README.Rmd

---
output: github_document
---

<style>
body {
text-align: justify}
</style>

<!-- 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%"
)
library(knitr)

```

# bayesiantiters

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bayesiantiters is a Bayesian inference method that calculates a serum
sample’s antibody concentration, $\phi$, and titer based on data from a
standard virus neutralization assay. The method uses a dose-response
relationship in a logistic function to simulate mortality of cell
monolayers as a function of antibody concentration.

Given the limited information per sample that’s inherent in the
experimental design of neutralization assays (number of replicates per
dilution and number of dilutions), the advantage of Bayesian inference
here is the use of probability distributions to incorporate uncertainty
in the outcome.


## Installation

You can install the development version of bayesiantiters from
[GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("ekamau/bayesianTiterCalc")
```