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Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning

Code sharing for the ciprofloxacin prediction research.
Published paper: https://www.nature.com/articles/s41598-020-71693-5

Used reference genome:

wget ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/743/255/GCA_000743255.1_ASM74325v1/GCA_000743255.1_ASM74325v1_genomic.fna.gz

Running the whole project requires ~ 3 TB storage and a machine with 64 GB RAM.

Code and data downloading details

  1. run data_download/wrapper_download.sh
  • also set the bash variables in that file according to your local folder system (folders must exist)
  • this script will download the MIC metadata, the FASTQ files and check the md5sum of the downloaded files
  1. run data_preprocess/wrapper_preprocess.sh
  • also set the bash variables in that file according to your local folder system (folders must exist)
  • this script will generate VCF files and an SNP matric from the samples and run the resfinder on the samples
  1. run the jupyter notebooks in the machine_learning_and_stats folder

Version:

  • python 3.6.5
  • samtools 1.9
  • bcftools 1.9
  • bwa 0.7.17
  • resfinder 3.1.0
  • KMA 1.1.4

Python package versions can be found in the requirements.txt file.

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Code sharing for the ciprofloxacin prediction research

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