Maximum likelihood diffusion coefficient calculation for single particle tracks

computeDmle.R

# Estimate per-step and per-trajectory diffusion coefficients from SPT data
#
# Created by: Raibatak Das
# Jan 2016

library(readxl)
library(dplyr)

# Function to compute per-step diffusion coefficients
singlestepDmle = function(frame, x, y, pxl, dt){
    # Compute Dmle for each step in a track
    gaps = diff(frame)
    dx = pxl*diff(x)
    dy = pxl*diff(y)
    sqdisp = dx^2 + dy^2
    return( c(0, sqdisp/(gaps*4*dt)) )
}

# Acquisition parameters
pixelsize = 0.064 # pixel size in microns
delta_t = 0.03 # time step in seconds (= 1/frame rate)

# Import tracks - Change filename below
tracks = read_excel("Cbx7-PGK12-1-30ms.xlsx")

# Estimate per step maximum likelihood diffusion coefficients
perstepDmle = tracks %>%
    group_by(ExptID, Cell, Track) %>%
    transmute(singlestepDmle = singlestepDmle(Frame, x, y, pixelsize, delta_t)) %>%
    filter(singlestepDmle != 0)

# Compute per-track and first-step diffusion coefficients
pertrackDmle = perstepDmle %>%
    summarise(steps = n(),
              firststepDmle = first(singlestepDmle),
              trackDmle = mean(singlestepDmle))

# Save output - change filenames below
write.csv(perstepDmle, file="Cbx7-PGK12-1-30ms-per-step.csv", row.names=F) # per-step estimates
write.csv(pertrackDmle, file="Cbx7-PGK12-1-30ms-per-track.csv", row.names=F) # per-track estimates