Docker & Singularity/Apptainer images for convenience. These containers can also be found on:
- DockerHub.
- Internally on the HPC group directory
ref/singularity_images
| Docker image | Description | Reference | Repository |
|---|---|---|---|
| cell2location | Cell type deconvolution tool for Spatial Transcriptomics | Kleshchevnikov, V., Shmatko, A., Dann, E. et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nat Biotechnol 40, 661–671 (2022). https://doi.org/10.1038/s41587-021-01139-4 | GitHub |
| Giotto | Toolbox for Spatial Transcriptomics. Micromamba-based image with R-version 4.4.1. Also contains pak, GaitiLab/GaitiLabUtils and radian |
Dries, R., Zhu, Q., Dong, R. et al. Giotto: a toolbox for integrative analysis and visualization of spatial expression data. Genome Biol 22, 78 (2021). https://doi.org/10.1186/s13059-021-02286-2; Dong, R., Yuan, GC. SpatialDWLS: accurate deconvolution of spatial transcriptomic data. Genome Biol 22, 145 (2021). https://doi.org/10.1186/s13059-021-02362-7 | GitHub |
| RCTD | Tool for cell type annotation of Spatial Transcriptomics. Image builds on the Seurat_v5 image (v5.1.0). |
Cable, D.M., Murray, E., Zou, L.S. et al. Robust decomposition of cell type mixtures in spatial transcriptomics. Nat Biotechnol 40, 517–526 (2022). https://doi.org/10.1038/s41587-021-00830-w | GitHub |
| Seurat_v4 | Micromamba-based image with R version 4.3.3, Seurat v4.4.0 & GaitiLab/GaitiLabUtils. Commonly used packages are also installed: pak, tidyverse, data.table, stringr. For convenience when working interactively, radian is installed as well. |
Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zager, M., Hoffman, P., Stoeckius, M., Papalexi, E., Mimitou, E. P., Jain, J., Srivastava, A., Stuart, T., Fleming, L. M., Yeung, B., … Satija, R. (2021). Integrated analysis of multimodal single-cell data. Cell, 184(13), 3573-3587.e29. https://doi.org/10.1016/j.cell.2021.04.048 | Seurat |
| seurat_v5 | Micromamba-based image with R version 4.3.3, Seurat v5.1.0 & GaitiLab/GaitiLabUtils. Commonly used packages are also installed: pak, tidyverse, data.table, stringr. For convenience when working interactively, radian is installed as well. |
Hao, Y., Stuart, T., Kowalski, M.H. et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat Biotechnol 42, 293–304 (2024). https://doi.org/10.1038/s41587-023-01767-y | Seurat |
| cell2cell | Image used in the Nextflow pipeline GaitiLab/scrnaseq-cellcomm-pipeline to run cell2cell. Image is based on Python 3.10.8 |
Armingol E, Ghaddar A, Joshi CJ, Baghdassarian H, Shamie I, et al. (2022) Inferring a spatial code of cell-cell interactions across a whole animal body. PLOS Computational Biology 18(11): e1010715. https://doi.org/10.1371/journal.pcbi.1010715 | GitHub |
| cellphonedb | Image used in the Nextflow pipeline GaitiLab/scrnaseq-cellcomm-pipeline to run CellPhoneDB v5. Image is based on Python 3.8.18 |
Garcia-Alonso, L., Lorenzi, V., Mazzeo, C. I. et al. Single-cell roadmap of human gonadal development. Nature 607, 540–547 (2022). https://doi.org/10.1038/s41586-022-04918-4 | GitHub |
| scrnaseqcellcomm | Image used in the Nextflow pipeline GaitiLab/scrnaseq-cellcomm-pipeline to run all Rscripts, incl. CellChat (v2.1.2)& LIANA (v0.1.14). The image installs R-version 4.2.2, Seurat 4.4.0 and GaitiLab/GaitiLabUtils |
Jin, S., Plikus, M. V., & Nie, Q. (2023). CellChat for systematic analysis of cell-cell communication from single-cell and spatially resolved transcriptomics (p. 2023.11.05.565674). bioRxiv. https://doi.org/10.1101/2023.11.05.565674; Dimitrov, D., Türei, D., Garrido-Rodriguez M., Burmedi P. L., Nagai, J. S., Boys, C., Flores, R. O. R., Kim, H., Szalai, B., Costa, I. G., Valdeolivas, A., Dugourd, A. and Saez-Rodriguez, J. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat Commun 13, 3224 (2022). https://doi.org/10.1038/s41467-022-30755-0 | CellChat v2, LIANA, scrnaseq-cellcomm |
| cytotrace2 | Based on the joank23/seurat:4.4.0 image. Contains the R-based version of cytoTRACE2. |
Kang M, Armenteros JJA, Gulati GS, Gleyzer R, Avagyan S, Brown EL, Zhang W, Usmani A, Earland N, Wu Z, Zou J, Fields RC, Chen DY, Chaudhuri AA, Newman AM. Mapping single-cell developmental potential in health and disease with interpretable deep learning. bioRxiv Preprint. 2024 Mar 21:2024.03.19.585637. doi: 10.1101/2024.03.19.585637. PMID: 38562882; PMCID: PMC10983880. | GitHub |
| mutational_signatures | Image to be used for mutational signature analysis. Based on R-version 4.3.1 and MutationalPatterns 3.12.0. |
Manders, F., Brandsma, A.M., de Kanter, J. et al. MutationalPatterns: the one stop shop for the analysis of mutational processes. BMC Genomics 23, 134 (2022). https://doi.org/10.1186/s12864-022-08357-3 | GitHub,BioConductor |
| Monocle3 | Image based on joank23/seurat:4.4.0 |
Trapnell C. et. al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014). https://doi.org/10.1038/nbt.2859; Qiu, X. et. al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979–982 (2017). https://doi.org/10.1038/nmeth.4402; Cao, J. et. al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019). https://doi.org/10.1038/s41586-019-0969-x | Monocle3 |
| ensemble_vep | Image downloaded from Ensemble VEP (version 113) | https://doi.org/10.1093/nar/gkad1049 | Ensemble VEP |
| sigprofiler | Image to be used for Alexandrov's SigProfiler suite (mutational signature extraction and assignment). SigProfilerMatrixGenerator (1.3.2), SigProfilerPlotting (1.4.1) and SigProfilerAssignment (0.1.8) |
Bergstrom EN, Huang MN, Mahto U, Barnes M, Stratton MR, Rozen SG, and Alexandrov LB (2019) SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events. BMC Genomics 20, Article number: 685. https://doi.org/10.1186/s12864-019-6041-2 | Github |
- Build image
- Save Docker image as '.tar'
docker save <docker-image> > <docker-image>.tar- Move tar file to H4H
- Build Apptainer/Singularity image
module load apptainer
export APPTAINER_CACHEDIR=$PWD/cache
export APPTAINER_TMPDIR=$PWD/tmp
mkdir -p $APPTAINER_CACHEDIR
mkdir -p $APPTAINER_TMPDIR
apptainer build <image>.sif docker-archive:<image>.tar
rm -rf $APPTAINER_CACHEDIR
rm -rf $APPTAINER_TMPDIR- Running a container interactively
module load apptainer
apptainer run <image>.sif <command>- Build image
# platform, e.g. linux/amd64, linux/arm64
docker buildx build -t <name> . --platform <your-platform>- Running a container interactively.
# platform, e.g. linux/amd64 linux/arm64
docker run -it --rm --platform <your-platform> <docker-image> <command>- Build image from DockerHub (https://hub.docker.com/repositories/joank23)
apptainer build <image>.sif docker://<docker-hub-image>- Running a container interactively
apptainer run <image>.sif <command>