extr_ObjectJ - veeninglab/BactMAP GitHub Wiki

Upload and transform ObjectJ bounding box data.

Description

ObjectJ detects a bounding box around each cell, which it uses to calculate spot localization, cell width and cell length along the medial axis. It is possible to save the bounding box points manually by defining them in the Columns section of the ObjectJ results. Here you can download an ObjectJ Settings file where the bounding box columns are already created.

Usage

extr_ObjectJ( dataloc,
              mag = "No_PixelCorrection",
              boundingBoxX = c("X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10", "X11"),
              boundingBoxY = c("Y1", "Y2", "Y3", "Y4", "Y5", "Y6", "Y7", "Y8", "Y9", "Y10", "Y11"),
              turn_meshes = TRUE,
              cellList = FALSE)

Arguments

  • dataloc The path to the saved .CSV or .TXT file from ObjectJ.

  • mag Magnification conversion factor (see pixels2um)

  • boundingBoxX The column names of the 11 X-coordinates of the bounding box of the cells. Put these columns in your ObjectJ analysis manually or download the ObjectJ Settings here.

  • boundingBoxY The column names of the 11 Y-coordinates of the bounding box of the cells. Put these columns in your ObjectJ analysis manually or download the ObjectJ Settings here.

  • turn_meshes Default TRUE. When TRUE, the bounding boxes are all turned so the mid-point is at [0,0] while the length axis of the cell is parallel to the X-axis.

  • cellList Default FALSE. When TRUE, one of the outputs in the output list is the cellList (see Values below).

Details

ObjectJ can already convert it’s data to micron for you! Therefore, the default setting for “mag” is “no_PixelCorrection”. Check what your settings are before converting the data using BactMAP.

Value

  • $cellList The original CSV as dataframe.

  • $mesh Dataframe containing the X and Y coordinates of the bounding box and cell dimensions. When turn_meshes=TRUE, it also contains the coordinates of the turned meshes, cell angle (to the x axis of the image) and mid-point coordinates.

  • GFPframe Dataset contains self-defined (by the user) fluorescence information from the ObjectJ eg septal position or fluorescence intensity.

  • $chainframe Dataset contains information on cell chains: chain ID, length, width and if specified, fluorescence information.

Note

It is possible to define your own column names in ObjectJ - but (apart from the bounding box columns) bactMAP recognises the standard names only. See the example objectJ settings file for the standard column names.

Author(s)

Renske van Raaphorst

References

https://sils.fnwi.uva.nl/bcb/objectj/

Vischer, Norbert OE, et al. “Cell age dependent concentration of Escherichia coli divisome proteins analyzed with ImageJ and ObjectJ.” Frontiers in microbiology 6 (2015): 586.

Examples

  #Take ObjectJ file interactively. example in the "localization" dataset on veeninglab.com/bactmap

  #Using pipes:
  library(tidyverse)

  ObjectJ_output <- file.choose() %>% extr_ObjectJ()

  #check summary
  ObjectJ_output %>% summary()

  #plot chain length distribution
  ggplot(ObjectJ_output$chainframe, aes(x=ChainAxis)) + geom_histogram()

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