From bd27edc8595ccecc753c50dae56a20a2e4b5a054 Mon Sep 17 00:00:00 2001 From: cflerin Date: Tue, 19 May 2020 11:01:47 +0200 Subject: [PATCH] Documentation updates for 0.10.1 --- README.rst | 20 ++++++++++++++++--- docs/installation.rst | 45 +++++++++++++++++++++++-------------------- 2 files changed, 41 insertions(+), 24 deletions(-) diff --git a/README.rst b/README.rst index bcb18a3..7f8bf44 100644 --- a/README.rst +++ b/README.rst @@ -17,6 +17,14 @@ in no time. The latter is achieved via the dask_ framework for distributed compu News ---- +2020-05-17 +^^^^^^^^^^ + +**0.10.1 release** + +* CLI: file compression (optionally) enabled for intermediate files for the major steps: grn (adjacencies matrix), ctx (regulons), and aucell (auc matrix). Compression is used when the file name argument has a .gz ending. + + 2020-02-27 ^^^^^^^^^^ @@ -47,10 +55,15 @@ All the functionality of the original R implementation is available and in addit 3. Regulons, i.e. the regulatory network that connects a TF with its target genes, with targets that are repressed are now also derived and used for cell enrichment analysis. -Website -------- +Additional resources +-------------------- + +For more information, please visit LCB_, or SCENIC_ (R version). +The CLI to pySCENIC has also been streamlined into a pipeline that can be run with a single command, using the Nextflow workflow manager. +There are two Nextflow implementations available: -For more information, please visit LCB_, SCENIC_ (R version), or SCENICprotocol_ (for a Nextflow implementation). +* `SCENICprotocol`_: A Nextflow DSL1 implementation of pySCENIC alongside a basic "best practices" expression analysis. Includes details on pySCENIC installation, usage, and downstream analysis, along with detailed tutorials. +* `VSNPipelines`_: A Nextflow DSL2 implementation of pySCENIC with a comprehensive and customizable pipeline for expression analysis. Includes additional pySCENIC features (multi-runs, integrated motif- and track-based regulon pruning, loom file generation). Acknowledgments @@ -82,6 +95,7 @@ References .. _arboreto: https://arboreto.readthedocs.io .. _LCB: https://aertslab.org .. _`SCENICprotocol`: https://github.com/aertslab/SCENICprotocol +.. _`VSNPipelines`: https://github.com/vib-singlecell-nf/vsn-pipelines .. _notebooks: https://github.com/aertslab/pySCENIC/tree/master/notebooks .. _issue: https://github.com/aertslab/pySCENIC/issues/new .. _PyPI: https://pypi.python.org/pypi/pyscenic diff --git a/docs/installation.rst b/docs/installation.rst index a491685..c8be575 100644 --- a/docs/installation.rst +++ b/docs/installation.rst @@ -115,31 +115,31 @@ A mount point (or more than one) needs to be specified, which contains the input .. code-block:: bash docker run -it --rm \ - -v /path/to/data:/scenicdata \ - aertslab/pyscenic:[version] pyscenic grn \ + -v /data:/data \ + aertslab/pyscenic:0.10.0 pyscenic grn \ --num_workers 6 \ - -o /scenicdata/expr_mat.adjacencies.tsv \ - /scenicdata/expr_mat.tsv \ - /scenicdata/allTFs_hg38.txt + -o /data/expr_mat.adjacencies.tsv \ + /data/expr_mat.tsv \ + /data/allTFs_hg38.txt docker run -it --rm \ - -v /path/to/data:/scenicdata \ - aertslab/pyscenic:[version] pyscenic ctx \ - /scenicdata/expr_mat.adjacencies.tsv \ - /scenicdata/hg19-tss-centered-5kb-7species.mc9nr.feather \ - /scenicdata/hg19-tss-centered-10kb-7species.mc9nr.feather \ - --annotations_fname /scenicdata/motifs-v9-nr.hgnc-m0.001-o0.0.tbl \ - --expression_mtx_fname /scenicdata/expr_mat.tsv \ + -v /data:/data \ + aertslab/pyscenic:0.10.0 pyscenic ctx \ + /data/expr_mat.adjacencies.tsv \ + /data/hg19-tss-centered-5kb-7species.mc9nr.feather \ + /data/hg19-tss-centered-10kb-7species.mc9nr.feather \ + --annotations_fname /data/motifs-v9-nr.hgnc-m0.001-o0.0.tbl \ + --expression_mtx_fname /data/expr_mat.tsv \ --mode "dask_multiprocessing" \ - --output /scenicdata/regulons.csv \ + --output /data/regulons.csv \ --num_workers 6 docker run -it --rm \ - -v /path/to/data:/scenicdata \ - aertslab/pyscenic:[version] pyscenic aucell \ - /scenicdata/expr_mat.tsv \ - /scenicdata/regulons.csv \ - -o /scenicdata/auc_mtx.csv \ + -v /data:/data \ + aertslab/pyscenic:0.10.0 pyscenic aucell \ + /data/expr_mat.tsv \ + /data/regulons.csv \ + -o /data/auc_mtx.csv \ --num_workers 6 Singularity @@ -169,7 +169,7 @@ The first step (GRN inference) is shown as an example: Using the Docker or Singularity images with Jupyter notebook ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -As of version 0.9.7, the pySCENIC containers have the `ipykernel` package installed, and can also be used interactively in a notebook. +As of version 0.9.7, the pySCENIC containers have the ``ipykernel`` package installed, and can also be used interactively in a notebook. This can be achieved using a kernel command similar to the following (for singularity). Note that in this case, a bind needs to be specified. @@ -181,12 +181,15 @@ Note that in this case, a bind needs to be specified. Nextflow -------- -The CLI to pySCENIC has also been streamlined into a pipeline that can be run with a single command, using the Nextflow workflow manager. -For details on this usage, along with more detailed pySCENIC tutorials, see the `SCENICprotocol`_ repository. +There are two Nextflow implementations available: + +* `SCENICprotocol`_: A Nextflow DSL1 implementation. +* `VSNPipelines`_: A Nextflow DSL2 implementation. .. _`Singularity Hub`: https://www.singularity-hub.org/collections/2033 .. _`SCENICprotocol`: https://github.com/aertslab/SCENICprotocol +.. _`VSNPipelines`: https://github.com/vib-singlecell-nf/vsn-pipelines .. _dask: https://dask.pydata.org/en/latest/ .. _distributed: https://distributed.readthedocs.io/en/latest/ .. _`Docker Hub`: https://hub.docker.com/r/aertslab/pyscenic