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Containers.md

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Almost all packages (excepting those with a "/" in their id in the table below) used by Cactus are Biocontainers. Biocontainer packages have the advantage to be available on conda and Mamba virtual environments, Singularity and Docker containers. As much as possible, single tools Biocontainers were used for easier maintenance. However, in some cases multiple-tools are needed (e.g. analysis in R) in which cases "mulled containers" were created via BioContainers' multi-package-containers tool. The download of all tools happens automatically the first time Cactus is run. Singularity images are hosted on the Galaxy singularity repository.

Below are more details regarding the use of Singularity containers.

Downloading all singularity containers uses 4 Gb of disk space in total. The parameter singularity_containers_path set in the ./.cactus.config file should be set to indicate in which directory the containers should be downloaded.

Here is the detail of the Singularity containers used and their size:

name size id
pypdf2:2.11.1 479M
bowtie2_samtools 463M mulled-v2-c742dccc9d8fabfcff2af0d8d6799dbc711366cf:b6524911af823c7c52518f6c886b86916d062940-0
figures 450M mulled-v2-e0e17c59e64598cdb16a01c347c673dd021f778a:0dd10d4b12b50eec83ccd1f7b7740a08f2703bdf-0
homer 434M homer:4.9.1--pl5.22.0_5
differential_analysis 309M mulled-v2-abcadfb509d8692abe35c0bd02689ab7756d85f8:1b35d287a7c9c53a258be40306bdca167e2e078a-0
venndiagram 306M pegi3s/r_venn-diagram:1.7.0
bbmap 293M bbmap:38.96--h5c4e2a8_0
r_basic 292M mulled-v2-b21cd52f0c50bbd777eaed41c0b8228b84cff4bd:b09be1d801d248a5a61257583e629f17052d8181-0
skewer_pigz 291M mulled-v2-734ede4cc65b3b212388567aac99f6182e023a8f:26fbad413ebdf8aee65d8aa554d52a4f69548508-0
fastqc 261M fastqc:0.11.7--4
bioconductor 167M mulled-v2-0161037c6d8979d1ff5de7e591f5adfb3ffe38b8:2b97ca0a3f4f5409852afe863ef8068a83779815-0
picard 165M picard:2.26.9--hdfd78af_0
diffbind 145M mulled-v2-9ec5efd66a9a09ea4f9ad9bad5485675f031aeb4:cf736786cecad89eca5fea6d119a837e4bad7c08-0
deeptools 107M deeptools:3.4.3--py_0
samtools_bedtools_perl 95M mulled-v2-95fc59e28f845da0ff950325f8138eff9cedff14:0bc453d1b98bff9aef79c31f643f6b9f93bc7fbd-0
sleuth 55M r-sleuth:0.30.0--r41hdfd78af_5
macs2 43M macs2:2.2.7.1--py37hf01694f_1
bioperl 21M perl-bioperl-core:1.007002--pl5321hdfd78af_4
kallisto 11M kallisto:0.46.2--h4f7b962_1
- - -
Total: 4081M -

Here are more details on the tools in each mulled container:

  • bowtie2_samtools: bowtie2=2.4.4, samtools=1.13
  • r_basic: r-base=4.1.3, r-magrittr=2.0.3, r-dplyr=1.0.9, r-purrr=0.3.4, r-ggplot2=3.3.5, r-data.table=1.14.2
  • samtools_bedtools_perl: samtools=1.15.1, bedtools=2.30.0, perl=5.32.1
  • skewer_pigz: skewer=0.2.2, pigz=2.6
  • bioconductor: r-base=4.3, bioconductor-chipseeker=1.36.0, r-magrittr=2.0.3, bioconductor-genomicfeatures=1.52.1, bioconductor-clusterprofiler=4.8.1, bioconductor-annotationdbi=1.62.2, r-purrr=1.0.2, r-ggplot2=3.4.4
  • diffbind: bioconductor-diffbind=3.4.0, bioconductor-csaw=1.28.0, bioconductor-edger=3.36.0, r-optparse=1.7.1
  • figures: r-base=4.3, r-ggplot2=3.4.4, r-magrittr=2.0.3, r-gridextra=2.3, r-rcolorbrewer=1.1_3, r-data.table=1.14.8
  • differential_abundance: r-base=4.1.3, bioconductor-diffbind=3.4.11, r-sleuth=0.30.0, r-ggplot2=3.3.5, r-magrittr=2.0.3, r-openxlsx=4.2.5