Feature wishlist

Introduction

At the upstart meeting we decided that the Stockholm node creates an initial feature wish-list based on previous discussions at Stockholm clinical microbiology.

This list were to be divided into initial, intermediate and long-term needs to try to already identify what a MVP should contain.

Initial Stockholm wishlist

Initial

Features an MVP should have

• 1: QC:

  • A table including:
    • Total bases
    • The number of raw reads
    • Trimmed reads
    • Filtered reads
    • Reads mapped to the host genome (human)
    • Input reads for classifiers
    • Unclassified reads
    • Reads assigned to Homo sapiens, fungi, archaea, bacteria and viruses, respectively.
  • View/download multiQC report

• 2: visualisation of classification results

  • Individual Krona plots for each classifier.
  • A pretty table displaying the number of reads per hit from different classifiers based on Taxpasta outputs.

• 3: Metadata

  • A table including sample information, sample source, batch, ticket number, priority, accreditation, library preparation, CT values, wet-lab methods, Taxprofiler version, and software versions.
  • A brief description, a few sentences, of the taxprofiler pipeline analysis used to produce the results.
  • A summary table of tickets, sample information, key QC metrics, pass or fail status (?), and the number of reads assigned to viruses.

Intermediate

Features which can wait until follow-up releases

• Manually uploading mapping results for post-processing analyses and displaying coverage plots.
• Krona plots for each sample across different classifiers.
• Flag known pathogens and contaminants, and provide a list of pathogens and contaminants.
• Ability to download an accreditation report.
• Barplots for high-level taxonomic profile comparisons between classifiers for a sample (stacked normalized bar plots for (P)hylum/(C)lass).
  • Stacked normalised bar plot for high-level taxonomic profile comparisons between samples for a classifier.

Longterm

Features which would be nice/interesting to explore long-term

• Validation
  • A click button to run post-processing in a separate repository to validate the interesting species.
    • KrakenTools will be used to extract reads from Kraken2 report. Custom scripts will be needed to extract reads from reports generated by other classifiers.
    • Run BLAST separately for the species of interest.
    • Mapping: Map the extracted reads against the target genome and the human genome.
• Visualisation of mapping results using IGV; consult the Scout group for guidance.
• Comparison of the same organisms across samples, which could be done by Taxpasta in the near future and displayed as a table.
• Request and link to different analyses by other pipelines for a sample:
  • Resistance analysis?
  • Species specific typing analysis?
  • Extend metagenomics analysis: mag, funscan etc.