33  Pathogenwatch 2

TipLearning Objectives
  • Analyse S. penumoniae genomes on Pathogenwatch and extract relevant information to use as metadata to annotate phylogenetic trees.
ExerciseExercise 1 - Analysing Pneumococcal genomes with Pathogenwatch

Whilst you can upload FASTQ files to Pathogenwatch, it’s quicker if we work with already assembled genomes. We’ve provided pre-processed results for the S. pneumoniae data generated with assembleBAC in the preprocessed/ directory which you can use to upload to Pathogenwatch in this exercise.

  • Upload the assembled S. pneumoniae genomes to Pathogenwatch.
  • Once Pathogenwatch has finished processing the genomes, save the results to a collection called Chaguza Serotype 1.
  • Download the Typing and AMR profile tables to the S_pneumoniae directory.
  • Rename the tables to chaguza-serotype-1-typing.csv and chaguza-serotype-1-amr-profile.csv respectively.
  • Merge the two tables with sample_info.csv by running the merge_pneumo_data.py script in the scripts directory. Make sure you are on the base software environment.
    • Note: If you have not managed to run the Pathogenwatch analysis, we provide the output files from the previous steps in preprocessed/pathogenwatch that you can use instead.

Refer back to Pathogenwatch if you need a reminder on how to perform these tasks.

  • We opened Pathogenwatch in our web browser and logged in. We then clicked on UPLOAD, the Upload FASTA(s) button in the “Single Genome FASTAs” section and the + button before navigating to the preprocessed/assemblebac/assemblies directory. We then selected all the assembly files and clicked Open on the dialogue window.
  • We waited for Pathogenwatch to finish processing the genomes, clicked the VIEW GENOMES button, then saved the results to a collection called Chaguza Serotype 1 by clicking Selected Genomes –> Create Collection and adding Chaguza Serotype 1 to the Title box. Finally, we clicked Create Now button to create our collection.

  • We clicked on the download icon in the top right-hand corner and selected Typing table.
  • We clicked on the download icon in the top right-hand corner and selected AMR profile.
  • We renamed the files to chaguza-serotype-1-typing.csv and chaguza-serotype-1-amr-profile.csv respectively and moved them to the S_pneumoniae directory.
  • We went back to the base software environment with mamba activate base
  • We ran the merge_pneumo_data.py script to create a TSV file called pneumo_metadata.tsv in your analysis directory:
python scripts/merge_pneumo_data.py -s sample_info.csv -t chaguza-serotype-1-typing.csv -a chaguza-serotype-1-amr-profile.csv