Skip to main content

Python wrapper for multi-sample 16S classification using EMU

Project description

GermGenie

GermGenie was specifically designed to analyse 16S data from clinical FFPE specimens, however it can be used to analyse any bacterial sample. GermGenie outputs stacked barplot showing the abundance of every species/genus in your sample. By setting an abundance threshold, any species/genus below the threshold will be added to an 'other' category.
This tool was designed with Oxford Nanopore sequencing reads (ONT), and was not tested with any other sequencing data. The input should be a folder containing one or more samples in a fastq.gz format.

Dependencies

The pipeline is based on EMU. Data is visualized using the Plotly library.

Installation

Follow EMU's installation instructions from the repo.
After installing EMU, install GermGenie in the same conda environment.

python -m pip install GermGenie

Usage

usage: GermGenie [-h] [--threads THREADS] [--threshold THRESHOLD] [--tsv]
                 fastq output db

EMU wrapper for analyzing and plotting relative abundance from 16S data

positional arguments:
  fastq                 Path to folder containing gzipped fastq files
  output                Path to directory to place results (created if not
                        exists.)
  db                    Path to EMU database

optional arguments:
  -h, --help            show this help message and exit
  --threads THREADS, -t THREADS
                        Number of threads to use for EMU classification
                        (defaults to 2)
  --threshold THRESHOLD, -T THRESHOLD
                        Percent abundance threshold. Abundances below
                        threshold will be shown as 'other' (defaults to 1
                        percent)
  --tsv                 Write abundances to tsv file (abundances.tsv)

Developed by Daan Brackel & Sander Boden @ ATLS-Avans

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

GermGenie-0.0.6.tar.gz (5.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

GermGenie-0.0.6-py3-none-any.whl (6.6 kB view details)

Uploaded Python 3

File details

Details for the file GermGenie-0.0.6.tar.gz.

File metadata

  • Download URL: GermGenie-0.0.6.tar.gz
  • Upload date:
  • Size: 5.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for GermGenie-0.0.6.tar.gz
Algorithm Hash digest
SHA256 ffd474012d29623e4bccf817f246cc2072fc696fdffa5174b70c415ee45c8cd8
MD5 cffe7bb8c0fdcb7a206a4c9a100110a1
BLAKE2b-256 7b385f61bc3a40fda3b940527041ac62fad99e7b928dd023b1e79eca38a14ddb

See more details on using hashes here.

File details

Details for the file GermGenie-0.0.6-py3-none-any.whl.

File metadata

  • Download URL: GermGenie-0.0.6-py3-none-any.whl
  • Upload date:
  • Size: 6.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for GermGenie-0.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 bd3d5715a87822b7e72f64f68d225ca709eeb1eb604601ffcacf141db5d666d9
MD5 19c7b2b25600d12d346a5856c63097e5
BLAKE2b-256 6f6f043fdee894c6501678f46ff7064ebe68464328b1517afbf28fcca9129d80

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page