<?xml version='1.0' encoding='utf-8'?>
<scheme description="Load the data from scOrange single cell database, see the expression values in a spreadsheet, and use Louvain clustering to find cell groups. Visualize cell landscape in a t-SNE projection and inspect the results of clustering. Select a subset of cells in t-SNE to examine their type or gene expression statistics in the Box Plot. Find enriched Gene Ontology terms, which hint on cell types." title="Clustering and Cluster Analysis" version="2.0">
	<nodes>
		<node id="0" name="t-SNE" position="(384.0, 135.0)" project_name="Orange3-SingleCell" qualified_name="orangecontrib.single_cell.widgets.owtsne.OWtSNE" title="t-SNE" version="" />
		<node id="1" name="Data Table" position="(254.0, 293.0)" project_name="Orange3" qualified_name="Orange.widgets.data.owtable.OWDataTable" title="Data Table" version="" />
		<node id="2" name="Box Plot" position="(498.0, 136.0)" project_name="Orange3" qualified_name="Orange.widgets.visualize.owboxplot.OWBoxPlot" title="Box Plot" version="" />
		<node id="3" name="Single Cell Datasets" position="(103.0, 236.0)" project_name="Orange3-SingleCell" qualified_name="orangecontrib.single_cell.widgets.owscdatasets.OWscDataSets" title="Single Cell Datasets" version="" />
		<node id="4" name="Louvain Clustering" position="(254.0, 181.0)" project_name="Orange3" qualified_name="Orange.widgets.unsupervised.owlouvainclustering.OWLouvainClustering" title="Louvain Clustering" version="" />
		<node id="5" name="Cluster Analysis" position="(387.0, 238.0)" project_name="Orange3-Bioinformatics" qualified_name="orangecontrib.bioinformatics.widgets.OWClusterAnalysis.OWClusterAnalysis" title="Cluster Analysis" version="" />
	</nodes>
	<links>
		<link enabled="true" id="0" sink_channel="Data" sink_node_id="2" source_channel="Selected Data" source_node_id="0" />
		<link enabled="true" id="1" sink_channel="Data" sink_node_id="1" source_channel="Data" source_node_id="3" />
		<link enabled="true" id="2" sink_channel="Data" sink_node_id="4" source_channel="Data" source_node_id="3" />
		<link enabled="true" id="3" sink_channel="Data" sink_node_id="0" source_channel="Data" source_node_id="4" />
		<link enabled="true" id="4" sink_channel="Data" sink_node_id="5" source_channel="Data" source_node_id="4" />
	</links>
	<annotations>
		<text font-family="Helvetica" font-size="14" id="0" rect="(45.0, 115.0, 150.0, 82.0)" type="text/plain">Load the data on bone marrow mononuclear cells with AML (Zheng et. al. 2017).  </text>
		<text font-family="Helvetica" font-size="20" id="1" rect="(15.0, 116.0, 150.0, 32.0)" type="text/plain">(1)</text>
		<text font-family="Helvetica" font-size="14" id="2" rect="(243.0, 351.0, 150.0, 82.0)" type="text/plain">See the data in a spreadsheet. Input gene expression data is already normalized.</text>
		<text font-family="Helvetica" font-size="20" id="3" rect="(213.0, 352.0, 150.0, 32.0)" type="text/plain">(2)</text>
		<text font-family="Helvetica" font-size="20" id="4" rect="(185.0, 50.0, 150.0, 32.0)" type="text/plain">(3)</text>
		<text font-family="Helvetica" font-size="20" id="5" rect="(360.0, -29.0, 150.0, 32.0)" type="text/plain">(4)</text>
		<text font-family="Helvetica" font-size="14" id="6" rect="(216.0, 50.0, 150.0, 69.0)" type="text/plain">Find clusters of cells with similar expression profiles.</text>
		<text font-family="Helvetica" font-size="14" id="7" rect="(392.0, -26.0, 154.0, 124.0)" type="text/html">Project cells into a cell landscape with &lt;i&gt;t-SNE&lt;/i&gt;. Notice the separation into clusters of cells with AML/healthy status.

</text>
		<text font-family="Helvetica" font-size="20" id="8" rect="(562.0, 20.0, 150.0, 32.0)" type="text/plain">(5)</text>
		<text font-family="Helvetica" font-size="14" id="9" rect="(595.0, 21.0, 169.0, 60.0)" type="text/html">Select cells in &lt;i&gt;t-SNE&lt;/i&gt; and observe distribution of cell types in &lt;i&gt;Box Plot&lt;/i&gt;. </text>
		<text font-family="Helvetica" font-size="14" id="10" rect="(581.0, 100.0, 150.0, 110.0)" type="text/html">Change the selection of the Variable in &lt;i&gt;Box Plot&lt;/i&gt; to examine cluster-specific gene expression.</text>
		<text font-family="Helvetica" font-size="14" id="11" rect="(527.2727272727273, 253.63636363636357, 170.0, 110.0)" type="text/plain">Analyze clusters by finding cluster-specific, highly expressed genes.

Search for known cell types with the help of Gene Ontology terms.</text>
		<text font-family="Helvetica" font-size="20" id="12" rect="(497.27272727272725, 253.63636363636363, 74.5454545454545, 56.363636363636374)" type="text/plain">(6)</text>
	</annotations>
	<thumbnail />
	<node_properties>
		<properties format="pickle" node_id="0">gAN9cQAoWAsAAABhdXRvX2NvbW1pdHEBiFgSAAAAY29udHJvbEFyZWFWaXNpYmxlcQKIWA0AAABs
[encoded data, 76137 characters]
</properties>
		<properties format="pickle" node_id="1">gAN9cQAoWAsAAABhdXRvX2NvbW1pdHEBiFgOAAAAY29sb3JfYnlfY2xhc3NxAohYEgAAAGNvbnRy
[encoded data, 24409 characters]
AABJRHIMBAAASwNYBwAAAEJhcmNvZGVyDQQAAEsDdXViYXUu
</properties>
		<properties format="pickle" node_id="2">gAN9cQAoWAsAAABhdXRvX2NvbW1pdHEBiFgHAAAAY29tcGFyZXECSwJYEgAAAGNvbnRyb2xBcmVh
[encoded data, 73766 characters]
AAB0c25lLXlyBgwAAEsCdXViZXUu
</properties>
		<properties format="literal" node_id="3">{'auto_commit': True, 'controlAreaVisible': True, 'header_state': b'\x00\x00\x00\xff\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x01\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\xdd\x00\x00\x00\x08\x01\x01\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00d\xff\xff\xff\xff\x00\x00\x00\x81\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00!\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00d\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x03\xe8\x00\x00\x00\x00d', 'savedWidgetGeometry': b'\x01\xd9\xd0\xcb\x00\x02\x00\x00\x00\x00\x034\x00\x00\x01\x87\x00\x00\x06\xb7\x00\x00\x03\xf4\x00\x00\x034\x00\x00\x01\x9d\x00\x00\x06\xb7\x00\x00\x03\xf4\x00\x00\x00\x00\x00\x00\x00\x00\n\x00', 'selected_id': 'aml-1k.pickle', 'splitter_state': b'\x00\x00\x00\xff\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x01,\x00\x00\x00\xc8\x01\xff\xff\xff\xff\x01\x00\x00\x00\x02\x00', '__version__': 1}</properties>
		<properties format="pickle" node_id="4">gAN9cQAoWAsAAABhdXRvX2NvbW1pdHEBiFgSAAAAY29udHJvbEFyZWFWaXNpYmxlcQKIWBMAAABz
[encoded data, 23947 characters]
AEJhcmNvZGVyBgQAAEsDdXViYXUu
</properties>
		<properties format="pickle" node_id="5">gAN9cQAoWAsAAABhdXRvX2NvbW1pdHEBiVgSAAAAY29udHJvbEFyZWFWaXNpYmxlcQKIWBkAAABj
[encoded data, 25872 characters]
dGVyclEEAABLAXV1YmF1Lg==
</properties>
	</node_properties>
	<session_state>
		<window_groups />
	</session_state>
</scheme>
