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Comment out tools for Single-cell GalaxyLab #245

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226 changes: 113 additions & 113 deletions communities/spoc/lab/sections/1_beginner.yml
Original file line number Diff line number Diff line change
Expand Up @@ -41,13 +41,13 @@ tabs:
heading_md: >
Using public data is free! Learn how to retrieve data from common sources.
content:
- title_md: Importing files from the Single Cell Expression Atlas
description_md: >
You can import data directly from the Single Cell Expression Atlas with one tool. You will need an **experiment accession** ID, which you can find by browsing experiments at the [EBI Atlas site](https://www.ebi.ac.uk/gxa/sc/experiments). Input that **experiment accession** ID in the *Tool Parameters* box when of the following tool. Then **Run tool** to get your matrix!
<code>EBI SCXA Data Retrieval</code>
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fretrieve_scxa%2fretrieve_scxa"
button_icon: run
button_tip: Run tool
# - title_md: Importing files from the Single Cell Expression Atlas
# description_md: >
# You can import data directly from the Single Cell Expression Atlas with one tool. You will need an **experiment accession** ID, which you can find by browsing experiments at the [EBI Atlas site](https://www.ebi.ac.uk/gxa/sc/experiments). Input that **experiment accession** ID in the *Tool Parameters* box when of the following tool. Then **Run tool** to get your matrix!
# <code>EBI SCXA Data Retrieval</code>
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fretrieve_scxa%2fretrieve_scxa"
# button_icon: run
# button_tip: Run tool
- title_md: Importing from public atlases - Tutorial
description_md: >
You can learn more by following our dedicated to tutorial for importing files from public atlases.
Expand All @@ -60,128 +60,128 @@ tabs:
button_link: https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-ncbi-anndata/tutorial.html
button_icon: tutorial
button_tip: View tutorial
- title_md: Importing 10X Files
description_md: >
You can find many tools for importing 10X formatted data into target datatypes.
<code>Scanpy Read10x</code>
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fscanpy_read_10x%2fscanpy_read_10x"
button_icon: run
button_tip: Run tool
- title_md: <code>Seurat Read10x</code>
description_md: >
Import 10X formatted data into a Seurat object. Seurat is an R package designed for QC, analysis, and exploration of single cell RNA-seq data.
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fseurat_read10x%2fseurat_read10x"
button_icon: run
button_tip: Run tool
- title_md: <code>DropletUtils Read10x</code>
description_md: >
DropletUtils provides a number of utility functions for handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics. This includes data loading, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fdropletutils_read_10x%2fdropletutils_read_10x"
button_icon: run
button_tip: Run tool
#- title_md: Importing 10X Files
# description_md: >
# You can find many tools for importing 10X formatted data into target datatypes.
# <code>Scanpy Read10x</code>
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fscanpy_read_10x%2fscanpy_read_10x"
# button_icon: run
# button_tip: Run tool
#- title_md: <code>Seurat Read10x</code>
# description_md: >
# Import 10X formatted data into a Seurat object. Seurat is an R package designed for QC, analysis, and exploration of single cell RNA-seq data.
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fseurat_read10x%2fseurat_read10x"
# button_icon: run
# button_tip: Run tool
#- title_md: <code>DropletUtils Read10x</code>
# description_md: >
# DropletUtils provides a number of utility functions for handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics. This includes data loading, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fdropletutils_read_10x%2fdropletutils_read_10x"
# button_icon: run
# button_tip: Run tool

- id: data_convert
title: Converting datatypes
heading_md: >
Single-cell data comes in many formats.
Here we show a few key tools in Galaxy for converting and manipulating objects in Galaxy.
content:
- title_md: <code>SCEasy Converter</code>
description_md: >
This tool allows you to convert between the following formats:

- `hdf5` (AnnData/Loom)
- `rds` (Seurat)
- `rdata.sce` (Single Cell Experiment)
- `h5` (Seurat)
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fiuc/sceasy_convert%2fsceasy_convert"
button_icon: run
button_tip: Run tool
#- title_md: <code>SCEasy Converter</code>
# description_md: >
# This tool allows you to convert between the following formats:
#
# - `hdf5` (AnnData/Loom)
# - `rds` (Seurat)
# - `rdata.sce` (Single Cell Experiment)
# - `h5` (Seurat)
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fiuc/sceasy_convert%2fsceasy_convert"
# button_icon: run
# button_tip: Run tool
- title_md: <code>Manipulate AnnData</code>
description_md: >
Under the parameter `Function to manipulate the object` you'll find key manipulations for AnnData, such as:

- `Concatenate along the observations axis` for combining AnnData objects together
- `Transpose the data matrix` for help with converting formats
- `Filter observations or variables` for refining or subsetting your dataset
- `Adding annotations` and `Rename categories` for manipulating metadata
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fiuc/anndata_manipulate%2fanndata_manipulate"
button_icon: run
button_tip: Run tool
- title_md: <code>AnnData Operations</code>
description_md: >
This tool allows you to flag genes (such as mitochondrial genes) as well as change names in the metadata.
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fanndata_ops%2fanndata_ops"
button_icon: run
button_tip: Run tool
# Under the parameter `Function to manipulate the object` you'll find key manipulations for AnnData, such as:
#
# - `Concatenate along the observations axis` for combining AnnData objects together
# - `Transpose the data matrix` for help with converting formats
# - `Filter observations or variables` for refining or subsetting your dataset
# - `Adding annotations` and `Rename categories` for manipulating metadata
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fiuc/anndata_manipulate%2fanndata_manipulate"
# button_icon: run
# button_tip: Run tool
# - title_md: <code>AnnData Operations</code>
# description_md: >
# This tool allows you to flag genes (such as mitochondrial genes) as well as change names in the metadata.
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fanndata_ops%2fanndata_ops"
# button_icon: run
# button_tip: Run tool
- title_md: Data conversion training
description_md: >
You can also explore our dedicated tutorial on single-cell data conversion.
button_link: "https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-data-ingest/tutorial.html"
button_icon: tutorial
button_tip: View tutorial

- id: data_viz
title: Visualising Data
heading_md: >
There are a few key tools for visualising single-cell data in Galaxy.
content:
- title_md: <code>Plot with Scanpy</code>
description_md: >
This tool allows you to generate many plots, from scatterplots, to violin plots, to gene heatplots.
inputs:
- label: Single cell data
datatypes:
- hdf5 (AnnData)
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fiuc/scanpy_plot%2fscanpy_plot"
button_icon: run
button_tip: Run tool
- title_md: <code>Scanpy PlotEmbed</code>
description_md: >
This tool allows you to plot embeddings like UMAPs.
inputs:
- label: Single cell data
datatypes:
- hdf5 (AnnData)
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fscanpy_plot_embed%2fscanpy_plot_embed"
button_icon: run
button_tip: Run tool
- title_md: <code>Scanpy PlotTrajectory</code>
description_md: >
This tool allows you to plot trajectory data, such as PAGA, pre-calculated in an AnnData object.
inputs:
- label: Single cell data
datatypes:
- hdf5 (AnnData)
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxi%2fscanpy_plot_trajectory/scanpy_plot_trajectory"
button_icon: run
button_tip: Run tool
- title_md: <code>Scanpy Plot dimension reduction</code>
description_md: >
This tool allows you to plot embeddings such as PCA, UMAP, and tSNE.
inputs:
- label: Single cell data
datatypes:
- rds (Seurat object)
- rdata.sce (Single Cell Experiment)
- h5 (Seurat)
- hdf5 (Loom/AnnData)
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fseurat_dim_plot%2fseurat_dim_plot"
button_icon: run
button_tip: Run tool
- title_md: <code>Plot with Seurat</code>
description_md: >
This tool allows you to plot gene expressions, such as with Violin Plots.
inputs:
- label: Single cell data
datatypes:
- rds (Seurat object)
- rdata.sce (Single Cell Experiment)
- h5 (Seurat)
- hdf5 (Loom/AnnData)
button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fseurat_plot%2fseurat_plot"
button_icon: run
button_tip: Run tool
# - id: data_viz
# title: Visualising Data
# heading_md: >
# There are a few key tools for visualising single-cell data in Galaxy.
# content:
# - title_md: <code>Plot with Scanpy</code>
# description_md: >
# This tool allows you to generate many plots, from scatterplots, to violin plots, to gene heatplots.
# inputs:
# - label: Single cell data
# datatypes:
# - hdf5 (AnnData)
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fiuc/scanpy_plot%2fscanpy_plot"
# button_icon: run
# button_tip: Run tool
# - title_md: <code>Scanpy PlotEmbed</code>
# description_md: >
# This tool allows you to plot embeddings like UMAPs.
# inputs:
# - label: Single cell data
# datatypes:
# - hdf5 (AnnData)
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fscanpy_plot_embed%2fscanpy_plot_embed"
# button_icon: run
# button_tip: Run tool
# - title_md: <code>Scanpy PlotTrajectory</code>
# description_md: >
# This tool allows you to plot trajectory data, such as PAGA, pre-calculated in an AnnData object.
# inputs:
# - label: Single cell data
# datatypes:
# - hdf5 (AnnData)
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxi%2fscanpy_plot_trajectory/scanpy_plot_trajectory"
# button_icon: run
# button_tip: Run tool
# - title_md: <code>Scanpy Plot dimension reduction</code>
# description_md: >
# This tool allows you to plot embeddings such as PCA, UMAP, and tSNE.
# inputs:
# - label: Single cell data
# datatypes:
# - rds (Seurat object)
# - rdata.sce (Single Cell Experiment)
# - h5 (Seurat)
# - hdf5 (Loom/AnnData)
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fseurat_dim_plot%2fseurat_dim_plot"
# button_icon: run
# button_tip: Run tool
# - title_md: <code>Plot with Seurat</code>
# description_md: >
# This tool allows you to plot gene expressions, such as with Violin Plots.
# inputs:
# - label: Single cell data
# datatypes:
# - rds (Seurat object)
# - rdata.sce (Single Cell Experiment)
# - h5 (Seurat)
# - hdf5 (Loom/AnnData)
# button_link: "{{ galaxy_base_url }}/tool_runner?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Febi-gxa%2fseurat_plot%2fseurat_plot"
# button_icon: run
# button_tip: Run tool

- id: help
title: Help
Expand Down