In sherrillmix/antiprofr: Functions to Work with measurements of antibody profiling from serum

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Introduction

antiprofr provides some simple functions to read in and display measurements of antibody profiling in serum.

The major functions are: * readAnti: read in antibody profiling data * convertStackedToMat: average stacked data to a single value per patient-antigen * plotAnti: plot the raw data from positive controls and patient serum * plotHeat: plot the average patient-antigen values

And a simple use case might look like (see below for more details):

library(antiprofr)
raw<-read.csv('antibodyData.csv',stringsAsFactors=FALSE,header=FALSE)
stacked<-readAnti(raw,p24Cut=10)
odMat<-convertStackedToMat(stacked)
par(mar=c(6,10,1,3))
plotHeat(odMat,main='',filterLess=200,filterMore=50000,scaleMain='Dilution reaching OD450(p24=10pg)')

Installation

The package is available from github, use the devtools library and run:

devtools::install_github("sherrillmix/antiprofr")

To use the library, load it in R:

library(antiprofr)

Usage

Data format

This package is designed for antibody profiling data where each row given the OD for various dilutions of a patient serum with a given antigen (or positive or negative control). The data should be in a 15 column .csv where the first column gives the patient ID in the first row of each plate of data and is empty for remaining rows of that plate, the second column gives the antigen and columns 3-14 give OD values for given dilutions of the patient serum for that antigen.

Reading in data

In most cases, the user will be reading in data from a .csv file (if an Excel file then Save As .csv in Excel or OpenOffice):

raw<-read.csv('antibodyData.csv',stringsAsFactors=FALSE,header=FALSE)

Here we'll use data cached from the package:

raw<-antibodyData
head(raw)

sherrillmix/antiprofr documentation built on Sept. 3, 2022, 12:19 a.m.