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 in your sample. By setting an abundance threshold, any species below the threshold will be added to an 'other' category (>1% by default).
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. Optional QC is performed with chopper. Data is visualized using the Plotly library.

Installation

Follow EMU's installation instructions from the repo. If you want to filter based on qualityscores or length, install chopper with the instructions from the repo After installing EMU, install GermGenie in the same conda environment.

python -m pip install GermGenie

Usage

usage: GermGenie [-h] [--version] [--threads THREADS]
                 [--threshold THRESHOLD] [--tsv] [--nreads]
                 [--subsample SUBSAMPLE] [--top_n TOP_N]
                 [--min-length MIN_LENGTH] [--max-length MAX_LENGTH]
                 [--min-quality MIN_QUALITY]
                 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

options:
  -h, --help            show this help message and exit
  --version             Show program's version number 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)
  --nreads, -nr         Visualize number of reads per sample in
                        barplot
  --subsample SUBSAMPLE, -s SUBSAMPLE
                        WARNING: DO NOT USE !!!
  --top_n TOP_N, -tn TOP_N
                        Number of top taxa to plot. 0 for all taxa.
  --min-length MIN_LENGTH, -mil MIN_LENGTH
                        Minimum length of reads to keep. Default is
                        to keep all reads.
  --max-length MAX_LENGTH, -mal MAX_LENGTH
                        Maximum length of reads to keep. Default is
                        to keep all reads.
  --min-quality MIN_QUALITY, -miq MIN_QUALITY
                        Minimum average Phred quality score of reads
                        to keep. Default is to keep all reads.

Developed by Daan Brackel, Birgit Rijvers & 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-0.1.9.tar.gz (7.1 kB view details)

Uploaded Source

Built Distribution

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

germgenie-0.1.9-py3-none-any.whl (7.9 kB view details)

Uploaded Python 3

File details

Details for the file germgenie-0.1.9.tar.gz.

File metadata

  • Download URL: germgenie-0.1.9.tar.gz
  • Upload date:
  • Size: 7.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for germgenie-0.1.9.tar.gz
Algorithm Hash digest
SHA256 9b0137cfb84778ff5a277783e348b82876ee115cbde58b291a3f2631bb387c47
MD5 ed777db952b07d0f25b28cb2418d5497
BLAKE2b-256 e9d4da21e33b092efa1859e69f55078ea5276bd962c5a81a9e5533209cdc826f

See more details on using hashes here.

File details

Details for the file germgenie-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: germgenie-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 7.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for germgenie-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 57adddfdeb612274bdaf974038ea880088ec9424e5c328b94cdf35c493a77e73
MD5 dca505aef1393721190d9e837f583017
BLAKE2b-256 2e1090f20ecc5b5bf62c66903bdf61a1fccd1aa05ee7b176e7d04d257f740121

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