Merged all custom images into one

        self.frag_hist['group'] = group_short

        self.frag_hist['replicate'] = rep_short

        self.frag_hist = self.frag_hist.reset_index(drop=True)

        self.frag_violin = pd.DataFrame( { "fragment_size" : frags_arr, "group" : group_arr , "replicate": rep_arr} )

    def load_binned_frags(self):

FROM nfcore/base:2.1

# Install conda packages

COPY ./environment.yml /

RUN conda env create -f /environment.yml && conda clean -a

ENV PATH /opt/conda/envs/packages/bin:$PATH

# conda env create -f environment.yml

name: packages

channels:

  - conda-forge

  - bioconda

  - defaults

dependencies:

  # python version

  - python=3.9.*

  # conda packages

  - numpy=1.22.*

  - pandas=1.4.*

  - seaborn=0.11.*

  - deeptools=3.5.*

  - pysam=0.19.*

  - pyranges=0.0.*

 # - dask=2021.9.1

  - dask=2022.*

  - conda-forge::upsetplot=0.6.*

    label 'process_high'

    conda (params.enable_conda ? "conda-forge::python=3.8.3 bioconda::deeptools=3.5.* bioconda::pysam=0.17.*" : null)

    container "luslab/cutandrun-dev-frip:latest"

    container "chrischeshire/nfcore-cutandrun:latest"

    input:

    tuple val(meta), path(bam), path(bai), path(bed)

    label 'process_ultralow'

    conda (params.enable_conda ? "conda-forge::python=3.8.3 conda-forge::dask=2021.9.1 conda-forge::pandas=1.3.3" : null)

    container "luslab/cutandrun-dev-peakrepo:latest"

    container "chrischeshire/nfcore-cutandrun:latest"

    input:

    tuple val(meta), path(bed)