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-0.0.3.tar.gz (4.6 kB view details)

Uploaded Source

Built Distribution

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

GermGenie-0.0.3-py3-none-any.whl (5.7 kB view details)

Uploaded Python 3

File details

Details for the file GermGenie-0.0.3.tar.gz.

File metadata

  • Download URL: GermGenie-0.0.3.tar.gz
  • Upload date:
  • Size: 4.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for GermGenie-0.0.3.tar.gz
Algorithm Hash digest
SHA256 33024d71ea05a809508b275d93f48f3f4775f34578352661fdde3d283fb3e51d
MD5 61f037414b090a9b98acd0cc9e6f9102
BLAKE2b-256 edd613f1fd516deadab3ee5d02dfb4cf33925648c74cf32e51ee06c07c3fb8f0

See more details on using hashes here.

File details

Details for the file GermGenie-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: GermGenie-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 5.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for GermGenie-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 cdf0166990d5c5de2e7b9612e5188707fa76533bd4c8ab54a106c54bf0dfe068
MD5 67be4db1dc27134da5dfc9a1d93e9468
BLAKE2b-256 90623bc0c711aac1f2f9c47b4fe3a9018baa737b592715ecd4c5126eeb0ee638

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