Microbial Sequence Analysis and Loci-based Typing pipeline

The microbial sequence analysis and loci-based typing pipeline (microSALT) is used to analyse microbial samples. It produces a quality control of the sample, determines a sample's organism specific sequence type, and its resistance pattern. microSALT also provides a database storage solution and report generation of these results.

microSALT uses a combination of python, sqLite and flask. Python is used for the majority of functionality, the database is handled through sqLite and the front-end is handled through flask. All analysis activity by microSALT requires a SLURM cluster.

Quick installation

1. yes | bash <(curl https://raw.githubusercontent.com/Clinical-Genomics/microSALT/master/install.sh)
2. cp configExample.json $HOME/.microSALT/config.json
3. vim $HOME/.microSALT/config.json

Configuration

Copy the configuration file to microSALTs hidden home directory, or copy the configuration file anywhere and direct the envvar MICROSALT_CONFIG to it. See example:

cp configExample.json $HOME/.microSALT/config.json

or

cp configExample.json /MY/FAV/FOLDER/config.json
export MICROSALT_CONFIG=/MY/FAV/FOLDER/config.json

Then edit the fields to match your environment.

Usage

• microSALT analyse contains functions to start sbatch job(s) & produce output to folders['results']. Afterwards the parsed results are uploaded to the SQL back-end and produce reports (HTML), which are then automatically e-mailed to the user.
• microSALT utils contains various functionality, including generating the sample description json, manually adding new reference organisms and re-generating reports.

Databases

MLST Definitions

microSALT will automatically download & use the MLST definitions for any organism on pubMLST. Other definitions may be used, as long as they retain the same format.

Resistance genes

microSALT will automatically download & use the resistance genes of ResFinder. Any definitions will work, as long as they retain the same formatting.

Requirements

Hardware

• A SLURM enabled HPC system
• A (clarity) LIMS server

Software

• Conda
• Python 3.6
• SQLite

Contributing to this repo

This repository follows the Github flow approach to adding updates. For more information, see https://guides.github.com/introduction/flow/

Credits

• Isak Sylvin - Lead developer
• Emma Sernstad - Accreditation ready reports
• Tanja Normark - Various issues
• Maya Brandi - Various issues