diff --git a/docker/cumulus/1.3.0/Dockerfile b/docker/cumulus/1.3.0/Dockerfile new file mode 100644 index 00000000..9d93d615 --- /dev/null +++ b/docker/cumulus/1.3.0/Dockerfile @@ -0,0 +1,73 @@ +FROM debian:buster-slim +SHELL ["/bin/bash", "-c"] + +RUN mkdir -p /usr/share/man/man1 && \ + apt-get -qq update && \ + apt-get -qq -y install --no-install-recommends \ + build-essential \ + gnupg \ + libfftw3-dev \ + default-jdk \ + curl \ + python3 \ + python3-dev \ + python3-pip + +RUN echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] http://packages.cloud.google.com/apt cloud-sdk main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list && \ + curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key --keyring /usr/share/keyrings/cloud.google.gpg add - && \ + apt-get update -y && apt-get install -y google-cloud-sdk=326.0.0-0 + +RUN ln -s /usr/bin/python3 /usr/bin/python + +RUN python -m pip install --upgrade pip --no-cache-dir && \ + python -m pip install setuptools==53.0.0 --no-cache-dir && \ + python -m pip install numpy==1.19.5 --no-cache-dir && \ + python -m pip install pandas==1.2.1 --no-cache-dir && \ + python -m pip install scipy==1.5.4 --no-cache-dir && \ + python -m pip install Cython==0.29.21 --no-cache-dir && \ + python -m pip install pybind11==2.6.2 --no-cache-dir && \ + python -m pip install scikit-image==0.18.1 --no-cache-dir && \ + python -m pip install scikit-learn==0.24.1 --no-cache-dir && \ + python -m pip install h5py==3.1.0 --no-cache-dir && \ + python -m pip install fitsne==1.1.1 --no-cache-dir && \ + python -m pip install importlib-metadata==3.4.0 --no-cache-dir && \ + python -m pip install joblib==1.0.0 --no-cache-dir && \ + python -m pip install psutil==5.8.0 --no-cache-dir && \ + python -m pip install threadpoolctl==2.1.0 --no-cache-dir && \ + python -m pip install python-igraph==0.8.3 --no-cache-dir && \ + python -m pip install leidenalg==0.8.3 --no-cache-dir && \ + python -m pip install lightgbm==3.1.1 --no-cache-dir && \ + python -m pip install loompy==3.0.6 --no-cache-dir && \ + python -m pip install matplotlib==3.3.4 --no-cache-dir && \ + python -m pip install natsort==7.1.1 --no-cache-dir && \ + python -m pip install numba==0.52.0 --no-cache-dir && \ + python -m pip install scanorama==1.7 --no-cache-dir && \ + python -m pip install scikit-misc==0.1.3 --no-cache-dir && \ + python -m pip install seaborn==0.11.1 --no-cache-dir && \ + python -m pip install statsmodels==0.12.2 --no-cache-dir && \ + python -m pip install numcodecs==0.7.3 --no-cache-dir && \ + python -m pip install networkx==2.5 --no-cache-dir && \ + python -m pip install zarr==2.6.1 --no-cache-dir && \ + python -m pip install anndata==0.7.5 --no-cache-dir && \ + python -m pip install hnswlib==0.5.0 --no-cache-dir && \ + python -m pip install louvain==0.7.0 --no-cache-dir && \ + python -m pip install umap-learn==0.4.6 --no-cache-dir && \ + python -m pip install torch==1.7.1 --no-cache-dir && \ + python -m pip install harmony-pytorch==0.1.6 --no-cache-dir && \ + python -m pip install cirrocumulus==1.1.13.post1 --no-cache-dir && \ + python -m pip install annoy==1.17.0 --no-cache-dir && \ + python -m pip install pegasusio==0.2.10 --no-cache-dir && \ + python -m pip install demuxEM==0.1.5.post1 --no-cache-dir && \ + python -m pip install forceatlas2-python==1.1 --no-cache-dir && \ + python -m pip install pegasuspy==1.3.0 --no-cache-dir + +RUN apt-get -qq -y remove curl gnupg && \ + apt-get -qq -y autoremove && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* /var/log/dpkg.log + +RUN mkdir /software +ADD https://raw.githubusercontent.com/klarman-cell-observatory/cumulus/master/docker/monitor_script.sh /software +RUN chmod a+rx /software/monitor_script.sh + +ENV PATH=/software:$PATH diff --git a/docker/pegasus-terra/1.3/Dockerfile b/docker/pegasus-terra/1.3/Dockerfile new file mode 100644 index 00000000..10682c4a --- /dev/null +++ b/docker/pegasus-terra/1.3/Dockerfile @@ -0,0 +1,69 @@ +FROM us.gcr.io/broad-dsp-gcr-public/terra-jupyter-base:0.0.19 +USER root +#this makes it so pip runs as root, not the user +ENV PIP_USER=false + +RUN apt-get update && apt-get install -yq --no-install-recommends \ + build-essential \ + python3-dev \ + libfftw3-dev && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +RUN pip3 -V && \ + pip3 install --upgrade pip && \ + pip3 install setuptools==53.0.0 && \ + pip3 install numpy==1.19.5 && \ + pip3 install pandas==1.2.1 && \ + pip3 install scipy==1.5.4 && \ + pip3 install Cython==0.29.21 && \ + pip3 install pybind11==2.6.1 && \ + pip3 install scikit-image==0.18.1 && \ + pip3 install scikit-learn==0.24.1 && \ + pip3 install h5py==3.1.0 && \ + pip3 install fitsne==1.1.1 && \ + pip3 install importlib-metadata==3.4.0 && \ + pip3 install joblib==1.0.0 && \ + pip3 install psutil==5.8.0 && \ + pip3 install threadpoolctl==2.1.0 && \ + pip3 install python-igraph==0.8.3 && \ + pip3 install leidenalg==0.8.3 && \ + pip3 install lightgbm==3.1.1 && \ + pip3 install loompy==3.0.6 && \ + pip3 install matplotlib==3.3.4 && \ + pip3 install natsort==7.1.1 && \ + pip3 install numba==0.52.0 && \ + pip3 install scanorama==1.7 && \ + pip3 install scikit-misc==0.1.3 && \ + pip3 install seaborn==0.11.1 && \ + pip3 install statsmodels==0.12.2 && \ + pip3 install numcodecs==0.7.3 && \ + pip3 install networkx==2.5 && \ + pip3 install zarr==2.6.1 && \ + pip3 install anndata==0.7.5 && \ + pip3 install hnswlib==0.5.0 && \ + pip3 install louvain==0.7.0 && \ + pip3 install umap-learn==0.4.6 && \ + pip3 install torch==1.7.1 && \ + pip3 install harmony-pytorch==0.1.6 && \ + pip3 install cirrocumulus==1.1.13.post1 && \ + pip3 install annoy==1.17.0 && \ + pip3 install pegasusio==0.2.10 && \ + pip3 install demuxEM==0.1.5.post1 && \ + pip3 install forceatlas2-python==1.1 && \ + pip3 install pegasuspy==1.3.0 + +RUN wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip && \ + unzip ngrok-stable-linux-amd64.zip && \ + rm ngrok-stable-linux-amd64.zip && \ + mkdir -p /software && \ + mv ngrok /software/ + +ENV PATH=/software:$PATH + +ENV USER jupyter-user +USER $USER +#we want pip to install into the user's dir when the notebook is running +ENV PIP_USER=true + +ENTRYPOINT ["/usr/local/bin/jupyter", "notebook"] diff --git a/docker/pegasus-terra/1.3/pegasus-terra-1.3-versions.json b/docker/pegasus-terra/1.3/pegasus-terra-1.3-versions.json new file mode 100644 index 00000000..c4f14d79 --- /dev/null +++ b/docker/pegasus-terra/1.3/pegasus-terra-1.3-versions.json @@ -0,0 +1,68 @@ +{ + "python": { + "adjustText": "0.7.3", + "anndata": "0.7.5", + "annoy": "1.17.0", + "cirrocumulus": "1.1.13.post1", + "Cython": "0.29.21", + "demuxEM": "0.1.5.post1", + "firecloud": "0.16.25", + "fitsne": "1.1.1", + "forceatlas2-python": "1.1", + "gprofiler-official": "1.0.0", + "h5py": "3.1.0", + "harmony-pytorch": "0.1.6", + "hnswlib": "0.5.0", + "importlib-metadata": "3.4.0", + "joblib": "1.0.0", + "jupyter": "1.0.0", + "jupyter-client": "6.1.11", + "jupyter-console": "6.2.0", + "jupyter-contrib-core": "0.3.3", + "jupyter-contrib-nbextensions": "0.5.1", + "jupyter-core": "4.7.0", + "jupyter-highlight-selected-word": "0.2.0", + "jupyter-latex-envs": "1.4.6", + "jupyter-nbextensions-configurator": "0.4.1", + "jupyterlab": "0.35.4", + "jupyterlab-pygments": "0.1.2", + "jupyterlab-server": "0.2.0", + "leidenalg": "0.8.3", + "lightgbm": "3.1.1", + "loompy": "3.0.6", + "louvain": "0.7.0", + "matplotlib": "3.3.4", + "natsort": "7.1.1", + "nbclient": "0.5.1", + "nbconvert": "6.0.7", + "nbformat": "5.1.2", + "networkx": "2.5", + "notebook": "6.1.1", + "numba": "0.52.0", + "numpy": "1.19.5", + "pandas": "1.2.1", + "pegasusio": "0.2.10", + "pegasuspy": "1.3.0", + "Pillow": "8.1.0", + "pip": "21.0.1", + "pyarrow": "3.0.0", + "pybind11": "2.6.1", + "python-igraph": "0.8.3", + "scanorama": "1.7", + "scikit-image": "0.18.1", + "scikit-learn": "0.24.1", + "scikit-misc": "0.1.3", + "scipy": "1.5.4", + "seaborn": "0.11.1", + "setuptools": "53.0.0", + "statsmodels": "0.12.2", + "torch": "1.7.1", + "umap-learn": "0.4.6", + "XlsxWriter": "1.3.7", + "zarr": "2.6.1" + }, + "tools": { + "google-cloud-sdk": "324.0.0", + "ngrok": "2.3.35" + } +} \ No newline at end of file diff --git a/docs/cumulus.rst b/docs/cumulus.rst index d2fe40f5..de92978c 100644 --- a/docs/cumulus.rst +++ b/docs/cumulus.rst @@ -121,11 +121,10 @@ Cumulus steps: #. **plot**. This step is optional. In this step, **Cumulus** can generate 6 types of figures based on the **cluster** step results: - **composition** plots which are bar plots showing the cell compositions (from different conditions) for each cluster. This type of plots is useful to fast assess library quality and batch effects. - - **tsne**, **fitsne**, and **net_tsne**: t-SNE like plots based on different algorithms, respectively. Users can specify cell attributes (e.g. cluster labels, conditions) for coloring side-by-side. - **umap** and **net_umap**: UMAP like plots based on different algorithms, respectively. Users can specify cell attributes (e.g. cluster labels, conditions) for coloring side-by-side. + - **tsne**: FIt-SNE plots. Users can specify cell attributes (e.g. cluster labels, conditions) for coloring side-by-side. - **fle** and **net_fle**: FLE (Force-directed Layout Embedding) like plots based on different algorithms, respectively. Users can specify cell attributes (e.g. cluster labels, conditions) for coloring side-by-side. - - **diffmap** plots which are 3D interactive plots showing the diffusion maps. The 3 coordinates are the first 3 PCs of all diffusion components. - - If input is CITE-Seq data, there will be **citeseq_fitsne** plots which are FIt-SNE plots based on epitope expression. + - If input is CITE-Seq data, there will be **citeseq_umap** plots which are UMAP plots based on epitope expression. #. **cirro_output**. This step is optional. Generate `Cirrocumulus`_ inputs for visualization using `Cirrocumulus`_ . @@ -160,10 +159,10 @@ global inputs - This is the name of subdirectory for the current sample; and all output files within the subdirectory will have this string as the common filename prefix. - "my_sample" - - * - cumulus_version - - cumulus version to use. Versions available: 1.1.0, 1.0.0, 0.16.0, 0.15.0, 0.13.0, 0.12.0, 0.11.0, 0.10.0. - - "1.1.0" - - "1.1.0" + * - pegasus_version + - Pegasus version to use for analysis. Versions available: ``1.3.0``. + - "1.3.0" + - "1.3.0" * - docker_registry - Docker registry to use. Options: @@ -599,6 +598,7 @@ cluster outputs | To load this file in Python, you need to first install `PegasusIO`_ on your local machine. Then use ``import pegasusio as io; data = io.read_input('output_name.zarr.zip')`` in Python environment. | ``data`` is a *MultimodalData* object, and points to its default *UnimodalData* element. You can set its default *UnimodalData* to others by ``data.set_data(focus_key)`` where ``focus_key`` is the key string to the wanted *UnimodalData* element. | For its default *UnimodalData* element, the log-normalized expression matrix is stored in ``data.X`` as a Scipy CSR-format sparse matrix, with cell-by-gene shape. + | Alternatively, to get the raw count matrix, first run ``data.select_matrix('raw.X')``, then ``data.X`` will be switched to point to the raw matrix. | The ``obs`` field contains cell related attributes, including clustering results. | For example, ``data.obs_names`` records cell barcodes; ``data.obs['Channel']`` records the channel each cell comes from; | ``data.obs['n_genes']``, ``data.obs['n_counts']``, and ``data.obs['percent_mito']`` record the number of expressed genes, total UMI count, and mitochondrial rate for each cell respectively; @@ -608,8 +608,7 @@ cluster outputs | The ``obsm`` field records embedding coordinates. | For example, ``data.obsm['X_pca']`` records PCA coordinates, ``data.obsm['X_tsne']`` records t-SNE coordinates, | ``data.obsm['X_umap']`` records UMAP coordinates, ``data.obsm['X_diffmap']`` records diffusion map coordinates, - | ``data.obsm['X_diffmap_pca']`` records the first 3 PCs by projecting the diffusion components using PCA, - | and ``data.obsm['X_fle']`` records the force-directed layout coordinates from the diffusion components. + | and ``data.obsm['X_fle']`` records the force-directed layout coordinates. | The ``uns`` field stores other related information, such as reference genome (``data.uns['genome']``), kNN on PCA coordinates (``data.uns['pca_knn_indices']`` and ``data.uns['pca_knn_distances']``), etc. * - **output_log** - File @@ -619,8 +618,7 @@ cluster outputs - | List of output file(s) in Seurat-compatible h5ad format (output_name.focus_key.h5ad), in which each file is associated with a focus of the input data. | To load this file in Python, first install `PegasusIO`_ on your local machine. Then use ``import pegasusio as io; data = io.read_input('output_name.focus_key.h5ad')`` in Python environment. | After loading, ``data`` has the similar structure as *UnimodalData* object in Description of **output_zarr** in `cluster outputs <./cumulus.html#cluster-outputs>`_ section. - | In addition, ``data.raw.X`` records filtered raw count matrix as a Scipy CSR-format sparse matrix, with cell-by-gene shape. - | ``data.uns['scale.data']`` records variable-gene-selected and standardized expression matrix which are ready to perform PCA, and ``data.uns['scale.data.rownames']`` records indexes of the selected highly variable genes. + | In addition, ``data.uns['scale.data']`` records variable-gene-selected and standardized expression matrix which are ready to perform PCA, and ``data.uns['scale.data.rownames']`` records indexes of the selected highly variable genes. | This file is used for loading in R and converting into a Seurat object (see `here <./cumulus.html#load-h5ad-file-into-seurat>`_ for instructions) * - output_filt_xlsx - File @@ -660,8 +658,7 @@ cluster outputs | ``ds.ca['louvain_labels']``, ``ds.ca['leiden_labels']``, ``ds.ca['spectral_louvain_labels']``, and ``ds.ca['spectral_leiden_labels']`` record each cell's cluster labels using different clustering algorithms; | ``ds.ca['X_pca']`` records PCA coordinates, ``ds.ca['X_tsne']`` records t-SNE coordinates, | ``ds.ca['X_umap']`` records UMAP coordinates, ``ds.ca['X_diffmap']`` records diffusion map coordinates, - | ``ds.ca['X_diffmap_pca']`` records the first 3 PCs by projecting the diffusion components using PCA, - | and ``ds.ca['X_fle']`` records the force-directed layout coordinates from the diffusion components. + | and ``ds.ca['X_fle']`` records the force-directed layout coordinates. | The ``ra`` field contains gene related attributes as column attributes. | For example, ``ds.ra['var_names']`` records gene symbols, ``ds.ra['gene_ids']`` records Ensembl gene IDs, and ``ds.ra['highly_variable_features']`` records selected variable genes. @@ -748,8 +745,8 @@ de_analysis outputs - | List of h5ad-formatted results with DE results updated (output_name.focus_key.h5ad), in which each file is associated with a focus of the input data. | To load this file in Python, you need to first install `PegasusIO`_ on your local machine. Then type ``import pegasusio as io; data = io.read_input('output_name.focus_key.h5ad')`` in Python environment. | After loading, ``data`` has the similar structure as *UnimodalData* object in Description of **output_zarr** in `cluster outputs <./cumulus.html#cluster-outputs>`_ section. - | Besides, there is one additional field ``varm`` which records DE analysis results in ``data.varm['de_res']``. You can use Pandas DataFrame to convert it into a reader-friendly structure: ``import pandas as pd; df = pd.DataFrame(data.varm['de_res'], index = data.var_names)``. Then in the resulting data frame, genes are rows, and those DE test statistics are columns. - | DE analysis in cumulus is performed on each cluster against cells in all the other clusters. For instance, in the data frame, column ``mean_logExpr:1`` refers to the mean expression of genes in log-scale for cells in Cluster 1. The number after colon refers to the cluster label to which this statistic belongs. + | Besides, there is one additional field ``varm`` which records DE analysis results in ``data.varm['de_res']``. You can use Pandas DataFrame to convert it into a reader-friendly structure: ``import pandas as pd; df = pd.DataFrame(data.varm['de_res'], index=data.var_names)``. Then in the resulting data frame, genes are rows, and those DE test statistics are columns. + | DE analysis in cumulus is performed on each cluster against cells in all the other clusters. For instance, in the data frame, column ``1:log2Mean`` refers to the mean expression of genes in log-scale for cells in Cluster 1. The number before colon refers to the cluster label to which this statistic belongs. * - output_de_xlsx - Array[File] - | List of spreadsheets reporting DE results (output_name.focus_key.de.xlsx), in which each file is associated with a focus of the input data. diff --git a/docs/release_notes.rst b/docs/release_notes.rst index 51de5a4b..95a04f12 100644 --- a/docs/release_notes.rst +++ b/docs/release_notes.rst @@ -1,3 +1,10 @@ +Version 1.3.0 `February 2, 2021` +-------------------------------- + +* On *cumulus* workflow: + * Change ``cumulus_version`` to ``pegasus_version`` to avoid confusion. + * Update to use Pegasus v1.3.0 for analysis. + Version 1.2.0 `January 19, 2021` -------------------------------- diff --git a/docs/versions.rst b/docs/versions.rst index c0edb313..38aec49c 100644 --- a/docs/versions.rst +++ b/docs/versions.rst @@ -4,6 +4,54 @@ Latest and stable versions on Terra_ Cumulus is a fast growing project. As a result, we frequently update WDL snapshot versions on Terra_. See below for latest and stable WDL versions you can use. +Stable version - v1.3.0 +^^^^^^^^^^^^^^^^^^^^^^^^^^ + +.. list-table:: + :widths: 15 5 30 + :header-rows: 1 + + * - WDL + - Snapshot + - Function + * - cumulus/cellranger_workflow + - `15 `__ + - Run Cell Ranger tools, which include extracting sequence reads using cellranger mkfastq or cellranger-atac mkfastq, generating count matrix using cellranger count or cellranger-atac count, running cellranger vdj or feature-barcode extraction. + * - cumulus/spaceranger_workflow + - `1 `_ + - Run Space Ranger tools to process spatial transcriptomics data, which includes extracting sequence reads using spaceranger mkfastq, and generating count matrix using spaceranger count. + * - cumulus/star_solo + - `3 `_ + - Run STARsolo to generate gene-count matrices fro FASTQ files. + * - cumulus/count + - `18 `__ + - Run alternative tools (STARsolo, Optimus, Salmon alevin, or Kallisto BUStools) to generate gene-count matrices from FASTQ files. + * - cumulus/demultiplexing + - `22 `_ + - Run tools (demuxEM, souporcell, or demuxlet) for cell-hashing/nucleus-hashing/genetic-pooling analysis. + * - cumulus/cellranger_create_reference + - `9 `__ + - Run Cell Ranger tools to build sc/snRNA-seq references. + * - cumulus/cellranger_atac_aggr + - `2 `__ + - Run Cell Ranger tools to aggregate scATAC-seq samples. + * - cumulus/cellranger_atac_create_reference + - `2 `__ + - Run Cell Ranger tools to build scATAC-seq references. + * - cumulus/cellranger_vdj_create_reference + - `3 `__ + - Run Cell Ranger tools to build single-cell immune profiling references. + * - cumulus/smartseq2 + - `7 `__ + - Run HISAT2/STAR/Bowtie2-RSEM to generate gene-count matrices for SMART-Seq2 data from FASTQ files. + * - cumulus/smartseq2_create_reference + - `8 `__ + - Generate user-customized genome references for SMART-Seq2 data. + * - cumulus/cumulus + - `36 `__ + - Run cumulus analysis module for variable gene selection, batch correction, PCA, diffusion map, clustering, visualization, differential expression analysis, cell type annotation, etc. + + Stable version - v1.2.0 ^^^^^^^^^^^^^^^^^^^^^^^^^^ diff --git a/workflows/cumulus/cumulus.wdl b/workflows/cumulus/cumulus.wdl index 8e9c3611..fbcb6150 100644 --- a/workflows/cumulus/cumulus.wdl +++ b/workflows/cumulus/cumulus.wdl @@ -1,6 +1,6 @@ version 1.0 -import "https://api.firecloud.org/ga4gh/v1/tools/cumulus:cumulus_tasks/versions/26/plain-WDL/descriptor" as tasks +import "https://api.firecloud.org/ga4gh/v1/tools/cumulus:cumulus_tasks/versions/27/plain-WDL/descriptor" as tasks # import "cumulus_tasks.wdl" as tasks workflow cumulus { @@ -12,8 +12,8 @@ workflow cumulus { # Results name prefix and subdirectory name. String output_name - # cumulus version, default to "1.1.0" - String cumulus_version = "1.1.0" + # Pegasus version, default to "1.3.0" + String pegasus_version = "1.3.0" # Docker registry to use String docker_registry = "quay.io/cumulus" # Google cloud zones, default to "us-central1-a us-central1-b us-central1-c us-central1-f us-east1-b us-east1-c us-east1-d us-west1-a us-west1-b us-west1-c" @@ -265,7 +265,7 @@ workflow cumulus { default_reference = default_reference, select_only_singlets = select_only_singlets, minimum_number_of_genes = minimum_number_of_genes, - cumulus_version = cumulus_version, + pegasus_version = pegasus_version, zones = zones, memory = memory, disk_space = disk_space, @@ -355,7 +355,7 @@ workflow cumulus { citeseq = citeseq, citeseq_umap = citeseq_umap, citeseq_umap_exclude = citeseq_umap_exclude, - cumulus_version = cumulus_version, + pegasus_version = pegasus_version, zones = zones, num_cpu = num_cpu, memory = memory, @@ -386,7 +386,7 @@ workflow cumulus { annotate_de_test = annotate_de_test, organism = organism, minimum_report_score = minimum_report_score, - cumulus_version = cumulus_version, + pegasus_version = pegasus_version, zones = zones, num_cpu = num_cpu, memory = memory, @@ -411,7 +411,7 @@ workflow cumulus { plot_net_umap = plot_net_umap, plot_net_fle = plot_net_fle, plot_citeseq_umap = plot_citeseq_umap, - cumulus_version = cumulus_version, + pegasus_version = pegasus_version, zones = zones, memory = memory, disk_space = disk_space, @@ -426,7 +426,7 @@ workflow cumulus { input_h5ad = focus_h5ad, output_directory = output_directory_stripped + '/' + output_name, output_name = focus_prefix, - cumulus_version = cumulus_version, + pegasus_version = pegasus_version, zones = zones, memory = memory, disk_space = disk_space, @@ -443,7 +443,7 @@ workflow cumulus { output_directory = output_directory_stripped + '/' + output_name, output_name = focus_prefix, output_dense = output_dense, - cumulus_version = cumulus_version, + pegasus_version = pegasus_version, zones = zones, memory = memory, disk_space = disk_space, diff --git a/workflows/cumulus/cumulus_tasks.wdl b/workflows/cumulus/cumulus_tasks.wdl index 26f63cd2..439c6e1a 100644 --- a/workflows/cumulus/cumulus_tasks.wdl +++ b/workflows/cumulus/cumulus_tasks.wdl @@ -8,7 +8,7 @@ task run_cumulus_aggregate_matrices { File input_count_matrix_csv String output_directory String output_name - String cumulus_version + String pegasus_version String zones String memory Int disk_space @@ -61,7 +61,7 @@ task run_cumulus_aggregate_matrices { } runtime { - docker: "~{docker_registry}/cumulus:~{cumulus_version}" + docker: "~{docker_registry}/cumulus:~{pegasus_version}" zones: zones memory: memory bootDiskSizeGb: 12 @@ -76,7 +76,7 @@ task run_cumulus_cluster { File input_file String output_directory String output_name - String cumulus_version + String pegasus_version String zones Int num_cpu String memory @@ -367,7 +367,7 @@ task run_cumulus_cluster { } runtime { - docker: "~{docker_registry}/cumulus:~{cumulus_version}" + docker: "~{docker_registry}/cumulus:~{pegasus_version}" zones: zones memory: memory bootDiskSizeGb: 12 @@ -383,7 +383,7 @@ task run_cumulus_cirro_output { String output_directory String output_name String docker_registry - String cumulus_version + String pegasus_version String zones String memory Int disk_space @@ -408,7 +408,7 @@ task run_cumulus_cirro_output { } runtime { - docker: "~{docker_registry}/cumulus:~{cumulus_version}" + docker: "~{docker_registry}/cumulus:~{pegasus_version}" zones: zones memory: memory disks: "local-disk ~{disk_space} HDD" @@ -422,7 +422,7 @@ task run_cumulus_de_analysis { File input_h5ad String output_directory String output_name - String cumulus_version + String pegasus_version String zones Int num_cpu String memory @@ -529,7 +529,7 @@ task run_cumulus_de_analysis { } runtime { - docker: "~{docker_registry}/cumulus:~{cumulus_version}" + docker: "~{docker_registry}/cumulus:~{pegasus_version}" zones: zones memory: memory bootDiskSizeGb: 12 @@ -544,7 +544,7 @@ task run_cumulus_plot { File input_h5ad String output_directory String output_name - String cumulus_version + String pegasus_version String zones String memory Int disk_space @@ -619,7 +619,7 @@ task run_cumulus_plot { } runtime { - docker: "~{docker_registry}/cumulus:~{cumulus_version}" + docker: "~{docker_registry}/cumulus:~{pegasus_version}" zones: zones memory: memory bootDiskSizeGb: 12 @@ -635,7 +635,7 @@ task run_cumulus_scp_output { String output_directory String output_name Boolean output_dense - String cumulus_version + String pegasus_version String zones String memory Int disk_space @@ -656,7 +656,7 @@ task run_cumulus_scp_output { } runtime { - docker: "~{docker_registry}/cumulus:~{cumulus_version}" + docker: "~{docker_registry}/cumulus:~{pegasus_version}" zones: zones memory: memory bootDiskSizeGb: 12