Description of feature

Dear NFcore-ATACseq team,
when running nf-core/atacseq -r 2.1.2 I noticed in the .command.log of the tasks NFCORE_ATACSEQ:ATACSEQ:FASTQ_FASTQC_UMITOOLS_TRIMGALORE:TRIMGALORE that this rule seems to make inefficient use of gzip trying to parallelize. A solution could be to add pigz to the Singularity container. I did not specify extra number of cores, etc.. See below the relevant part of .command.log:

====.coomand.log:
Using an excessive number of cores has a diminishing return! It is recommended not to exceed 8 cores per trimming process (you asked for 8 cores). Please consider re-specifying
Path to Cutadapt set as: 'cutadapt' (default)
Cutadapt seems to be working fine (tested command 'cutadapt --version')
Cutadapt version: 3.4
Could not detect version of Python used by Cutadapt from the first line of Cutadapt (but found this: >>>#!/bin/sh<<<)
Letting the (modified) Cutadapt deal with the Python version instead
Proceeding with 'gzip' for compression. PLEASE NOTE: Using multi-cores for trimming with 'gzip' only has only very limited effect! (see here: FelixKrueger/TrimGalore#16 (comment))
To increase performance, please install 'pigz' and run again

==== call of workflow:
nextflow run nf-core/atacseq -r 2.1.2 -profile singularity -c hpc_slurm_cbg_execution.config
--input samplesheet.csv
--outdir .
--read_length 100
--fasta genome/mm39_dm6.fa
--gtf genome/mm39_dm6.gtf
--blacklist genome/mm39_dm6_bl_v2.bed
--mito_name MT
--ataqv_mito_reference MT
--trim_nextseq 20
--aligner bowtie2
--keep_dups false
--keep_multi_map false
--narrow_peak false
--min_reps_consensus 1
--save_macs_pileup true
--deseq2_vst true
--skip_deseq2_qc false

==== hpc_slurm_cbg_execution.config:
process{
executor='slurm'
queue='batch'
clusterOptions = '--ntasks=1 --time=24:00:00'
}

==== nextflow version:
nextflow version 24.04.4.5917