update

ChangeLog.md

@@ -1,4 +1,4 @@
-- 1.3.7.3
+- 1.3.7.3-4
    * Added option of the fixed random seed (option *random_state*) for the whole prcessing pipeline
 
 - 1.3.7.2

DigitalCellSorter/__main__.py

@@ -4,53 +4,53 @@
 import DigitalCellSorter
 
 if __name__ == '__main__':
-    ans = input('This will execute the demo of DCS. Continue?(y/n): ')
+    print('Demo of DCS\n')
 
-    if ans in ['y', 'yes', 'Y']:
-        metadata = '''    Data used in this demo:
-        Downloaded from https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.1.0/manual_5k_pbmc_NGSC3_ch1
-        Peripheral blood mononuclear cells (PBMCs) from a healthy donor - Manual (channel 1)
-        Single Cell Gene Expression Dataset by Cell Ranger 3.1.0
-        PBMCs isolated and cryopreserved by AllCells. PBMCs are primary cells with relatively small amounts of RNA (~1pg RNA/cell).
-        Libraries were prepared following the Chromium Single Cell 3' Reagent Kits v3.1 User Guide (CG000204 RevD). 
-        8 libraries were prepared on 1 chip. This is channel 1 of the chip.
-        5000 cells targeted, 4339 cells detected
-        Sequenced on Illumina NovaSeq with approximately 52296 reads per cell
-        28bp read1 (16bp Chromium barcode and 12bp UMI), 91bp read2 (transcript), and 8bp I7 sample barcode
-        Published on February 28, 2020\n'''
-
-        print(metadata)
-
-        # Get the data. The file will be downloaded from github if not found locally
-        try:
-            filePath = os.path.join('data', 'manual_5k_pbmc_NGSC3_ch1.gz')
-
-            if not os.path.exists('data'):
-                os.makedirs('data')
-
-            if not os.path.isfile(filePath):
-                print('Downloading data file')
-                urllib.request.urlretrieve('https://github.com/sdomanskyi/DigitalCellSorter/raw/master/data/manual_5k_pbmc_NGSC3_ch1.gz', filePath)
-        except Exception as exception:
-            print('Could not download the file\n', exception)
-            exit()
-        else:
-            df_data = pd.read_pickle(filePath)
-
-        # Set up a copy of Digital Cell Sorter
-        DCS = DigitalCellSorter.DigitalCellSorter(dataName='PBMC5k', geneListFileName='CIBERSORT_LM22_14', verbose=2, random_state=42)
-        DCS.saveDir = 'output demo 5k'
-
-        # Process the data, annotate cell types and make plots
-        DCS.prepare(df_data)
-        DCS.process()
-        DCS.annotate()
-        DCS.visualize()
-
-        # Do additional analysis and plots
-        DCS.makeIndividualGeneTtestPlot('CD4')
-        DCS.makeIndividualGeneExpressionPlot(['CD19', DCS.getHugoName('CD56'), DCS.getHugoName('CD16'), 'CD4', 'CD8A', 'CD8B', 'CD33'])
-        DCS.makeSankeyDiagram(DCS.getCountsDataframe(DCS.loadAnnotatedLabels(), DCS.loadAnnotatedLabels(infoType='batch')))
-        DCS.makeMarkerExpressionPlot(fontscale=0.8)
-        DCS.makeHopfieldLandscapePlot(plot3D=True)
-        DCS.makeAnomalyScoresPlot()
+    metadata = '''    Data used in this demo:
+    Downloaded from https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.1.0/manual_5k_pbmc_NGSC3_ch1
+    Peripheral blood mononuclear cells (PBMCs) from a healthy donor - Manual (channel 1)
+    Single Cell Gene Expression Dataset by Cell Ranger 3.1.0
+    PBMCs isolated and cryopreserved by AllCells. PBMCs are primary cells with relatively small amounts of RNA (~1pg RNA/cell).
+    Libraries were prepared following the Chromium Single Cell 3' Reagent Kits v3.1 User Guide (CG000204 RevD). 
+    8 libraries were prepared on 1 chip. This is channel 1 of the chip.
+    5000 cells targeted, 4339 cells detected
+    Sequenced on Illumina NovaSeq with approximately 52296 reads per cell
+    28bp read1 (16bp Chromium barcode and 12bp UMI), 91bp read2 (transcript), and 8bp I7 sample barcode
+    Published on February 28, 2020\n'''
+
+    print(metadata)
+
+    # Get the data. The file will be downloaded from github if not found locally
+    try:
+        filePath = os.path.join('data', 'manual_5k_pbmc_NGSC3_ch1.gz')
+
+        if not os.path.exists('data'):
+            os.makedirs('data')
+
+        if not os.path.isfile(filePath):
+            print('Downloading data file')
+            urllib.request.urlretrieve('https://github.com/sdomanskyi/DigitalCellSorter/raw/master/data/manual_5k_pbmc_NGSC3_ch1.gz', filePath)
+    except Exception as exception:
+        print('Could not download the file\n', exception)
+        exit()
+    else:
+        df_data = pd.read_pickle(filePath)
+
+    # Set up a copy of Digital Cell Sorter
+    DCS = DigitalCellSorter.DigitalCellSorter(dataName='PBMC5k', geneListFileName='CIBERSORT_LM22_14', 
+                                                availableCPUsCount=1, verbose=2, random_state=42)
+    DCS.saveDir = 'output demo 5k'
+
+    # Process the data, annotate cell types and make plots
+    DCS.prepare(df_data)
+    DCS.process()
+    DCS.annotate()
+    DCS.visualize()
+
+    # Do additional analysis and plots
+    DCS.makeIndividualGeneTtestPlot('CD4')
+    DCS.makeIndividualGeneExpressionPlot(['CD19', DCS.getHugoName('CD56'), DCS.getHugoName('CD16'), 'CD4', 'CD8A', 'CD8B', 'CD33'])
+    DCS.makeSankeyDiagram(DCS.getCountsDataframe(DCS.loadAnnotatedLabels(), DCS.loadAnnotatedLabels(infoType='batch')))
+    DCS.makeMarkerExpressionPlot(fontscale=0.8)
+    DCS.makeHopfieldLandscapePlot(plot3D=True)
+    DCS.makeAnomalyScoresPlot()

setup.py

@@ -12,7 +12,7 @@
 setup(
     name='DigitalCellSorter',
     packages=find_packages(),
-    version='1.3.7.3',
+    version='1.3.7.4',
     description='Toolkit for analysis and identification of cell types from heterogeneous single cell RNA-seq data',
     long_description_content_type="text/markdown",
     long_description=long_description,