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2 changes: 1 addition & 1 deletion docs/html/_sources/index.rst.txt
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Expand Up @@ -3,7 +3,7 @@ SPARCSpy - image-based single cell analysis at scale in python

SPARCSpy is a scalable toolkit to analyse single-cell image datasets. This Python implementation efficiently segments individual cells, generates single-cell datasets and provides tools for the efficient deep learning classification of their phenotypes for downstream applications.

.. image:: pages/images/graphical_abstract_without_title.pdf
.. image:: pages/images/graphical_abstract_without_title.png
:width: 100%
:align: center
:alt: graphical abstract
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4 changes: 2 additions & 2 deletions docs/html/_sources/pages/pipeline/extraction.rst.txt
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Expand Up @@ -5,7 +5,7 @@ Extraction

The SPARCSpy framework is built around the idea of generating standardized single-cell image datasets. A SPARCSpy single cell image dataset consists of a collection of images for each cell containing both the segmentation masks and imaging channels of that particular cell.

.. image:: ../images/extraction_process.pdf
.. image:: ../images/extraction_process.png
:width: 100%
:align: center

Expand All @@ -26,6 +26,6 @@ For each cell, the extracted single-cell image dataset consists of a collection

Besides containing the images themselves, the single-cell image datasets also contain annotation information for each cell within the dataset. In the minimal form this consists of a ``cellID``, which is a unique numerical identifier assigned to each cell during segmentation. By directly linking single-cell images to the ``cellID`` of the extracted cell this allows you to trace individual extracted cells back to their original position in the input image to e.g. select them for subsequent laser microdissection or look at their localization. Depending on the extraction method used, the single-cell image dataset can also contain additional labelling information.

.. image:: ../images/HDF5_data_containers.pdf
.. image:: ../images/HDF5_data_containers.png
:width: 100%
:align: center
2 changes: 1 addition & 1 deletion docs/html/_sources/pages/pipeline/project.rst.txt
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Expand Up @@ -5,7 +5,7 @@ SPARCSpy Projects

Within SPARCSpy, all operations are centered around the concept of a ``Project``. A ``Project`` is a python class which manages all of the SPARCSpy processing steps and is the central element through which all operations are performed. Each ``Project`` directly maps to a directory on the file system which contains all of the inputs to a specific SPARCSpy run as well as the generated outputs. This directory also contains copies of the configuration file which specifies the parameters used for all methods associated with that run. This allows for easy reproducibility of results.

.. image:: ../images/project_structure.pdf
.. image:: ../images/project_structure.png
:width: 100%
:align: center
:alt: SPARCSpy project structure
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6 changes: 3 additions & 3 deletions docs/html/_sources/pages/pipeline/segmentation.rst.txt
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Expand Up @@ -142,7 +142,7 @@ This segmentation workflow is implemented to only run on the CPU. As such it can
Nucleus Segmentation Algorithm
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. image:: ../images/WGA_segmentation_nucleus.pdf
.. image:: ../images/WGA_segmentation_nucleus.png
:width: 100%
:align: left
:alt: Nuclear segmentation algorithm steps
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Cytosol Segmentation Algorithm
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. image:: ../images/WGA_segmentation_cytosol.pdf
.. image:: ../images/WGA_segmentation_cytosol.png
:width: 100%
:align: left
:alt: Cytosol segmentation algorithm steps
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Nucleus Segmentation Algorithm
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. image:: ../images/WGA_segmentation_nucleus.pdf
.. image:: ../images/WGA_segmentation_nucleus.png
:width: 100%
:align: center
:alt: Nuclear segmentation algorithm steps
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<section id="sparcspy-image-based-single-cell-analysis-at-scale-in-python">
<h1>SPARCSpy - image-based single cell analysis at scale in python<a class="headerlink" href="#sparcspy-image-based-single-cell-analysis-at-scale-in-python" title="Permalink to this headline"></a></h1>
<p>SPARCSpy is a scalable toolkit to analyse single-cell image datasets. This Python implementation efficiently segments individual cells, generates single-cell datasets and provides tools for the efficient deep learning classification of their phenotypes for downstream applications.</p>
<a class="reference internal image-reference" href="_images/graphical_abstract_without_title.pdf"><img alt="graphical abstract" class="align-center" src="_images/graphical_abstract_without_title.pdf" style="width: 100%;" /></a>
<a class="reference internal image-reference" href="_images/graphical_abstract_without_title.png"><img alt="graphical abstract" class="align-center" src="_images/graphical_abstract_without_title.png" style="width: 100%;" /></a>
</section>
<section id="installation">
<h1>Installation<a class="headerlink" href="#installation" title="Permalink to this headline"></a></h1>
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</li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="pipeline/config.html">Config Files</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
</ul>
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</li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="../pipeline/project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
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</li>
<li class="toctree-l3"><a class="reference internal" href="project.html#initializing-a-sparcspy-project">Initializing a SPARCSpy Project</a></li>
<li class="toctree-l3"><a class="reference internal" href="project.html#loading-images-into-a-sparcspy-project">Loading Images into a SPARCSpy project</a></li>
<li class="toctree-l3"><a class="reference internal" href="project.html#calling-the-sparcspy-workflow">Calling the SPARCSpy workflow</a></li>
<li class="toctree-l3"><a class="reference internal" href="project.html#rerunning-specific-steps">Rerunning specific steps</a></li>
</ul>
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<section id="extraction">
<span id="id1"></span><h1>Extraction<a class="headerlink" href="#extraction" title="Permalink to this headline"></a></h1>
<p>The SPARCSpy framework is built around the idea of generating standardized single-cell image datasets. A SPARCSpy single cell image dataset consists of a collection of images for each cell containing both the segmentation masks and imaging channels of that particular cell.</p>
<a class="reference internal image-reference" href="../../_images/extraction_process.pdf"><img alt="../../_images/extraction_process.pdf" class="align-center" src="../../_images/extraction_process.pdf" style="width: 100%;" /></a>
<a class="reference internal image-reference" href="../../_images/extraction_process.png"><img alt="../../_images/extraction_process.png" class="align-center" src="../../_images/extraction_process.png" style="width: 100%;" /></a>
<p>These datasets are generated by cropping out image regions corresponding to individual cells from the original image during a process called extraction. During this process, the segmentation masks generated during the segmentation step are taken and applied to the original image. All pixels within the mask dimensions are preserved, while the pixels outside of the mask are set to <code class="docutils literal notranslate"><span class="pre">0</span></code>. By using the segmentation masks to extract only those pixels that are annotated to belong to a given cell, SPARCSpy achieves exact clipping of individual cells from their background, eliminating noise from neighbouring cells. During this process, all single cell images are centered on their respective nuclei and the resulting single-cell images normalized to the the [0, 1] range. Extraction is only performed on cells that were fully imaged, i.e. their masks do not intersect with the image borders.</p>
<section id="extraction-classes">
<h2>Extraction classes<a class="headerlink" href="#extraction-classes" title="Permalink to this headline"></a></h2>
Expand All @@ -275,7 +273,7 @@ <h2>Single-cell image datasets<a class="headerlink" href="#single-cell-image-dat
<p>For each cell, the extracted single-cell image dataset consists of a collection of images containing the segmentation masks and imaging channels of that particular cell. The segmentation masks are saved as binary masks, while the imaging channels are saved as float images normalized to the range <code class="docutils literal notranslate"><span class="pre">[0,</span> <span class="pre">1]</span></code>. During extraction the nuclear channel is masked using the nucleus mask, while all other imaging channels are masked using the cytosol mask. During this procedure the input mask is expanded slighly and a gaussian blur is applied to ensure that the entire cell is captured. Aggregated across all cells in a SPARCSpy dataset, the image collections for each cell are saved to <code class="docutils literal notranslate"><span class="pre">HDF5</span></code>, a container file format that enables the retrieval of individual cells without loading the entire dataset. These <code class="docutils literal notranslate"><span class="pre">HDF5</span></code> datasets are the result of the extraction step and we refer to them as single-cell image datasets.</p>
<a class="reference internal image-reference" href="../../_images/single_cell_dataset.png"><img alt="../../_images/single_cell_dataset.png" src="../../_images/single_cell_dataset.png" style="width: 100%;" /></a>
<p>Besides containing the images themselves, the single-cell image datasets also contain annotation information for each cell within the dataset. In the minimal form this consists of a <code class="docutils literal notranslate"><span class="pre">cellID</span></code>, which is a unique numerical identifier assigned to each cell during segmentation. By directly linking single-cell images to the <code class="docutils literal notranslate"><span class="pre">cellID</span></code> of the extracted cell this allows you to trace individual extracted cells back to their original position in the input image to e.g. select them for subsequent laser microdissection or look at their localization. Depending on the extraction method used, the single-cell image dataset can also contain additional labelling information.</p>
<a class="reference internal image-reference" href="../../_images/HDF5_data_containers.pdf"><img alt="../../_images/HDF5_data_containers.pdf" class="align-center" src="../../_images/HDF5_data_containers.pdf" style="width: 100%;" /></a>
<a class="reference internal image-reference" href="../../_images/HDF5_data_containers.png"><img alt="../../_images/HDF5_data_containers.png" class="align-center" src="../../_images/HDF5_data_containers.png" style="width: 100%;" /></a>
</section>
</section>

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<section id="sparcspy-projects">
<span id="projects"></span><h1>SPARCSpy Projects<a class="headerlink" href="#sparcspy-projects" title="Permalink to this headline"></a></h1>
<p>Within SPARCSpy, all operations are centered around the concept of a <code class="docutils literal notranslate"><span class="pre">Project</span></code>. A <code class="docutils literal notranslate"><span class="pre">Project</span></code> is a python class which manages all of the SPARCSpy processing steps and is the central element through which all operations are performed. Each <code class="docutils literal notranslate"><span class="pre">Project</span></code> directly maps to a directory on the file system which contains all of the inputs to a specific SPARCSpy run as well as the generated outputs. This directory also contains copies of the configuration file which specifies the parameters used for all methods associated with that run. This allows for easy reproducibility of results.</p>
<a class="reference internal image-reference" href="../../_images/project_structure.pdf"><img alt="SPARCSpy project structure" class="align-center" src="../../_images/project_structure.pdf" style="width: 100%;" /></a>
<a class="reference internal image-reference" href="../../_images/project_structure.png"><img alt="SPARCSpy project structure" class="align-center" src="../../_images/project_structure.png" style="width: 100%;" /></a>
<section id="project-classes">
<h2>Project classes<a class="headerlink" href="#project-classes" title="Permalink to this headline"></a></h2>
<p>SPARCSpy provides several different <code class="docutils literal notranslate"><span class="pre">Project</span></code> classes which are designed to handle different input data types. Each <code class="docutils literal notranslate"><span class="pre">Project</span></code> class comes with its own set of segmentation and extraction methods which are tailored to the specific type of data. Please refer to the <a class="reference internal" href="segmentation.html#segmentation"><span class="std std-ref">segmentation</span></a> and <a class="reference internal" href="extraction.html#extraction"><span class="std std-ref">extraction</span></a> sections for more details. Below you can find a brief outline of the different <code class="docutils literal notranslate"><span class="pre">Project</span></code> classes, what type of data structures they are suited for and their associated methods classes.</p>
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