recipe bioconductor-fastqcleaner

A Shiny Application for Quality Control, Filtering and Trimming of FASTQ Files






An interactive web application for quality control, filtering and trimming of FASTQ files. This user-friendly tool combines a pipeline for data processing based on Biostrings and ShortRead infrastructure, with a cutting-edge visual environment. Single-Read and Paired-End files can be locally processed. Diagnostic interactive plots (CG content, per-base sequence quality, etc.) are provided for both the input and output files.

package bioconductor-fastqcleaner

(downloads) docker_bioconductor-fastqcleaner



depends bioconductor-biostrings:


depends bioconductor-iranges:


depends bioconductor-s4vectors:


depends bioconductor-shortread:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-dt:

depends r-htmltools:

depends r-rcpp:


depends r-shiny:

depends r-shinybs:



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 bioconductor-fastqcleaner

and update with::

   mamba update bioconductor-fastqcleaner

To create a new environment, run:

mamba create --name myenvname bioconductor-fastqcleaner

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 `bioconductor-fastqcleaner/tags`_ for valid values for ``<tag>``)

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