Examples by Tasks

All implemented modes are associated with examples, check “pyEnGNet examples” for more information.

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Run on CPU

“tests/test_integration/test_cpu.py” demonstrates the basic API for the generation of co-expression gene networks using CPUs.

1. Load gene co-expression dataset from input file

   from pyengnet.File import File
   
   dataset = File.load(path=os.getcwd()+"/datasets/Spellman.csv", separator=",", nmi_th=0.6, spearman_th=0.7, kendall_th=0.7, readded_th=0.7, hub_th = 3)
   

2. Run pyEnGNet based on CPUs.

   from pyengnet.Engnet import Engnet
   
   graphFiltered, infoGraphFiltered, graphComplete, infoGraphComplete = Engnet.process(dataset, saveComplete = True)
   

3. Save gene co-expression networks output (optional)

   from pyengnet.File import File
   
   File.saveFile(path='/home/user/Desktop/graphComplete.csv',graph=infoGraphComplete)
   File.saveFile(path='/home/user/Desktop/graphFiltered.csv',graph=infoGraphFiltered)
   

4. Print gene co-expression networks output (optional)

   from pyengnet.File import File
   
   File.showGraph(graph=graphComplete,title='Complete graph')
   File.showGraph(graph=graphFiltered,title="Filtered graph")
   

Run on GPU devices

“tests/test_integration/test_gpu.py” demonstrates the basic API for the generation of co-expression gene networks using GPU devices.

1. Load gene co-expression dataset from input file

   from pyengnet.File import File
   
   dataset = File.load(path=os.getcwd()+"/datasets/Spellman.csv", separator=",", nmi_th=0.6, spearman_th=0.7, kendall_th=0.7, readded_th=0.7, hub_th = 3)
   

2. Run pyEnGNet based on CPUs.

   from pyengnet.Engnet import Engnet
   
   graphFiltered, infoGraphFiltered, graphComplete, infoGraphComplete = Engnet.process(dataset, saveComplete = True, numGpus = 2, computeCapability = 61)
   

3. Save gene co-expression networks output (optional)

   from pyengnet.File import File
   
   File.saveFile(path='/home/user/Desktop/graphComplete.csv',graph=infoGraphComplete)
   File.saveFile(path='/home/user/Desktop/graphFiltered.csv',graph=infoGraphFiltered)
   

4. Print gene co-expression networks output (optional)

   from pyengnet.File import File
   
   File.showGraph(graph=graphComplete,title='Complete graph')
   File.showGraph(graph=graphFiltered,title="Filtered graph")