mdftracks

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Overview

mdftracks reads and writes MTrackJ Data Files (.mdf). Supports clusters, 2D data, and channel information. If desired, generates unique track identifiers based on cluster and id data from the .mdf file.

Installation

install.packages('mdftracks')

Development version

To get a bug fix or to use a feature from the development version, you can install the development version from GitHub.

# install.packages("remotes")
remotes::install_github("burgerga/mdftracks")

Usage

First load the package with

library(mdftracks)
#> Warning: package 'mdftracks' was built under R version 4.1.0

Reading 3D data

mdf.file <- system.file("extdata", "example.mdf", package = 'mdftracks')
data <- read.mdf(mdf.file)
head(data, 10)
#>        cluster id time   x   y z
#> 1.1.1        1  1    1 782  43 1
#> 1.1.2        1  1    2 784  45 1
#> 1.1.3        1  1    3 780  47 1
#> 1.1.4        1  1    4 786  56 1
#> 1.1.5        1  1    5 794  65 1
#> 1.1.6        1  1    6 800  69 1
#> 1.1.7        1  1    7 805  88 1
#> 1.1.8        1  1    8 804 100 1
#> 1.1.9        1  1    9 814 110 1
#> 1.1.10       1  1   10 823 125 1

Dropping the z-coordinate for 2D data

data <- read.mdf(mdf.file, drop.Z = T)
head(data, 10)
#>        cluster id time   x   y
#> 1.1.1        1  1    1 782  43
#> 1.1.2        1  1    2 784  45
#> 1.1.3        1  1    3 780  47
#> 1.1.4        1  1    4 786  56
#> 1.1.5        1  1    5 794  65
#> 1.1.6        1  1    6 800  69
#> 1.1.7        1  1    7 805  88
#> 1.1.8        1  1    8 804 100
#> 1.1.9        1  1    9 814 110
#> 1.1.10       1  1   10 823 125

Writing data in (id, t, x, y, z) format (e.g., from celltrackR)

library('celltrackR')
tracks.df <- as.data.frame(TCells)
head(tracks.df, 10)
#>    id       t       x       y    z
#> 1   0   0.000 132.521 118.692 8.75
#> 2   0  27.781 133.909 118.700 8.75
#> 3   0  55.484 131.763 118.129 6.25
#> 4   0  83.296 133.161 117.903 6.25
#> 5   0 111.093 131.530 117.894 6.25
#> 6   0 138.906 132.229 117.665 6.25
#> 7   0 166.656 131.763 118.595 6.25
#> 8   0 194.406 131.763 117.663 6.25
#> 9   0 222.078 131.996 117.664 6.25
#> 10  0 249.890 131.763 117.663 6.25
write.mdf(head(tracks.df, 10))
#> Using the following column mapping:
#> cluster      id    time       x       y       z channel   point 
#>      NA    "id"     "t"     "x"     "y"     "z"      NA      NA

#> Converting factor to numeric in columns: id

#> MTrackJ 1.5.1 Data File
#> Assembly 1
#> Cluster 1
#> Track 0
#> Point 1 132.5209960938 118.6920013428 8.75 0 1
#> Point 2 133.908996582 118.6999969482 8.75 27.7810001373 1
#> Point 3 131.7630004883 118.1289978027 6.25 55.4840011597 1
#> Point 4 133.1609954834 117.9029998779 6.25 83.2959976196 1
#> Point 5 131.5299987793 117.8939971924 6.25 111.0930023193 1
#> Point 6 132.2290039063 117.6650009155 6.25 138.9060058594 1
#> Point 7 131.7630004883 118.5950012207 6.25 166.6560058594 1
#> Point 8 131.7630004883 117.6630020142 6.25 194.4060058594 1
#> Point 9 131.9960021973 117.6640014648 6.25 222.0780029297 1
#> Point 10 131.7630004883 117.6630020142 6.25 249.8899993896 1
#> End of MTrackJ Data File

Writing data with cluster, channel, and point information

print(mdftracks.example.data)
#>    cl id p     x     y    z t ch uid
#> 1   1  1 1 187.1 263.2 27.4 1  2   1
#> 2   1  1 3 309.2 264.4 15.8 2  2   1
#> 3   1  2 1  18.4 438.5 28.1 1  2   2
#> 4   1  2 2 142.9  58.6 28.2 2  2   2
#> 5   1  2 5 290.1 197.5 18.8 3  2   2
#> 6   2  1 1 310.1  15.4  5.8 1  2   3
#> 7   2  2 1  99.1  33.5 22.5 1  2   4
#> 8   2  2 2 220.2 396.0 16.4 2  2   4
#> 9   2  3 1   8.4 305.8 30.2 1  2   5
#> 10  2  3 2  84.7 227.7 21.1 2  2   5
write.mdf(mdftracks.example.data, cluster.column = 'cl', id.column = 'id',  
          pos.columns = letters[24:26], channel.column = 'ch', 
          point.column = "p")
#> Using the following column mapping:
#> cluster      id    time       x       y       z channel   point 
#>    "cl"    "id"    "id"     "x"     "y"     "z"    "ch"     "p"

#> MTrackJ 1.5.1 Data File
#> Assembly 1
#> Cluster 1
#> Track 1
#> Point 1 187.1 263.2 27.4 1 2
#> Point 3 309.2 264.4 15.8 1 2
#> Track 2
#> Point 1 18.4 438.5 28.1 2 2
#> Point 2 142.9 58.6 28.2 2 2
#> Point 5 290.1 197.5 18.8 2 2
#> Cluster 2
#> Track 1
#> Point 1 310.1 15.4 5.8 1 2
#> Track 2
#> Point 1 99.1 33.5 22.5 2 2
#> Point 2 220.2 396 16.4 2 2
#> Track 3
#> Point 1 8.4 305.8 30.2 3 2
#> Point 2 84.7 227.7 21.1 3 2
#> End of MTrackJ Data File

For more information, please consult the package documentation.