Skip to content

Latest commit

 

History

History
96 lines (67 loc) · 3.91 KB

README_viewInPlotter.md

File metadata and controls

96 lines (67 loc) · 3.91 KB

DistancePlotter

Running

  • create a folder to accomodate DistancePlotter, e.g. PlottingApp
  • copy server.R and ui.R into that folder, e.g. PlottingApp or git clone https://github.com/imbforge/DistancePlotter.git
  • the application can be run either via command line R or Rstudio

command line R

library(shiny)
runApp(PlottingApp)

Rstudio

  • open either server.R, ui.R or both
  • hit "Run App"
  • depending on your preferences you can maximise the window into browser

Usage

DistancePlotter screenshot

Data

The "Data" tab is used to open data files and a naming table.

All input files should be saved as TAB delimited files.

Data Input file

  • the file containing the data to be plotted should contain headers

  • DistancePlotter will create an "experiment ID" from the 3 columns named "Row", "Column", "Timepoint", e.g. "2_4_0"

    Row Column Timepoint Field Object No ...
    2 5 0 2 1 ...
    2 5 0 2 2 ...
    2 6 0 4 3 ...

multiple Data Input files

  • DistancePlotter also digests a folder structure of tab delimited files
  • the folder has to be compressed to a zip archive and can be uploaded via the file upload field
  • ! Note: as fusion of all input files in the folder may involve a lot of data the process until the plotting area becomes available may take a bit !

Naming Input file

  • a translation table can be used to name experiments according to your wishes instead of raw experiment IDs

    • the file should be TAB delimited
    • the table must contain a header, but the wording is not important
    • first column should contain the "experiment ID", e.g. 2_4_0
    • second column should contain your desired experiment name
    • the order of experiments given in this file will determine the order of experiments plotted
    old name real name
    2_5_0 treated
    2_6_0 untreated

Plotting

All fields of the "Plot" tab influence the plot shown on the right hand side instantly and can be revised at any time.

  • select the type of plot

    • violin plot (a box plot with a rotated kernel density plot on each side.)
    • box plot
    • jitter plot (a box plot showing all data points instead of boxes)
    • density will draw empty areas
    • density (fill) will draw colored areas
    • histogram (stack) will stack all bars
    • histogram (dodge) will print each experiment's bar starting at x-axis
    • all plots can be produced in "coloured" variant, which will paint your samples according to colours chosen in "Sample" tab

  • select which column to plot

  • select samples to plot ("Samples" tab)

  • change the title and y-axis label of the plot, whereas y-axis label will be used as x-axis label for density plots and histograms

  • limiting of plotted data and scaling of the y- or x-axis may cause confusion, i.e. log10 scaling with minimal value=0

  • select data column for filtering:

    • one column can be selected to filter the plotted data, e.g. to selectively show data of nuclei containing 2 spots, ...
    • if you're happy with the filter settings "Add" the filter
    • later you can combine several filter settings to your liking

  • Download will save the last plot as "plot.pdf"

The "Samples" tab may be used to:

  • select samples to plot (each change will reset this tab including color choices)
  • select which colour the samples are plotted in - default colour is white

Statistics

  • ! Note: don't get nervous, if no statistics is shown immediately. It takes a bit... !
  • DistancePlotter will calculate Mann-Whitney (aka Wilcoxon) test on all data selected by the chosen column to plot
  • a matrix of all vs. all will be shown and can be downloaded as csv (comma separated file)