From fa5c192c652ede170a124023ea0ae0178d047c3e Mon Sep 17 00:00:00 2001 From: Chris Flerin Date: Fri, 11 Dec 2020 12:03:04 +0100 Subject: [PATCH] Doc updates - typo fixes, edit for clarity --- README.rst | 4 +++- docs/development.rst | 4 ++-- docs/features.rst | 28 ++++++++++++++-------------- docs/getting-started.rst | 2 +- docs/pipelines.rst | 10 +++++----- 5 files changed, 25 insertions(+), 23 deletions(-) diff --git a/README.rst b/README.rst index 52ab9363..4be64d21 100644 --- a/README.rst +++ b/README.rst @@ -8,7 +8,8 @@ A repository of pipelines for single-cell data analysis in Nextflow DSL2. **Full documentation** is available on `Read the Docs `_, or take a look at the `Quick Start `_ guide. -This main repo contains multiple workflows for analyzing single cell transcriptomics data, and depends on a number of tools, which are organized into submodules within the VIB-Singlecell-NF_ organization. +This main repo contains multiple workflows for analyzing single cell transcriptomics data, and depends on a number of tools, which are organized into subfolders within the ``src/`` directory. +The VIB-Singlecell-NF_ organization contains this main repo along with a collection of example runs (`VSN-Pipelines-examples `_). Currently available workflows are listed below. If VSN-Pipelines is useful for your research, consider citing: @@ -109,6 +110,7 @@ Sample Aggregation Workflows --- + In addition, the pySCENIC_ implementation of the SCENIC_ workflow is integrated here and can be run in conjunction with any of the above workflows. The output of each of the main workflows is a loom_-format file, which is ready for import into the interactive single-cell web visualization tool SCope_. In addition, data is also output in h5ad format, and reports are generated for the major pipeline steps. diff --git a/docs/development.rst b/docs/development.rst index 2cda7cbb..67d0e939 100644 --- a/docs/development.rst +++ b/docs/development.rst @@ -83,7 +83,7 @@ Steps: #. Update the ``nextflow.config`` file to create the ``harmony.config`` configuration file. - * Each process's options should be in their own level. With a single proccess, you do not need one extra level. + * Each process's options should be in their own level. With a single process, you do not need one extra level. .. code:: dockerfile @@ -624,7 +624,7 @@ Steps: } -#. Finally add a new entry in main.nf of the ``vsn-pipelines`` repository +#. Finally add a new entry in ``main.nf`` of the ``vsn-pipelines`` repository .. code:: groovy diff --git a/docs/features.rst b/docs/features.rst index 37a900bd..e6fa68cc 100644 --- a/docs/features.rst +++ b/docs/features.rst @@ -55,14 +55,14 @@ Finally run the pipeline, Set the seed ------------ -Some steps in the pipelines are nondeterministic. In order to have reproducible results, a seed is set by default to: +Some steps in the pipelines are non-deterministic. In order to have reproducible results, a seed is set by default to: .. code:: groovy workflow.manifest.version.replaceAll("\\.","").toInteger() -The seed is a number derived from the the version of the pipeline used at the time of the analysis run. -To override the seed (integer) you have edit the nextflow.config file with: +The seed is a number derived from the version of the pipeline used at the time of the analysis run. +To override the seed (integer) you have edit the ``nextflow.config`` file with: .. code:: groovy @@ -154,19 +154,19 @@ Two methods (``params.sc.cell_annotate.method``) are available: If you have a single file containing the metadata information of all your samples, use ``aio`` method otherwise use ``obo``. -For both methods, here are the mandatory params to set: +For both methods, here are the mandatory parameters to set: - ``off`` should be set to ``h5ad`` - ``method`` choose either ``obo`` or ``aio`` - ``annotationColumnNames`` is an array of columns names from ``cellMetaDataFilePath`` containing different annotation metadata to add. -If ``aio`` used, the following additional params are required: +If ``aio`` used, the following additional parameters are required: - ``cellMetaDataFilePath`` is a file path pointing to a single .tsv file (with header) with at least 2 columns: a column containing all the cell IDs and an annotation column. - ``indexColumnName`` is the column name from ``cellMetaDataFilePath`` containing the cell IDs information. This column **can** have unique values; if it's not the case, it's important that the combination of the values from the ``indexColumnName`` and the ``sampleColumnName`` are unique. -- ``sampleColumnName`` is the column name from ``cellMetaDataFilePath`` containing the sample ID/name information. Make sur that the values from this column match the samples IDs inferred from the data files. To know how those are inferred, please read the `Input Data Formats`_ section. +- ``sampleColumnName`` is the column name from ``cellMetaDataFilePath`` containing the sample ID/name information. Make sure that the values from this column match the samples IDs inferred from the data files. To know how those are inferred, please read the `Input Data Formats`_ section. -If ``obo`` is used, the following params are required: +If ``obo`` is used, the following parameters are required: - ``cellMetaDataFilePath`` @@ -267,7 +267,7 @@ Two methods (``params.sc.cell_filter.method``) are available: If you have a single file containing the metadata information of all your samples, use ``external`` method otherwise use ``internal``. -For both methods, here are the mandatory params to set: +For both methods, here are the mandatory parameters to set: - ``off`` should be set to ``h5ad`` - ``method`` choose either ``internal`` or ``external`` @@ -276,20 +276,20 @@ For both methods, here are the mandatory params to set: - ``id`` is a short identifier for the filter - ``valuesToKeepFromFilterColumn`` is array of values from the ``filterColumnName`` that should be kept (other values will be filtered out). -If ``internal`` used, the following additional params are required: +If ``internal`` used, the following additional parameters are required: - ``filters`` is a List of Maps where each Map is required to have the following parameters: - ``sampleColumnName`` is the column name containing the sample ID/name information. It should exist in the ``obs`` column attribute of the h5ad. - ``filterColumnName`` is the column name that will be used to filter out cells. It should exist in the ``obs`` column attribute of the h5ad. -If ``external`` used, the following additional params are required: +If ``external`` used, the following additional parameters are required: - ``filters`` is a List of Maps where each Map is required to have the following parameters: - ``cellMetaDataFilePath`` is a file path pointing to a single .tsv file (with header) with at least 3 columns: a column containing all the cell IDs, another containing the sample ID/name information, and a column to use for the filtering. - ``indexColumnName`` is the column name from ``cellMetaDataFilePath`` containing the cell IDs information. This column **must** have unique values. - - `optional` ``sampleColumnName`` is the column name from ``cellMetaDataFilePath`` containing the sample ID/name information. Make sur that the values from this column match the samples IDs inferred from the data files. To know how those are inferred, please read the `Input Data Formats`_ section. + - `optional` ``sampleColumnName`` is the column name from ``cellMetaDataFilePath`` containing the sample ID/name information. Make sure that the values from this column match the samples IDs inferred from the data files. To know how those are inferred, please read the `Input Data Formats`_ section. - `optional` ``filterColumnName`` is the column name from ``cellMetaDataFilePath`` which be used to filter out cells. @@ -348,8 +348,8 @@ If you want to apply custom parameters for some specific samples and have a "gen } } -Using this config, the param ``params.sc.scanpy.cellFilterMinNGenes`` will be applied with a threshold value of ``600`` to ``1k_pbmc_v2_chemistry``. The rest of the samples will use the value ``800`` to filter the cells having less than that number of genes. -This strategy can be applied to any other paramameter of the config. +Using this config, the parameter ``params.sc.scanpy.cellFilterMinNGenes`` will be applied with a threshold value of ``600`` to ``1k_pbmc_v2_chemistry``. The rest of the samples will use the value ``800`` to filter the cells having less than that number of genes. +This strategy can be applied to any other parameter of the config. Parameter exploration @@ -437,4 +437,4 @@ The following command, will create a Nextflow config which the pipeline will und -profile min,[data-profile],scanpy_data_transformation,scanpy_normalization,[...],singularity > nextflow.config - ``[data-profile]``: Can be one of the different possible data profiles e.g.: ``h5ad`` -- ``[...]``: Can be other profiles like ``bbknn``, ``harmony``, ``pcacv``, ... \ No newline at end of file +- ``[...]``: Can be other profiles like ``bbknn``, ``harmony``, ``pcacv``, ... diff --git a/docs/getting-started.rst b/docs/getting-started.rst index c91e2eae..6c8cd24b 100644 --- a/docs/getting-started.rst +++ b/docs/getting-started.rst @@ -126,6 +126,6 @@ The pipelines will generate 3 types of results in the output directory (`params. - See the example output report from the 1k PBMC data `here `_ -- ``pipeline_reports``: nextflow dag, execution, timeline, and trace reports +- ``pipeline_reports``: Nextflow dag, execution, timeline, and trace reports If you would like to use the pipelines on a custom dataset, please see the `pipelines <./pipelines.html>`_ section below. diff --git a/docs/pipelines.rst b/docs/pipelines.rst index 8e69cc6e..9178c23f 100644 --- a/docs/pipelines.rst +++ b/docs/pipelines.rst @@ -8,7 +8,7 @@ This pipeline can be configured and run on custom data with a few steps. The recommended method is to first run ``nextflow config ...`` to generate a complete config file (with the default parameters) in your working directory. The tool-specific parameters, as well as Docker/Singularity profiles, are included when specifying the appropriate profiles to ``nextflow config``. -1. First, update to the latest pipeline version (this will update the nextflow cache of the repository, typically located in ``~/.nextflow/assets/vib-singlecell-nf/``):: +1. First, update to the latest pipeline version (this will update the Nextflow cache of the repository, typically located in ``~/.nextflow/assets/vib-singlecell-nf/``):: nextflow pull vib-singlecell-nf/vsn-pipelines @@ -502,14 +502,14 @@ The output is a loom file with the results embedded. Utility Pipelines ***************** -Contrary to the aformentioned pipelines, these are not end-to-end. They are used to perfom small incremental processing steps. +Contrary to the aformentioned pipelines, these are not end-to-end. They are used to perform small incremental processing steps. **cell_annotate** ----------------- Runs the ``cell_annotate`` workflow which will perform a cell-based annotation of the data using a set of provided .tsv metadata files. We show a use case here below with 10x Genomics data were it will annotate different samples using the ``obo`` method. For more information -about this cell-based annotation feautre please visit `Cell-based metadata annotation`_ section. +about this cell-based annotation feature please visit `Cell-based metadata annotation`_ section. .. _`Cell-based metadata annotation`: https://vsn-pipelines.readthedocs.io/en/latest/features.html#cell-based-metadata-annotation @@ -561,7 +561,7 @@ Now we can run it with the following command: Runs the ``cell_annotate_filter`` workflow which will perform a cell-based annotation of the data using a set of provided .tsv metadata files following by a cell-based filtering. We show a use case here below with 10x Genomics data were it will annotate different samples using the ``obo`` method. For more information -about this cell-based annotation feautre please visit `Cell-based metadata annotation`_ section and `Cell-based metadata filtering`_ section. +about this cell-based annotation feature please visit `Cell-based metadata annotation`_ section and `Cell-based metadata filtering`_ section. .. _`Cell-based metadata filtering`: https://vsn-pipelines.readthedocs.io/en/latest/features.html#cell-based-metadata-filtering @@ -752,7 +752,7 @@ In the generated .config file, make sure the ``file_paths`` parameter is set wit - The ``suffix`` parameter is used to infer the sample name from the file paths (it is removed from the input file path to derive a sample name). -In case there are multiple .h5ad files that need to be processed with different suffixes, the multi-labelled strategy should be used to define the h5ad param:: +In case there are multiple .h5ad files that need to be processed with different suffixes, the multi-labelled strategy should be used to define the h5ad parameter:: [...] data {