clarite.plot.manhattan(dfs:Dict[str, pandas.core.frame.DataFrame], categories:Dict[str, str]={}, num_labeled:int=3, label_vars:List[str]=[], figsize:Tuple[int, int]=(12, 6), dpi:int=300, title:Union[str, NoneType]=None, figure:Union[figure, NoneType]=None, colors:List[str]=['#53868B', '#4D4D4D'], background_colors:List[str]=['#EBEBEB', '#FFFFFF'], filename:Union[str, NoneType]=None)

Create a Manhattan-like plot for a list of EWAS Results

dfs: DataFrame

Dictionary of dataset names to pandas dataframes of ewas results (requires certain columns)

categories: dictionary (string: string)

A dictionary mapping each variable name to a category name

num_labeled: int, default 3

Label the top <num_labeled> results with the variable name

label_vars: list of strings, default empty list

Label the named variables

figsize: tuple(int, int), default (12, 6)

The figure size of the resulting plot in inches

dpi: int, default 300

The figure dots-per-inch

title: string or None, default None

The title used for the plot

figure: matplotlib Figure or None, default None

Pass in an existing figure to plot to that instead of creating a new one (ignoring figsize and dpi)

colors: List(string, string), default [“#53868B”, “#4D4D4D”]

A list of colors to use for alternating categories (must be same length as ‘background_colors’)

background_colors: List(string, string), default [“#EBEBEB”, “#FFFFFF”]

A list of background colors to use for alternating categories (must be same length as ‘colors’)

filename: Optional str

If provided, a copy of the plot will be saved to the specified file



>>> clarite.plot_manhattan({'discovery':disc_df, 'replication':repl_df}, categories=data_categories, title="EWAS Results")