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 dataconvertStackedToMat
: average stacked data to a single value per patient-antigenplotAnti
: plot the raw data from positive controls and patient serumplotHeat
: 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)')
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)
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.
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)
## V1 V2 V3 V4 V5 V6 V7 V8
## 1 L016-01 BB 0.1018 0.0740 0.0663 0.0588 2.0930 1.0313
## 2 HSV-1 0.1192 0.0861 0.0781 0.0662 0.1205 0.0819
## 3 CMV-N 0.2488 0.1784 0.0901 0.0743 0.1951 0.1198
## 4 CMV-C 0.2174 0.1201 0.0874 0.0720 0.2575 0.1087
## 5 HSV-2 0.4526 0.2213 0.1303 0.0945 0.4012 0.2289
## 6 Negative Control 0.1906 0.0928 0.0832 0.0690 0.1350 0.0877
## V9 V10 V11 V12 V13 V14
## 1 0.5778 0.2599 2.0792 1.0701 0.5203 0.2457
## 2 0.0785 0.0630 0.1156 0.0811 0.0674 0.0630
## 3 0.0928 0.0712 0.2090 0.1226 0.0896 0.0765
## 4 0.0903 0.0701 0.2009 0.1171 0.0867 0.0718
## 5 0.1247 0.0933 0.3473 0.2005 0.1288 0.0856
## 6 0.0720 0.0623 0.1425 0.0845 0.0717 0.0640