Visualisation Expanded Help - mattravenhall/SV-Pop GitHub Wiki

The Visualisation module should effectively work out of the box by running Rscript easyRun.r (including installing dependencies). However, output from the Analysis must first be converted to the correct input for the Visualisation module with SVPop --PREPROCESS (nb. this will not convert your annotation file), before the files are placed in Visualisation/Files/. This section outlines the necessary input files and locations which the module will expect. Information covering the use of this module is also present on the Help tab within your browser.

Running

Rscript Visualisation/easyRun.r

Dependencies

nb. easyRun.r will attempt to install each of these.

• R (tested with 3.5.2)
• shiny
• plotly
• dplyr
• data.table

Input Files

All files for visualisation should be placed in Visualisation/Files/

• (DEL/DUP/INS/INV)_Variants.csv
  • CSV containing SV variant counts, standard SV-Pop output.
  • Used for producing variant subsets of highlighted regions.
  • Required columns: Chromosome, Start, End.
• (DEL/DUP/INS/INV)_Windows.csv
  • CSV containing SV window counts, standard SV-Pop output.
  • Critical for producing visualisation plots.
  • Required columns: Chromosome, Start, End, Count, Samples, (Sub-population counts and Fst scores), Feature.
• (DEL/DUP/INS/INV)_AllIndex.csv
  • CSV containing genomic locations for all variants for faster indexing.
  • Required columns: Chromosome, Start, End.
• (DEL/DUP/INS/INV)_FrqIndex.csv
  • CSV containing genomic locations of frequent variants for faster counts.
  • Required columns: Chromosome, Start, End.
• annotation.txt
  • Simple annotation file.
  • Required columns: Chromosome, Start, End, Feature.

Running the Test Set

A test dataset is present within Visualisation/Files/TestSet/, to perform a test run simply copy those files into Visualisation/Files/ and run Rscript easyRun.r.