The purpose of this toolbox is to analyze calcium imaging data obtained by using Fluo4 (non-ratiometric Calcium indicator) and raw mean gray values obtained from the ImageJ software.

• Download and install R. Instructions can be found here.
• Clone/download this repository on to your local machine. Extract all contents from the zip file, if necessary.
• Open R interface.
• Select File > Change dir: set Working Directory to the folder 'Calcium-Imaging-Analysis-with-R' that you downloaded and extracted. All the source R files and input csv files should be at the root of this directory. The output files will also be written there. You have to set this at the beginning of each session.
• In the R interface, select File > Source R code : select each R file. Repeat the process until all source files, namely Threshold_iono.R, Threshold.R, Normalization_ionomycin.R and Peakcurrent.R. All other files are optional.

Description: This function takes a separate drug response file and ionomycin response file(or any other drug you want to normalize to, for e.g. KCl) from a Calcium Imaging dataset as input and generates a .csv file with normalized intensity (F/Fmax) values for all the cells that meet threshold (mean + 5 * st.dev). The inputs are mean gray values of ROIs obtained directly from ImageJ. Read CaImagingFunctionsRDocumentation.docx for detailed methodology and variable listing.

Filename: Normalization_ionomycin.R

Important considerations:

• Make sure the input file is in .csv format.
• Column headers are [Time/frame#, cell number (1, 2, 3, ... n), column with background intensity (obtained by selecting a dark area in the field of view in ImageJ] from left to right.
• Each row of the csv file should contain intensity value for a single time instant/frame.
• Two sample input files are provided: one with ph5 response named TestR.csv and another with ionomycin response called ionotest.csv.
• SampleCalculations.xlsx shows a step-by-step breakdown of the calculations performed by this software in an excel format for ease of understanding.

To run this program: Type Normalization_ionomycin() in the R console and follow along with the prompt

Description: This function computes the maxima of each column from the data produced in Part 1.

Filename: Peakcurrent.R

Important consideration: Use the normalized (output) file from the above function in a .csv format.

To run this program: Type peakresponse() in your R prompt and follow subsequent instructions