Visualization

>>>scatter(data, dimension="2D", point_size=3, sty='default',
... label=None, title=None, alpha=None, aes_label=None
... )
>>>plt.show()

This function is to plot scatter plot of embedding points of single cell data. Scatter plot of either two-dimensions or three-dimensions will be generated.

• data (numpy.array): A numpy array which has 2 or 3 columns, every row represent a point.

• dimension (str): Specifiy the dimension of the plot, either “2D” or “3D”. Default: “2D”.

• point_size (float): Set the size of the points in scatter plot. Default: 3.

• sty (str): Styles of Matplotlib. Default: ‘default’.

• label (list or None): specifiy the label of each point. Default: None.

• title (str): Title of the plot. Default: None.

• alpha (float): The alpha blending value. Default: None.

• aes_label (list): Set the label of every axis. Default: None.

“scHiCTools” also support interactive scatter plot which require the module ‘plotly’

>>>interactive_scatter(loaded_data, data, out_file, dimension='2D', point_size=3,
... label=None, title=None, alpha=1, aes_label=None)

This function is to generate an interactive scatter plot of embedded single cell data. The plot will be stored in a file.

• schic (scHiCs): A scHiCs object.
• data (numpy.array): A numpy array which has 2 or 3 columns, every row represent a point.
• out_file (str): Output file path.
• dimension (str): Specifiy the dimension of the plot, either “2D” or “3D”. The default is “2D”.
• point_size (float): Set the size of the points in scatter plot. The default is 3.
• label (list or None): Specifiy the label of each point. The default is None.
• title (str): Title of the plot. The default is None.
• alpha (float): The alpha blending value. The default is 1.
• aes_label (list): Set the label of every axis. The default is None.