The purpose of this library is to process with the raw data from the Maverick M1 detection system (Genalyte, Inc., San Diego, CA) and output simple line graphs, bar charts, and box plots. The functions also generate companion csv files containning processed the prcoessed data for subsequent analysis. Additional functions are available to general calibration curves. The folder containing output from the M1 typically consists of:
The comments file is not needed for this program. In addition to the csv files for each ring, a separate file containing the chip layout is required. An example of a chip layout file is provided in the sample data. To access this data, execute the following code:
library(biosensor)
dir <- setwd(system.file("extdata", "sampleChipLayout", package = "biosensor"))
example <- read.csv("groupNames_Example.csv")
View(example)
Note: This version of the software is optimized for the Bailey lab's HRP assay. See dx.doi.org/10.1021/acscentsci.5b00250 for a description. However, input variables can be altered to accomodate many alternative experiments.
To get started, follow these steps:
update.packages()
in the Console in RStudio.devtools
library. Run the following code to
install devtools
and the biosensor
package.# uncomment the line below if devtools is not installed
# install.packages("devtools")
devtools::install_github("BaileyLabUM/biosensor")
The functions within this library include:
analyzeBiosensorData
- This function processes raw data from a single
biosensor experiment and outputs simple line graphs, bar charts, and box plots.
In principle, this code should also work for any bionsensor data that ouputs
Time in column one and Signal in column two. The function call also generates
companion csv files containning processed the prcoessed data for subsequent
analysis.calibrationStation
- This function processes a series of experiments
using the analyzeBiosensorData
function. Then, the data from each experiment
is combined to generate a calibration curve for each target of interest.analyzeBiosensorData
:Ensure the you have the necessary libraries installed and up to date.
Copy the chip layout file (e.g., "groupNames_XPP.csv") into the directory containing the raw ring data you wish to analyze. Note: This program has the highest chance of success if the directory only contains:
Set the working directory to the directory containing your raw data and chip
layout file. See instructions on setting the working directory
in R here. For example,
if you are using a Windows machine and your ring data is on your Desktop
folder, you could set your working directory by executing the following line
in the console:
setwd("C:/Users/USERNAME/Desktop/CHIPNAME_gaskGASKNAME_DATE")
.
Execute the code by running the analyzeBiosensorData
function. This
function requires 13 input variables:
Note: to calculate net shift measurements, the relative shift at time2 is subtracted from time1 (netshift = time1 - time2).
Here is an example of code to run:
library(biosensor)
setwd("C:/Users/USERNAME/Desktop/CHIPNAME_gaskGASKNAME_DATE")
# this will run with code defaults
analyzeBiosensorData()
To see an example with data provided as part of this library execute the following code:
library(biosensor)
dir <- system.file("extdata", "20171112_gaskTestData_MRR", package = "biosensor")
setwd(dir)
analyzeBiosensorData()
calibrationStation
:calibrationStation
function. The function
has a single input variable:Here is an example of code to run:
library(biosensor)
setwd("C:/Users/USERNAME/Desktop/CalibrationData")
calibrationStation(celebrate = TRUE)
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