from [CRAN](http://cran.r-project.org/). Then install `CalibraCurve` from [Bioconductor](http://bioconductor.org/) using the following code:
```{r 'install', eval = FALSE}
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("CalibraCurve")
```
And the development version from [GitHub](https://github.com/mpc-bioinformatics/CalibraCurve) with:
```{r 'install_dev', eval = FALSE}
BiocManager::install("mpc-bioinformatics/CalibraCurve")
```
## Implementation
CalibraCurve is written in R and available as an R package.
Furthermore, a nextflow-workflow running this script is available at https://github.com/mpc-bioinformatics/CalibraCurve_NF.
Formerly, CalibraCurve was available as a KNIME-workflow based on an R script.
The last version of this workflow can be found here: https://github.com/mpc-bioinformatics/CalibraCurve/releases/tag/v_2_0 .
However, development of the KNIME-workflow was discontinued and replaced by the R
package and nextflow workflow.
## Usage
For details on the usage of CalibraCurve and some examples please see the vignettes.
## Publication
Kohl M, Stepath M, Bracht T, Megger DA, Sitek B, Marcus K, Eisenacher M. CalibraCurve: A Tool for Calibration of Targeted MS-Based Measurements. Proteomics. 2020 Jun;20(11):e1900143. doi: 10.1002/pmic.201900143. Epub 2020 Mar 6. PMID: 32086983.
## Funding
The development and maintanence of CalibraCurve is funded by de.NBI (https://www.denbi.de/) and CUBiMed.RUB (https://www.cubimed.ruhr-uni-bochum.de/index.html.en).
We offer also other cool tools and consulting for statistics, bioninformatics and machine learning!
## Terms of use
- All software, tools, and workflows provided by CUBiMed.RUB are intended exclusively for academic research and training purposes.
- They must not be used for clinical diagnosis, medical decision-making, or any form of patient care.
- Users are responsible for ensuring that results generated with these tools are appropriately validated before any further use.
- CalibraCurve is published under the BSD 3-Clause License (see [LICENSE](LICENSE)).
## Feedback
Please fill out the following survey to give feedback:
https://de.surveymonkey.com/r/denbi-service?sc=bioinfra-prot&tool=calibracurve