recipe afterqc

Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data. AfterQC can simply go through all fastq files in a folder and then output three folders: good, bad and QC folders, which contains good reads, bad reads and the QC results of each fastq file/pair. Currently it supports processing data from HiSeq 2000/2500/3000/4000, Nextseq 500/550, MiniSeq…and other Illumina 1.8 or newer formats.






package afterqc

(downloads) docker_afterqc



depends python:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install afterqc

and update with::

   mamba update afterqc

To create a new environment, run:

mamba create --name myenvname afterqc

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `afterqc/tags`_ for valid values for ``<tag>``)

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